March 2024 - Page 4 of 6 - Online Manipal

Marketing jobs after a BA degree

An online Bachelor of Arts (BA) degree can be your launchpad to propel you into a dynamic world of marketing. The journey from a BA to a marketing career involves more than just crossing a graduation threshold. It involves harnessing a diverse set of transferable skills and a keen understanding of the evolving business scenario.

With an online BA degree from a top-class university, an individual can kickstart a flourishing career in marketing. This three-year undergraduate course helps BA graduates demonstrate their creativity and compelling marketing skills through communication, critical thinking, research, and analytical skills across various job roles in the marketing sector.

Want to learn more about the best marketing career opportunities for BA graduates in today’s business landscape? Then, read this article, where we will acquaint you with the best marketing career options for online BA graduates.

Understanding marketing: Skills & knowledge required

An online Bachelor of Arts (BA) degree acts as a comprehensive training ground for skills crucial in the fast-paced world of marketing. Students take part in various discussions, do presentations, and network with others globally. All these help them make a mark for themselves in bright career paths in the marketing industry.

Listed below are the key skills and qualifications for marketing jobs that can make an online BA graduate the best candidate for a variety of job roles:

Written and verbal communication skills: A Bachelor of Arts graduate possesses excellent written and verbal communication skills. These skills help craft compelling messages to attract the target audience during marketing campaigns and strategies.

Great proficiency for research: Throughout the BA course, students are required to conduct research on various topics. This makes them skilled enough to analyze market trends and competitive landscapes and show their worth in the marketing sector.

Critical thinking skills: Students are instilled with critical thinking abilities during the online BA degree program from Sikkim Manipal University via the Online Manipal platform. Their ability to think critically makes them apt for undergoing strategic decision-making required in several marketing jobs.

Interdisciplinary knowledge: Since BA education is often a mixed frame of various disciplines, it fosters an individual’s holistic understanding of society, literature, culture, and business. Based on this interdisciplinary knowledge, a BA graduate can easily become part of top-notch marketing careers.

Problem-solving capability: BA graduates also become skilled in solving problems in their day-to-day lives, and this ability makes them ready to dig deep into the marketing world. With a problem-solving mindset, they can address challenges in campaign performance and respond to consumer preferences.

Marketing jobs after BA

An online BA course from Sikkim Manipal University (SMU) can be your stepping stone for great networking and career growth in marketing. This popular UG course equips students with a strong foundation in vivid aspects of marketing. Moreover, during an online BA course, individuals can refine their research, analytical, and communication skills, the three basic skill sets that are always in demand in all in-demand marketing positions.

Feel free to check out the table given below that describes the key roles and responsibilities in entry-level marketing positions for a BA graduate:

*Job Roles*	*Job Description*	*Approximate Salary (per annum)*
Digital Marketing Specialist	Responsible for implementing and optimizing digital marketing campaigns such as online advertising, email marketing, and SEO to boost the online presence	INR 7.5 lakhs per annum
Event Manager	Responsible for planning and executing events, promotional activities, and trade shows to enhance the overall band visibility	INR 7 lakhs per annum
Content Writer	Responsible for creating engaging and informative content for marketing collateral, blogs, and social media to attract the target audiences	INR 6.7 lakhs per annum
Market Research Analyst	Responsible for collecting and analyzing data to provide insights into the latest market trends and consumer behavior	INR 4 lakhs per annum
Social Media Coordinator	Responsible for managing and curating content across popular social media platforms to engage with the target audience	INR 3.2 lakhs per annum

Pursue an online BA from Sikkim Manipal University

Choosing an online BA course from Sikkim Manipal University using the Online Manipal platform is both convenient and flexible in today’s fast-paced world. This online mode of education is at par with the traditional campus way, and the degree earned from the university is UGC-entitled and recognized globally owing to its prestigious Manipal tag. Moreover, when you choose Sikkim Manipal for an online BA program, you get access to a wealth of digital resources, databases, and online libraries to keep yourself well-informed about the latest trends in the marketing sector.

SMU is known for its industry-connected faculty and interactive learning tools like the Learning Management System (LMS), which help students become digitally literate. This further helps them stay aligned with the industry’s increasing reliance on digital channels. Not to forget, Sikkim Manipal University offers an affordable fee structure at no-cost EMI mode, and deserving students also stand a chance to get attractive scholarships to pursue this online degree program.

Conclusion

We assume you are now aware of salaries and benefits in marketing careers after taking an online BA degree course. However, when we say a BA degree helps lay the foundation for a bright career in marketing, we encourage you to pursue it from a reputed institution like Sikkim Manipal University (SMU) via the Online Manipal platform. Counted as the top-most university in North East India, SMU offers an online BA degree program, which is a combination of three main subjects: English, Political Science, and Sociology. Enroll in SMU’s online BA course and become part of the glorious Manipal alumni and open a gateway of marketing opportunities with 100% placement assistance provided by the expert faculty of the university.

Everything you need to know: AI Engineer vs Data Scientist

The technology sphere, which is constantly changing, has brought forth two new and vigorous domains of study: artificial intelligence (AI) and data science. Due to the rapid development of AI and data-driven intelligence, the number of jobs required in the domains is rapidly growing, too.

AI engineering includes designing, testing, and maintaining operating artificial intelligence systems. In contrast, data science is a cross-disciplinary field that stems from an understanding of insights from the provided data.

The rapid digitalization of business and the advent of a large volume of data show that the skills needed to create artificial intelligence systems and extract value from data are in high demand. But what is the difference between the two fields? Let’s find out. This blog delves into the distinctions between AI engineers and data scientists.

Must read: Everything about the future of AI and Data Science

Understanding AI Engineering

AI (artificial intelligence) engineering is a domain that differs from regular engineering in focus (designing, developing, and deploying AI systems). Its key goal is to develop computer systems and devices possessing features that normal human intelligence uses, like sensing, reasoning, perceiving, and learning.

Objectives of AI Engineering:

Generate and optimize algorithms for machine learning applications to run.
Bolster AI applications and systems by incorporating AI technologies, for instance, linguistic processing, computer vision, or speech recognition.

Key Responsibilities and Tasks of AI Engineers:

Collaborate with stakeholders to understand business problems and define AI solutions.
Analyze and explore datasets to identify patterns and trends that inform the development of AI models.

Understanding Data Science

Data science is a multidisciplinary subject that blends techniques from statistics, mathematics, computer science, and domain expertise to facilitate the discovery of significant knowledge and useful information from huge masses of data.

Objectives of Data Science:

Gain insights into the structure and characteristics of the available data.
Identify patterns and trends within the data that may provide valuable information.

Key Responsibilities and Tasks of Data Scientists:

Collect data from several platforms, including databases, APIs, and external datasets.
Clean and pre-process raw data to ensure accuracy and consistency.
Explore and visualize data to identify patterns, outliers, and relationships.

Must read: How Does an MSc in Data Science Help You in the AI Era?

AI Engineer vs. Data Scientist: Key Differences

Focus and Objectives

AI Engineer

Focus: Building and deploying AI systems and applications.

Objectives: Introduce complex mechanisms such as intelligent systems, machine learning models, and applications that can perform tasks without being controlled or guided by humans.

Data Scientist

Focus: Having the information, data can be scanned and insights extracted to make important decisions in the organizational setting.

Objectives: Unveil patterns, trends, and saleable data in large data sets.

Quick read: Why you should become a data scientist?

Skillsets

Skill sets unique to AI engineers and data scientists:

AI Engineer

Strong background in software engineering, machine learning, and AI technologies
Proficiency in various programming languages, for instance, Python, Java, or C++
Experience with high-level deep learning frameworks like Python or TensorFlow

Data Scientist

Skill in functioning with or making statistics, data analysis, and machine learning algorithms
Skills such as Python or R programming environments
Knowledge of pre-processing data, doing EDA, and building predictive models

Tools and Technologies

Technologies and tools commonly used in AI Engineering projects:

Programming Languages	PythonJavaC++
Machine Learning Libraries	TensorFlowPyTorchScikit-Learn
Cloud Platforms	AWSAzureGoogle Cloud Platform

Technologies and methodologies commonly used in Data Science projects:

Programming Languages	PythonR
Data Analysis and Visualization	PandasNumPyMatplotlibSeaborn
Machine Learning Libraries	Scikit-LearnTensorFlowPyTorch

End Goals

AI Engineer: Make artificial intelligence systems capable of doing specific functions without explicit programming.

Data Scientist: Instill effective and responsible data governance practices to maintain performance, continuity, and accountability in the business.

Career paths in AI Engineering and Data Science

Job Roles and Responsibilities in AI Engineering and Data Science

AI Engineering

Roles:

Machine Learning Engineer
AI Research Scientist
Computer Vision Engineer

Responsibilities:

Building and deploying machine learning models.
Developing AI algorithms and applications.

Data Scientist

Roles:

Data Analyst
Data Scientist
Business Intelligence Analyst

Responsibilities:

Interpreting and dealing with multi-faceted datasets.
Build valuable predictive models for business insights.

Educational Background and Skills

AI Engineer

Educational Background: A degree in computer science, mathematics, engineering, or any other related field.

Skills:

A co-op employment experience that culminated in strong programming skills (Python, Java, C++).
Algorithmic understanding of machine learning tools and frameworks.

Data Scientist

Educational Background: A degree in statistics, mathematics, computer science, or science-related fields.

Skills:

In-depth data research and problem-solving.
Programming abilities such as Python or R.

Industry Applications and Opportunities

Industry trends and demand for AI Engineers and Data Scientists:

Role	Industry Applications	Opportunities
AI Engineer	Healthcare: AI for medical image analysis and diagnostics.Finance: Fraud detection and algorithmic trading.	Research and development roles in tech companies.Implementation of AI solutions in various industries.
Data Scientist	Retail: Customer segmentation and demand forecasting.Healthcare: Predictive analytics for improved patient outcomes.	In-house data science teams in various industries.Consulting roles and providing data-driven solutions.

Challenges and Future Outlook

Challenges faced by AI engineers and data scientists:

Addressing ethical considerations in AI, including bias in algorithms and the responsible use of data.
Facilitating effective collaboration between technical experts, domain specialists, and business stakeholders.

Emerging trends and advancements:

Explainable AI (XAI) is increasing the need for the development of AI systems that are more transparent and interpretable by humans to generate trust among people.
Advancements in deploying AI models on edge devices enable faster and more efficient processing.

MAHE is the best choice for both: AI Engineer or Data Scientist!

Manipal Academy of Higher Education (MAHE) helps youths become experts in artificial intelligence (AI) and data science. MAHE offers the latest syllabi in these fields. The quality of the institution’s top-notch labs and research centers is a crucial factor in shaping students’ learning experiences.

The curriculum is intended to be complete, thus helping the graduates acquire skills and understanding of AI and data science models. It offers an MSc in Data Science, an MSc in Biostatistics, a BTech in Computer Science, a BTech in Artificial Intelligence and Machine Learning, etc.

Conclusion

To sum up, AI engineers and data scientists have similar starting points, with a foundation in data and technology. However, their different job functions make them compulsory professionals in the rapidly changing world of AI and data science. AI engineers create and utilize smart systems focused on solutions and user interaction. In contrast, data scientists concentrate on using data to inform decision-making and business strategies, gathering correct insights from using data. Both occupations offer different ways of careers, and the demand for AI engineers and data scientists is increasing with the development of new technology. Therefore, it plays a vital part in the future development of data-driven innovations in different industries.

Don’t be fooled: A student’s guide to identifying fake universities in India

Earning a degree is a significant investment of time and money. With the growing importance of higher education, unfortunately, so do fake universities. These institutions offer bogus degrees that hold no value, jeopardizing your future career prospects.

This blog empowers you, the student, with a clear checklist to identify fake universities in India, based on the official guidelines from the University Grants Commission (UGC). During the time of online degree programs, it is imperative for each students to use this checklist before enrolling in a program.

The red flags: Identifying fake universities

Here’s what to watch out for:

Non-recognition by UGC: Every legitimate university in India must be recognized by the UGC. Check the official UGC list of recognized universities. If the university you’re considering isn’t listed, it’s a major red flag.

Check out the list of fake universities on UGC portal: UGC has compiled full list of fake universities on its website. On this page, you will get state-wise details of fake universities. If the university you are planning to take admission in this list, please stop further processes.

Unrealistic promises: Beware of universities promising instant admissions, guaranteed placements, or degrees without rigorous coursework. Legitimate universities have established admission processes, academic standards, and placement processes.

Misleading website and infrastructure: A professional website with clear information about faculty, courses, and accreditation is a good sign. Be wary of poorly designed websites with limited information or those claiming affiliation with prestigious institutions they’re not associated with. If possible, visit the university physically. A dilapidated campus or lack of proper infrastructure can be a warning sign.

Unconventional modes of communication: Legitimate universities typically have official communication channels like email addresses with their domain name. Beware of universities relying solely on phone calls or text or WhatsApp/Telegram messages for communication.

Exorbitant fees and payment methods: While costs vary, be wary of universities demanding exceptionally high fees or pressuring you into unusual payment methods, like cash deposits.

If you would like to know more about the higher education in India, read this insightful blog on the state of higher education in India.

Beyond the checklist: Additional tips

Research the faculty: Look for universities with qualified and experienced professors with published research.
Check student reviews: While online reviews can be subjective, reading student testimonials can offer valuable insights.
Contact the UGC directly: If you have any doubts, reach out to the UGC helpline or email them for verification.
Use search engines or social media: You will get more details related to the universities on search engine such as Google, Bing, Yahoo etc. Use the search terms such as “is the xyz university legit” or “value of xyz university”. This will give you thousands of responses from various sources, including forums such as Quora, aggregators, social media posts, YouTube videos and many more.

You can find out more about the importance of DEB ID in online education.

Are online programs from Indian universities fake?

No, not all online programs from Indian universities are fake. However, there are some fake universities operating in India, so it’s important to be cautious before enrolling in an online program. Here are the tips for choosing legitimate online programs:

UGC Regulations: Since 2020, India allows recognized universities to offer online degrees under regulations set by the University Grants Commission (UGC). These universities must meet specific criteria like accreditation and ranking.
- Verification: Ensure status of Higher Educaton Institutions (HEIs) at respective UGC pages. UGC has issued a public notice with precautions to take before admitting to online mode –

Recognition status of HEIs: The year-wise and academic session-wise status of HEIs recognized to offer programs through Open and Distance Learning mode and/or Online mode is available on UGC website.

ii) Entitlement status of HEIs: The list of HEIs Entitled to offer programs in ODL mode and/or online mode with names of programs is available on UGC-DEB website.

iii) Please read notifications at Notice Board before taking admission. The notifications can also be accessed here as well.

Check university website: Look for information on the university website about the online program, including accreditation details and faculty credentials. For example, Online Manipal is the digital home of Manipal Universities, which features online programs offered by the prestigious universities under Manipal group. On this website, you will get all details regarding each program including fees, eligibility, accreditations & rankings, scholarship details, besides a large resource of blogs.

Reviews: Research online reviews (with caution) on platforms known for reliability. Look for consistent themes rather than individual experiences.

Check out: How worthwhile is Online Manipal for online education?

Additional resources:

UGC Website: https://www.ugc.gov.in/
UGC Helpline: 1800-111-656

Remember: Don’t be afraid to ask questions! A legitimate university will be happy to address your concerns and provide clear information.

Conclusion

In conclusion, the ever-expanding online education landscape in India offers exciting possibilities for students seeking flexibility and convenience. However, staying vigilant against fake universities disguising themselves is crucial. By wielding the information in this blog and conducting thorough research, you can confidently embark on your online learning journey with a recognized university and a legitimate degree program. Remember, a little extra effort now can safeguard your educational investment and open doors to a brighter future. Let’s work together to ensure online education empowers students, not exploits them.

Business analytics career after engineering

Business analytics implies dealing with data analysis to get insights that directly influence key business decisions and strategies. It is carried out via various tools, such as statistical analysis, predictive modeling, data mining, and others, to extract valuable information from vast data sources. Organizations can enhance operations optimization, identify trends, forecast future results, and reduce risks by deploying data analytics tools and methods.

Technological advancements have enabled the continuous increase in data generated by businesses, which, together with the need for skilled professionals in the field. Through this blog, we close the gap between business analytics roles and engineering graduates and find lucrative career opportunities in Business Analytics after engineering.

Understanding business analytics

Business analytics is a process of examining an organization’s data and deriving useful information to support decision-making. It includes using descriptive statistics, data mining, predictive modeling, and numerical approaches to find connections, trends, and patterns in data.

Key concepts and methodologies used in Business Analytics:

Descriptive Analytics: This concept mainly uses data visualization, dashboards, and key performance indicators (KPIs) to showcase information in a decent and understandable format.
Predictive Analytics: Predictive analytics employs historical data and mathematical models to predict what will happen in the future.
Prescriptive Analytics: Prescriptive analytics is not limited to predicting outcomes with data; instead, it can prescribe actions that would lead to optimal results.

Industry applications and demand for Business Analytics in engineering:

Retail: Shops employ business analytics to forecast consumer behavior and average sales, improve the quality of inventory, and develop marketing strategies to suit customer demands and preferences.
Healthcare: In healthcare, business analytics are used to improve patient outcomes and hospital operations.
Finance: The financial sector utilizes data analysis to determine credit risk, detect fraud, and raise returns on their investments.

Why consider a career in business analytics after engineering?

There are many benefits of opting for business analytics after engineering. The following are a few transferable skills from engineering:

Analytical Skills: Engineering graduates are known as analytical professionals who develop their skills through engineering coursework and problem-solving. These skills are also used in business analytics, where professionals perform data analysis to gain meaningful intelligence.
Quantitative Skills: Engineering education includes mathematical and quantitative reasoning, which are key for performing statistical analysis and creating predictive models.
Technical Proficiency: Graduates of engineering have a background in computer languages, data visualization tools, and statistical software. This knowledge is helpful in business analytics.

Business analytics collaborates with experts and professionals from different areas, such as marketing, finance, operations, and supply chain management. Engineers can utilize their unique skill sets to work in various departments of the organization and contribute to solving complex business problems.

As data-driven decision-making becomes more and more reliant, organizations constantly search for talented people who can be the main characters in the process of translating data into actionable business insights.

Roles in a Business Analytics Career

Business Analyst

Data Analyst

Data Scientist

Business Intelligence Analyst

Quick read: Who should do an MSc in Business Analytics?

Steps to transition into a business analytics career

Assess Existing Skills and Knowledge

Evaluate your current skill set, including quantitative abilities, programming proficiency, and analytical thinking skills gained from your engineering education.
Identify relevant coursework, projects, or experiences that demonstrate your analytical capabilities and problem-solving skills.

Identify Areas of Interest Within Business Analytics

Explore different roles and domains within business analytics, such as data analysis, data science, business intelligence, or predictive modeling.

Acquire Necessary Skills Through Additional Coursework or Self-Study

Identify the specific skills and tools required for your desired role in business analytics, such as programming languages (e.g., Python, R, SQL), statistical techniques, machine learning algorithms, and data visualization tools.
Enroll in online courses, boot camps, or certification programs to learn new skills or enhance existing ones.

Build a Portfolio Showcasing Analytical Projects and Achievements

Develop analytical projects that demonstrate your ability to apply data analysis techniques to real-world problems.
Showcase your projects through a portfolio website, GitHub repository, or online platform to highlight your skills, methodologies, and outcomes.

Network and Seek Mentorship Opportunities in the Field

Attend industry events, networking meetups, and professional conferences to connect with professionals working in business analytics.
Join online communities, forums, or LinkedIn groups related to business analytics to engage with peers, share knowledge, and seek advice.

Skill set required for transitioning to Business Analytics

Technical Skills	Soft Skills
Statistical analysis tools–R and Python	Critical thinking and problem-solving abilities
Data manipulation and visualization skills–Pandas in Python and Matplotlib/ggplot2	Effective communication and presentation skills
Database querying and management–SQL (Structured Query Language)	Collaboration and teamwork

Job roles and responsibilities in Business Analytics

Career Path	Roles and Responsibilities
Entry-Level Roles	Data Analysis and ReportingAssisting with analytical projects under the guidance of senior team members
Specialization Areas	Marketing AnalyticsFinancial AnalyticsSupply Chain Analytics
Advancement Opportunities	Senior Business AnalystData ScientistAnalytics Manager/DirectorChief Data Officer (CDO)

Resources for further learning and development

Online Courses and Tutorials:

Coursera: Offers a wide range of courses in business analytics, data science, and related topics taught by leading universities and instructors.
Udemy: Provides affordable courses on business analytics tools, techniques, and methodologies, suitable for beginners and experienced professionals alike.

Books and Academic Resources:

“Data Science for Business” by Foster Provost and Tom Fawcett: A comprehensive guide that introduces business analytics concepts and techniques, focusing on practical applications and case studies.

Professional Certifications and Training Programs:

Certified Analytics Professional (CAP): Offered by the Institute for Operations Research and the Management Sciences (INFORMS), CAP certification validates proficiency in analytics concepts, methodologies, and tools.
Microsoft Certified: Azure Data Scientist Associate: This course validates skills in designing and implementing machine learning models on Microsoft Azure, a popular cloud platform for data analytics.

For you: Why is the MSC in Business Analytics best done with Online Manipal?

Excelling in Business Analytics with MAHE

Manipal Academy of Higher Education (MAHE) provides a comprehensive platform for individuals looking to excel in the field of business analytics and successfully chart their career paths. The curriculum covers a wide range of topics, including statistical analysis, data mining, machine learning, and business intelligence.

MAHE emphasizes hands-on learning and practical experience, offering students opportunities to apply theoretical concepts to real-world problems. It also covers career counseling, resume writing workshops, mock interviews, and job placement assistance, ensuring that students are well-prepared to pursue rewarding careers in business analytics upon graduation.

Conclusion

In conclusion, transitioning into a business analytics career after engineering offers a promising pathway for individuals looking to leverage their analytical prowess and technical skills in a dynamic and data-driven field. With the growing demand for professionals skilled in data analysis and decision-making, engineering graduates are well-positioned to excel in roles ranging from data analysts to business intelligence managers.

Role of Supply Chain Management in healthcare sector

For most businesses, ensuring that products reach customers is a significant goal, but in healthcare, it’s vital because lives hinge on receiving supplies and medications promptly. Providing quality patient care swiftly is essential, as underscored by the recent COVID-19 pandemic.

Effective connections and communications among suppliers, manufacturers, and distributors are necessary to streamline the flow of goods, services, and information. This enables hospitals and other healthcare facilities to more effectively address patient requirements and enhance their financial outcomes.

Why supply chain management in healthcare?

Healthcare supply chain management is a collection of processes, teams, and the transportation of medicines, medical tools, and other products required by healthcare professionals to execute their jobs.

Another goal of supply chain management in the healthcare industry is to identify departmental weaknesses and provide prevention solutions. It tries to identify weak areas to attain desired health outcomes and to improve global health investments.

When companies use digital tools and technology to manage healthcare supply chains, they use actionable insights from multi-source data to alter and enhance supply chain structures and operations continuously.

Benefits of supply chain management in healthcare

Following are some of the benefits of supply chain management in healthcare.

Reduce operational costs

Medical producers rely on supply chain managers to design networks that match customer objectives at the lowest possible overall cost. Efficient logistics enable medical enterprises to compete more effectively in the marketplace.

Healthcare organizations are occasionally overcharged due to pricing fluctuations and errors made when deliveries are delayed, adding to unanticipated shortages and insufficient inventory controls.

Better processes

Some of the biggest problems in healthcare logistics are keeping devices working and clean, getting rid of waste, storing and keeping track of inventory, and shipping. When faced with issues such as a lack of suitable storage space, rising labor prices, and typical tedious techniques, it is the greatest alternative solution with solid logistics and supply chain management.

Help in automation

Supply chain software simplifies and automates typical manual procedures carried out inside healthcare organizations with the simple goal of enhancing the supply chain process. One of the numerous benefits of software automation is its capacity to streamline inventory, decrease waste, enable quick, data-driven choices, and save labor, supply, and operational costs.

For these reasons, enlisting the assistance of supply chain software development organizations is becoming increasingly important.

Gives a competitive advantage

Digitizing the supply chain makes it possible for healthcare providers to get the exact product to the patient at the right time and at a low cost.

Healthcare providers will be better placed to take advantage of technological developments in the data flow, analytics, provider-patient interaction, asset monitoring, and regulatory requirements by establishing a digital supply chain, which also implies that the future of healthcare is digital.

Improve the three C’s

Supply chain management focuses on enhancing the three Cs: communication, collaboration, and coordination between vendors, suppliers, transportation firms, and shipping organizations.

Supply chain management employs a centralized distribution approach, ensuring reliability for end users and providing correct output results. For more information, see our blog on the importance of vendor management.

Increased transparency

Logistics is an important component of supply chain management, with duties such as developing precise systems to plan and coordinate the complex movement of goods by delivering timely, safe, and dependable shipments.

Day-to-day logistics services vary depending on the business but often include order processing, warehousing, and, last but not least, shipping.

In addition to these items, logisticians provide data summaries to supply chain partners to improve the visibility of commodities as they transit from point A to point B. Logistics partners should improve transparency by coordinating live tracking updates and establishing open communication channels to increase customer service. Learn more about the importance of logistics in the retail industry.

Aids in demand forecasting

They may use healthcare supply chain analytics to estimate demand correctly, improve stock planning and management, and respond more quickly to changing market conditions by combining supply chain and clinical data.

Digital supply chain management technologies can assist raise productivity and reducing time to market by fostering improved communication and cooperation throughout the healthcare supply chain.

They help to develop a healthcare value chain that can respond directly to and recover from the difficulties of future pandemics and other public health catastrophes by enhancing confidence and openness across the supply network.

Challenges in healthcare supply chain management

The intricacy of the healthcare supply chain is compounded by factors like product diversity, fluctuating demand patterns, strict regulatory mandates, and the imperative for precise inventory control. Access to accurate and timely data is crucial for effective decision-making and optimizing inventory.

Challenges within the healthcare supply chain often revolve around issues such as managing inventory, predicting demand, controlling costs, and ensuring product quality and safety standards. Shortages, stockouts, or disruptions in the supply chain can significantly impact patient care, leading to treatment delays or limitations.

Supply Chain Management SCM in healthcare – best practices

The best practices listed below, with examples, can help anyone prevent mistakes and make the right choices:

Inventory management

You must ensure that your materials department orders the correct volume of supplies to match the volume used by your personnel. There shouldn’t be surplus material ordered based on someone’s gut instinct, and all of this occurs without risking the safety of your patients.

Centralize and categorize storage

Streamline supply management by implementing an automated inventory system to enhance efficiency and precision. Allocate specific storage spaces for medical equipment and supplies, ensuring convenient access for staff. Classify inventory according to product type, expiration dates, and usage frequency to streamline retrieval and minimize the likelihood of expired or misplaced items. Enforce a first-in, first-out (FIFO) and last-in, first-out (LIFO) method to maintain proper rotation and maximize inventory usage.

The advancement of technology

Organizations worldwide have been able to adjust their services with cutting-edge technology, solutions, and resources. Globally, supply chain management has grown in popularity as firms integrate their essential business activities from beginning to end.

For example, E-procurement and sophisticated supply chain planning systems have been released as advanced software and solutions. These software solutions have many applications in the healthcare supply chain management system. They can be utilized at numerous stages of the supply chain management process, including procurement, manufacturing, transportation, and storage.

Adopting cloud-based solutions

Cloud-based systems have several advantages, including reducing capital and running costs. The system requires no hardware or IT infrastructure, allowing businesses to optimize supply chain operations while avoiding capital expenses.

Furthermore, these solutions aid in consolidating various systems, such as warehouse management systems and transportation cost management, which are crucial for supply chain operations. Cloud technology assists healthcare businesses in coordinating and consolidating information with particular solutions to avoid miscommunications and lost savings.

Cloud computing also offers benefits to Small and Medium-sized Enterprises (SMEs) and on-premise IT systems, such as cost-effectiveness and the ability to minimize the total cost of ownership through pay-per-use. As a result of the benefits associated with this technology, healthcare systems worldwide have begun to incorporate cloud-based solutions in their supply chain operations.

It’s critical to understand what’s going on in your materials department. Any adjustments that need to be made should be executed as soon as possible so that savings can be realized. The materials portion of the supply chain can be leaner.

Supply chain job roles in healthcare

The healthcare industry is booming and there are a plethora of job opportunities to explore. Here is the list of the job roles in supply chain management in the healthcare industry:

Jobs	Salary
Supply Chain Manager	INR 17 LPA
Supply Chain Executive	INR 4.5 LPA
Supply Chain Analyst	INR 6.5 LPA
Associate Supply Chain Manager	INR 13.3 LPA

Conclusion

Supply chain management in the healthcare industry has shown to be a game changer, assisting healthcare providers in enhancing the patient experience, reducing manual errors in everyday business processes, optimizing inventory, and automating departmental activities.

As you are aware, supply chain management is a key function in the healthcare industry, and if you want to follow a profession in this field, Manipal Academy of Higher Education (MAHE) is the best option. Through Online Manipal, MAHE provides the best supply chain management course and an MBA in healthcare management, that allows you to pursue your interest in supply chain management.

This course gives a foundational understanding of supply chain management, the underlying pressures confronting managers today, and the solutions available to assist in dealing with the day-to-day issues of sustaining hospital and medical practice operations.

So, what are you holding out for? Apply for your favorite program on the Online Manipal website to learn hospital planning, a larger vision of healthcare management, and finally, to strengthen your communication abilities.

AI Engineer: Scope, job description, skills, salary, and more

In the fast-paced world of technology, AI engineering is a young and promising field with great prospects and importance. AI engineers are one of the key drivers in creating intelligent systems that utilize natural language processing and computer vision to enhance human capabilities and reinvent operations.

To succeed in this domain, you must have a diverse set of skills, which entails mastery of programming languages such as Python, competence in machine learning frameworks, and a firm understanding of mathematics and statistics. Good problem-solving skills and the ability to handle a large amount of data are a must as well.

The demand for AI engineers is soaring; they get paid from 100,000 to 150,000 US dollars annually, with their experience and location playing a role. AI will keep transforming businesses as people learn about this discipline, with new doors open to exciting careers and possibilities to design the future of technology.

Also read: Interesting predictions on data science trends for 2024 – Online Manipal

Understanding the Scope of AI Engineering

Engineering AI implies developing, creating, and using artificial intelligence systems and solutions to automate tasks and solve challenges in different areas.

In healthcare, AI engineering is employed for medical image analysis, disease diagnosis, drug discovery, and personalized treatment suggestions, which contribute to better care delivery and patient outcomes.
In finance, AI enables algorithmic trading, fraud detection, customer service chatbots, and risk management systems.
In the automotive industry, AI engineering is applied in self-driving cars, predictive maintenance, and vehicle safety, thus paving the way for smart transportation of the new age.

The significance of AI engineering is in its ability to spark innovation across industries through data analytics, automation, and the application of intelligent algorithms. AI makes it possible for organizations to capitalize on its power, increase efficiency, reduce expenses, and achieve a competitive advantage in a quickly changing market environment.

Job Description of an AI Engineer

Developing AI Models: AI engineers design and develop machine learning and deep learning models tailored to specific use cases, such as natural language processing, computer vision, or predictive analytics.
Implementing Algorithms: AI engineers translate algorithms and models into production-ready software solutions. This involves writing code, leveraging frameworks like TensorFlow or PyTorch, and integrating AI components into existing systems or applications.
Data Preparation and Analysis: AI engineers work closely with data scientists to preprocess and analyze data, ensuring its quality, relevance, and suitability for training AI models. They may also be involved in feature engineering, dimensionality reduction, and data augmentation tasks.
Collaboration with Cross-Functional Teams: AI engineers collaborate with cross-functional teams comprising data scientists, software engineers, domain experts, and stakeholders. They participate in brainstorming sessions, data gathering, and solution design discussions to ensure alignment with business objectives and technical feasibility.

Also read: Unleashing the potential of predictive analytics in data science – Online Manipal

Skills Required for AI Engineers

Technical Skills	Soft Skills
Proficiency in programming languages (Python, R, Java)	Problem-solving abilities
Knowledge of machine learning frameworks (TensorFlow, PyTorch, sci-kit-learn)	Effective communication and collaboration skills
Expertise in data preprocessing, feature engineering, and model evaluation	Adaptability and continuous learning mindset

Educational Background and Training

Computer Science or Related Degree: Many AI engineers hold a bachelor’s or master’s degree in computer science, artificial intelligence, machine learning, or a related field.
Mathematics and Statistics: A solid understanding of mathematics, including calculus, linear algebra, probability, and statistics, is essential for AI engineering.
Certifications and Courses: Taking specialized courses and obtaining certifications in artificial intelligence, machine learning, and deep learning can enhance an individual’s skills and knowledge in the field. Online platforms like Coursera, Udacity, and edX offer a wide range of AI-related courses and certification programs.

Also read: Top 10 things recruiters look for in Data Science aspirants – Online Manipal

Salary Trends for AI Engineers

Factors influencing AI engineer salaries:

Experience: Experienced AI engineers with several years of hands-on experience typically command higher salaries than entry-level professionals.
Skills and Expertise: Proficiency in in-demand programming languages, machine learning frameworks, and specialized AI techniques can positively impact salary levels.
Education: Higher education degrees, such as master’s or doctoral degrees in AI-related fields, may lead to higher salary offers.

In the United States, the average annual salary for an AI engineer exceeds 110,000 US dollars. Across the border in Canada, AI engineers can expect an average annual salary of over 85,000 Canadian dollars. Similarly, in Europe, particularly in the UK, the median annual salary for AI engineers is impressively over 60,000 pounds.

City (India)	Average Salary (Annual)
Bangalore	INR 12,00,000
Hyderabad	INR 10,00,000
Mumbai	INR 15,00,000

Source

Entry-level (0-2 years of experience): INR 4-8 lakhs per annum
Mid-level (2-5 years of experience): INR 8-15 lakhs per annum
Experienced (5-10 years of experience): INR 15-30 lakhs per annum
Senior-level (10+ years of experience): INR 30+ lakhs per annum

Career Growth and Opportunities in AI Engineering

AI Researcher

Machine Learning Engineer

Computer Vision Specialist

Deep Learning Engineer

AI engineers can choose to specialize in various subfields, including computer vision, natural language processing, robotics, reinforcement learning, and more.

Emerging trends shaping the future of AI engineering:

Explainable AI: There’s a growing emphasis on developing AI systems that are transparent and interpretable, allowing users to understand the reasoning behind AI decisions.
Ethical AI: With increased concerns about bias, fairness, and accountability in AI systems, there’s a growing demand for AI engineers skilled in designing and implementing ethically responsible AI solutions.

Also read: What is the difference between PGCP data science and MSc data science? – Online Manipal

Challenges and Ethical Considerations

Ethical dilemmas abound in AI development and deployment. AI algorithms may inadvertently perpetuate biases in training data, leading to unfair decisions or discrimination. Moreover, AI systems’ opacity raises concerns about accountability and transparency.

AI engineers can mitigate bias by carefully selecting and preprocessing training data, employing fairness-aware algorithms, and conducting thorough testing and validation. Transparency can be enhanced through model interpretability techniques, allowing stakeholders to understand how AI decisions are made.

How can MAHE help you realize your AI dream?

Manipal Academy of Higher Education (MAHE) offers an MSc Data Science program tailored to aspiring AI engineers. The MSc Data Science program at MAHE provides a comprehensive curriculum covering fundamental concepts in data science, machine learning, and AI. Students gain proficiency in programming languages, statistical analysis, and advanced machine-learning techniques. The program emphasizes ethical considerations, equipping students with the knowledge and skills to navigate the ethical challenges inherent in AI development and deployment.

Conclusion

In conclusion, the scope for AI engineering presents immense opportunities for innovation and societal impact, but it also poses significant ethical challenges. AI engineers play a pivotal role in addressing these challenges by promoting fairness, transparency, and accountability in AI systems. With the support of institutions like MAHE and programs like the MSc Data Science, aspiring AI engineers can acquire the skills and knowledge needed to realize their AI dreams.

Data science career after engineering

The development of technology, emerging along with data, has changed industries, which has supported data science as a trend of innovations. A data science job search will be particularly stimulating for engineering graduates, who often have good problem-solving abilities and advanced analytical thinking skills.

Data science presents engineers with a unique chance to use the advanced math and computation skills that they developed while in academic pursuits and gain deep understandings from huge data pools. The use of data science methodologies in the optimization of manufacturing processes, design of algorithms, and creation of the latest technologies has widened its scope of application in engineering. This blog highlights the opportunities for data science after engineering and the required skills for those who seek engineering data analysis careers.

Must read: Is Data Science a good career option for you?

Understanding data science

Data science is a multidisciplinary field that utilizes aspects of statistics, mathematics, computer science, and domain knowledge to discover insights and knowledge from structured and unstructured data. At its fundamental essence, data science revolves around processing, analyzing, and interpreting massive data to guide decision-making, solve complicated problems, and discover vital trends and patterns.

Some core concepts and techniques utilized in data science include:

Descriptive and Inferential Statistics: Techniques for data summary and interpretation, using skills such as mean, variance, hypothesis testing, and regression analysis.
Machine Learning: Algorithms and models that enable computers to learn from data and make decisions or predictions by themselves without getting explicitly programmed, such as decision trees, support vector machines, and neural networks.
Data Visualization: Developing visual displays of information that foster inquiry, examination, and the demonstration of insights, employing techniques such as charts, graphs, and data visualization.

Industry demand for data science skills in engineering:

Business and Finance: Analysis for predicting customers’ preferences, fraud, risks, and market forecasting for stocks.
Healthcare: EHR, medical imaging, and genetic analysis for medical diagnosis, clinical decisions, and drug research.
Marketing and Advertising: Targeted advertising campaigns, market segmentation, analysis of sentiments in social networks, and personalization of product recommendations.

Why consider a Data Science Career after Engineering?

Consider the skill transition from engineering to data science. Engineers are highly analytical thinkers, problem-solvers, and mathematical whizzes, and, therefore, they perfectly fit in a data science environment. The ability to use the systematic problem-solving approach to build efficient solutions is considered well-transferable to data pre-processing, algorithm development, and model evaluation. Apart from that, as the demand for data-driven insights grows across most industries, so does the need for information specialists who are in short supply.

Moreover, a data science career allows engineers to be involved in interdisciplinary work and bring innovation at the intersection of technology, data, and domain knowledge. By combining their engineering skills and data science practices, professionals can handle complex problems in different areas such as the health sector, finance, transportation, and other fields.

For you: Data science course duration: Become data scientist quickly!

Steps to Transition into a Data Science Career

Assessing Current Skills and Knowledge: Begin by assessing your engineering skills and applying them to data science. These skills would include proficiency in programming languages (e.g., Python, R, SQL), statistical analysis, data manipulation, and problem-solving abilities.
Filling Knowledge Gaps: Identify the gaps in your skill set and knowledge required for data science roles. Utilize online resources such as MOOCs (Massive Open Online Courses), tutorials, textbooks, and boot camps to learn new concepts and techniques.
Building a Portfolio: Choose diverse projects that showcase your ability to collect, clean, analyze, and visualize data to derive actionable insights. Utilize platforms like GitHub to showcase your code and projects, and create a personal website or portfolio to highlight your work.
Networking and Mentorship: Engage with professionals in the data science community through online forums, social media platforms, and networking events. Join data science meetups, workshops, and conferences to expand your network and stay updated on industry trends and best practices.
Tailoring Resumes and Interview Preparation: Customize your resume to highlight relevant skills, experiences, and projects related to data science. Practice technical interview questions, coding challenges, and case studies commonly discussed in data science interviews.

Essential Skills for Data Scientists

Technical Skills	Soft Skills
Proficiency in programming languages (e.g., Python, R)	Problem-solving and analytical thinking
Knowledge of statistics and probability	Effective communication and storytelling
Experience with data manipulation and visualization tools (e.g., Pandas, Matplotlib)	Collaboration and teamwork
Understanding of machine learning algorithms and techniques	Adaptability and continuous learning mindset
Familiarity with databases and SQL

Career Path Options in Data Science

Below are the career paths and growth in Data Science for engineers:

Career Level	Roles
Entry-Level	Data AnalystBusiness Intelligence AnalystJunior Data Scientist
Mid-Level	Data ScientistMachine Learning EngineerData Engineer
Senior-Level	Lead Data ScientistPrincipal Data ScientistChief Data Officer (CDO)
Specialization Areas	Machine Learning EngineerData EngineerData Visualization Specialist

Challenges and Considerations

Lack of Relevant Experience: Engineering graduates may lack direct experience in data science roles, making it challenging to compete in the job market. To overcome this, focus on building a strong portfolio of data science projects through self-study, online courses, and personal projects. Participate in hackathons, Kaggle competitions, or open-source projects to gain practical experience and showcase your skills to potential employers.
Skill Gap: Data science requires proficiency in various technical skills, such as programming, statistics, and machine learning. A basic engineering course may not teach these skills, and the curriculum differs from institution to institution. Identify your skill gaps and develop a personalized learning plan to fill them through online courses, tutorials, and hands-on practice.
Imposter Syndrome: Many individuals transitioning into data science may experience imposter syndrome, feeling inadequate or undeserving of their accomplishments. Remember that it’s normal to feel this way; focus on building confidence in your abilities through continuous learning and practical experience. Surround yourself with supportive peers and mentors who can provide encouragement and guidance along the way.

Data Science with MAHE

Making a successful career in data science with the Manipal Academy of Higher Education (MAHE) involves leveraging the right resources, programs, and opportunities. MAHE offers various postgraduate programs (M.Sc) in Data Science and MSc in Business Analytics etc.

Participating in the institute’s hands-on projects will allow you to apply theoretical concepts to real-world problems, build your portfolio, and gain practical experience. You can also attend career fairs, networking events, and employer talks organized by the university to expand your professional network and explore job opportunities.

Conclusion

In conclusion, a data science career presents an exciting and rewarding pathway for engineering graduates. It helps them apply their analytical skills and technical expertise in a dynamic and rapidly evolving field. With the increasing demand for data-driven insights across industries, the fusion of engineering principles with data science methodologies offers abundant opportunities for innovation, problem-solving, and impactful contributions. Therefore, engineering graduates can embark on a fulfilling journey in data science, driving innovation and making meaningful contributions to the digital economy.

Data Science Course Duration: Become Data Scientist Quickly!

Data science is the study of obtaining valuable information for business decision-making, strategic planning, and other purposes by utilizing cutting-edge analytics tools and scientific concepts. Data science drives organizations into better marketing and sales campaigns and boost operational effectiveness.

Data science is a field that is always evolving. It uses computer science and statistical techniques to gather information and produce insightful forecasts across various sectors. The term “data science” and the discipline have evolved. Recent years have seen a huge increase in popularity due to developments in data gathering, technology, and the mass output of data internationally.

According to Coursera, Data scientist jobs are predicted to rise by 36% between 2021 and 2031. If you are looking to become a data scientist or switch your career to data science, here are some of the top courses you can pursue.

Courses in data science

When pursuing a degree in data science, you will be intrigued by the variety of courses you have to choose from. Below is a list of the different categories of data science courses.

MSc in Data Science

An MSc in Data Science is a postgraduate academic degree program that focuses on providing students with advanced knowledge and skills in the field of data science. The program typically covers topics such as statistics, machine learning, data mining, big data analytics, data visualization, and programming languages commonly used in data analysis such as Python and R.

Postgraduate certificate in Data Science

The duration of a Postgraduate Certificate in Data Science varies but is typically shorter than a full master’s degree program, ranging from a few months to a year. These programs are often suitable for individuals who want to acquire specific skills in data science or want to upskill in data science. There are plenty of online data science certifications available, making it easy for working professionals to upskill without quitting their jobs.

MBA in Data Science

An MBA in Data Science is a specialized Master of Business Administration (MBA) program that focuses on integrating business management principles with advanced skills and techniques in data science. This program is designed to prepare students for leadership roles in organizations where data-driven decision-making is essential for success.

In an MBA in Data Science program, students typically learn about topics such as data analysis, machine learning, predictive modeling, data visualization, big data analytics, and statistical methods. They also study business-related subjects such as strategic management, finance, marketing, operations management, and organizational behavior.

The goal of an MBA in Data Science is to equip students with the knowledge and skills to effectively use data to inform business strategies, improve operational efficiency, drive innovation, and gain a competitive advantage in the marketplace. Graduates of this program are prepared to pursue a variety of career paths, including data science leadership roles, business analytics consulting, entrepreneurship, and executive positions in a wide range of industries.

How long does it take to learn Data Science?

The amount of time needed to master data science principles can be divided into three categories. Depending on your experience and how much time you are ready to devote to your data science studies, the time needed to reach a particular level of proficiency will vary.

People with analytical backgrounds, such as those in physics, mathematics, science, engineering, accounting, or computer science, typically need less time than people whose backgrounds are not complementary to data science. Let us know more about how much time it takes to learn data science.

Conclusion

Building a strong online presence, taking the top data science courses available, and adding them to your resume can help you stand out to companies. It will boost your likelihood of getting employed by demonstrating that you have the problem-solving and teamwork skills necessary to be successful as a data scientist.

Additionally, you can explore the various data science courses available on Online Manipal data science course will help you succeed in your job; if you need assistance deciding which course to choose, get in touch with us. We believe this data science learning course will help you pursue a career in this fascinating and rapidly expanding industry. Enroll now to learn data science online.

Best online bachelor’s degree programs in 2024

With the development of technology, most things have become digital. Online learning has gained much popularity in recent years, and many individuals now prefer to pursue online degree courses over regular ones. One of the reasons for the popularity of such courses is that they provide self-paced learning. Students can continue their education through online learning and invest their remaining time productively.

Like in other countries, students in India are also enrolling themselves in online degree courses and taking their careers to the next level. Therefore, an online bachelor’s degree will be an excellent option whether you are an employee or just completed your 10+2 and want to continue your study at your pace.

What is an online degree course?

As the name suggests, an online degree course is a course exclusively conducted online. To pursue this course, students don’t need to attend the college campus, and such a course accommodates those who cannot pursue the regular courses for various reasons. According to a survey, 61% of HR managers believe that online learning is of equal quality with traditional learning. 71% of organisations hire candidates completing online degree courses. 83% of business leaders believe that pursuing an online course from a well-known institute is far better than taking an on-campus course from an average institute.

Some of the features of online degree courses are:

There are no barriers to students in case of online courses as innumerable students can enrol into the course at the same time.
In a competitive country like India, students do not need to go through cutthroat competition to enrol in an online bachelor’s degree.
Students can attend classes at their convenience.
A flexible schedule helps the students pursue studies and other activities like working in an office, taking other courses, etc.
Since there is no expense on furniture and other infrastructure, the online course cost is lower and available at an affordable price.
Even students from low-income families can also afford online courses from top institutes.
In the online learning process, one to one interaction between teacher and students makes the class more engaging and interactive.
A high-quality curriculum helps the students increase their skills and knowledge in an unparalleled way.
Due to the flexibility of time and other conveniences, students can complete the full course without any difficulty, which leads to a higher retention rate.

Online degrees vs regular degrees

There are some basic differences between online degrees and regular degree courses. The differences are mentioned in the table below:

Online degree courses	Regular degree courses
Online degree courses are less costly	Regular degree courses are more costly
Innumerable students can attend classes simultaneously, and therefore there is no high competition for seats	Only a limited number of students can join the course, making the competition for seats very high
One to one interaction between teacher and students makes the content easily understandable	Lack of adequate interaction creates difficulty for students to understand the content
Classes become more engaging and interesting	Less engaging classes become less interesting
Instructors can clear doubts of students instantly	Students may have to wait to get their doubts cleared
Flexible timing makes it convenient for students to attend the classes	Fixed timing creates inconvenience for attending the classes on time
Self-paced learning	Learning is possible only in the stipulated time
No need to travel	Travelling is required
High-quality curriculum as only top-ranked institutes are allowed to offer online by UGC	The quality of the curriculum depends on the rank of the institute
Less time consuming	More time consuming
Retention rate of students is higher due to being more flexible schedule and engaging delivery	Retention rate of students is low due to lack of flexibility

Why get a bachelor’s degree vs a diploma?

Both bachelor’s degree and diploma programmes are fairly popular options after 10+2. Bachelor’s degree focuses on imparting knowledge by going to the root of a subject. Normally the duration of a bachelor’s degree may vary from three years to six years. In the case of a bachelor’s degree in general courses, the period may be three years. But, in the case of a bachelor’s degree in professional courses, the course period may vary from four to five years.

Unlike a bachelor’s degree, a diploma focuses on imparting a particular skill. The total time for completing a diploma may vary from three months to three years. Due to the absence of proper knowledge, some students go for diploma programmes instead of degree courses.

A student benefits more by doing a bachelor’s degree rather than a diploma. These have been explained below:

International institutes always recognise bachelor’s degrees, but foreign institutes may not recognise a diploma.
Bachelor’s degrees allow students to dive deep into a subject, unlike a diploma that focuses only on teaching what is required.
Many avenues may open up for students by doing a bachelor’s degree. But a diploma offers only those opportunities for which a diploma course has been created.
Bachelor’s degrees offer you opportunities to pursue master’s degrees and go for further studies. But by doing a diploma course, you may not be able to go for further studies.
The top companies always prefer those employees who have a bachelor’s degree rather than a diploma. Bachelor’s degrees are available in most of the top institutes.

What are the best online bachelor’s degrees in India?

There are many bachelor’s degree courses in India. To know about the best online bachelor’s degrees in India and top institutes that offer these courses along with the average salaries on graduation, look at the table below:

Online degree courses	Top colleges	Average salary (in INR)	Subjects covered
Bachelor of Business Administration	Manipal University Jaipur, Jain Deemed-to-be University, Amity University	8 lakhs	Effective Communication skills, Quantitative Methods, Financial Accounting, Principles of Management etc.
Bachelor of Commerce	Manipal University Jaipur, Lovely Professional University, Amity University	3 lakhs	Banking, Financial Services, Capital Markets, Market Research, Insurance, Supply Chain etc.
Bachelor of Computer Application	Manipal University Jaipur, University of Mysore, Symbiosis University, Lovely Professional University, Amity University	7.2 lakhs	Fundamentals of Computers, C Programming, Operating Systems, Multimedia Systems, Web-based application development.
BAJMC	Amity University, Chandigarh University, Kalinga Institute of Industrial Technology	5 lakhs	Mass Communication Model and Theory, Print Journalism, Graphics and Visual Communication, Business Communication.
Bachelor of Arts	Sikkim Manipal University, Symbiosis University, Amity University, Lovely Professional University, Aligarh Muslim University	Not Mentioned	Economics, English, History, Philosophy, Sanskrit, Sociology
B.Sc Travel and Tourism Management	Padmashree Dr. D.Y. Patil Vidyapeeth, Hindustan Institute of Technology & Science	Not Mentioned	Travel Business, Service Marketing, Hospitality Management

How to choose the best online UG program?

Before choosing an online UG program, you should carefully gather some information from reliable sources. Based on that information, you can make your decisions.

Before choosing an online program, you should go through the following steps:

Research the institute

Before making a choice for an online course, you should research the institute well. Find out the year of establishment, the total number of students enrolling every year etc. Moreover, you should also find out to which University the institute is affiliated, and whether the institute is accredited or not.

Course

Once you decide to take the online course, you should find out whether the course offered is fully online or not because some institutes offer partially online courses.

Fee

Once you decide on the institute, you should check the fee structure and compare the fee with other institutes. You should always compare with them for the same courses.

Faculty

You should also gather information regarding faculty, including their qualification and experience, which faculty member is given a higher rating by students etc.

Time table

You should check whether the time fixed for a class is flexible or not. Also, check whether the videos are available after the live class or not.

Check requirements

Before enrolling in the courses, you should find out the requirements for the particular course. Check the eligibility criteria. If the criteria match your eligibility, you should apply for admission to the online UG course.

How to get admission to an online bachelor’s degree programme?

Before taking admission into an online programme, you should find out certain information and follow certain procedures.

Visit the website

To get admission to an online bachelor’s degree programme, you have to visit the official website of the institute. By visiting the website, you will be able to gather all the required information mentioned there. After going through all the information, you have to decide whether you should get admission into the institute or not.

Apply on the website

After going through all the information; you should apply online to the course you are interested in pursuing.

Consult with admission counsellor

If you have any confusion regarding taking admission into your desired course, you can consult with an admission counsellor. An admission counsellor will also help you if you are unable to make any decision regarding taking an online course.

Payment of fee

You can make the payment online by using a credit/debit card or any other mode suggested by the institute.

Wait for approval

After making the payment, you have to wait for approval from the University. Once approved, you’ll be informed by mail.

Get a future-ready online bachelor’s degree from Online Manipal

Manipal University Jaipur offers three online bachelor’s degree programmes through Online Manipal at an affordable price. By enrolling in any of these courses, you can get lucrative opportunities. All three courses have been mentioned below:

Bachelor of Commerce

This course is designed so that you can acquire managerial skills and get success in the field of commerce by building competencies. This three-year degree programme will help you acquire knowledge of accounting principles, export and import laws, economic policies, and trade and business. In this course, subjects include Accounting, Managerial Economics, Marketing Management etc.

Bachelor of Business Administration

This course aims to prepare you in the field of business and make you industry-ready. You can access both live and recorded classes. This three-year online BBA course is open to all students irrespective of their high school streams. Those who are interested in building their career in the field of business administration can opt for this course. Subjects covered in this course are Business Management, Marketing strategy, Communication, Systems and Analytics, Finance etc.

Bachelor of Computer Application

This online degree course helps you build a lucrative career in computer technology. This three-year course is enriched with Google Cloud Computing Foundations, designed to introduce you to cloud technology. You will also learn from cloud infrastructure to application development. You will be provided practical knowledge with proper assessment and can learn at your own convenience from the comfort of your home. Subjects are IT and Computer Programming in C, Data Structure and Algorithms, Communication Skills and Personality Development etc.

Conclusion

Due to the popularity of online courses, many students have the opportunity to continue their education and other work. Technological developments have made online education more accessible, and students can access knowledge through online education at a very affordable price. Even working professionals can come forward to pursue online degrees to take their careers to the next level. Many institutes now offer online degree courses due to the increasing popularity of such courses. The universities on Online Manipal like Manipal University Jaipur and MAHE can help you find relevant bachelor’s degree courses.

Four pillars of data science

Let’s start this blog by giving a short introduction to data science. Data science is the scientific discipline that uses data to answer questions, solve problems and conduct hypothesis validation. Data scientists use programming languages, statistical analysis and algorithms to create models that help them gather insights from the data they collect. They use their skills across different industries, including medicine, finance, insurance and retail, and work with massive amounts of data daily to find trends and patterns, thus helping businesses improve their services.

For example, a data scientist may predict when people will buy a specific product or service based on past purchases or product reviews. Want to know what are the four pillars of data science? Read this blog to find out.

Four pillars of data science

Data science is a field that’s constantly changing and evolving. It is hard to keep up with the latest trends, tools, and methods. However, there are some concepts that you can’t ignore if you want to make your data science career successful.

Domain knowledge

Math & statistics skills

Computer science

Communication & visualization

Following are the 4 pillars of data science –

Domain knowledge

Domain knowledge is the first pillar of data science. It is the understanding of the industry or the field where data science operates, for instance, understanding of a business and its customer base that allows you to develop products and services relevant to your customers and their needs. For a data scientist, it’s crucial to grasp the intricacies of the business process, identify its challenges, and discern the requirements of stakeholders. Understanding the business objectives and the specific tasks necessitated by data analysis is paramount. Proficiency in domain knowledge aids data scientists in formulating pertinent queries, choosing suitable analytical approaches, interpreting analysis outcomes, and offering valuable insights to the organization.

For example, if you are working with a retail company, you can read about how other retailers have marketed their products in the past or attend industry conferences where experts discuss trends in retail marketing.

Math and statistics skills

The second pillar of data science is math and statistical skills. Math and statistics skills are crucial to data science, as you will use your knowledge of these subjects to analyze, interpret and present the data you collect.

The most common mathematical techniques in data science include probability theory and statistical analysis. Probability theory is used to understand the likelihood of an event occurring, while statistical analysis helps you determine whether a specific event has occurred.

Statistical analysis also involves calculating averages or medians or determining how close or far apart two sets of numbers are from each other. You can use this information to predict future events based on past events.

Computer science

The computer science pillar of data science is the foundation for all other 4 pillars of data science. Computer scientists use their expertise to solve complex problems and develop algorithms, software, and systems that allow for data collection, storage, analysis, and dissemination. They are also responsible for setting up decision automation processes that ensure accurate results from these systems.

Computer scientists have a wide range of skills they can apply to data science, such as –

In-depth knowledge of the computer’s functioning
Ability to write code in languages like Python or R
Working knowledge databases like SQL
Ability to design algorithms that process hypothesis validation efficiently.

Communication and visualization

The last pillar of data science is communication and visualization. This means that you need to be able to communicate your findings and present them in a way that’s easy for people who aren’t experts in your field. You also need to visualize your data so that others can quickly grasp what it shows.

Communication is vital because it allows you to share what you have learned with others in the organization and helps them understand how it will impact their lives. On the other hand, the visualization allows people unfamiliar with the information you have gathered from your data set to see its value more efficiently.

You can use graphs, charts, or diagrams to present information visually rather than just presenting raw numbers or text-based reporting data.

Essential skills for a data scientist

Apart from mastering the four components of data science, data scientists need many other skills to stay competitive and excel in the domain. Here are a few skills today’s data scientists need-

Data visualization
Machine learning
Deep learning
Managing structured data
Programming
Familiarity with Hadoop, SAS, Python, R

Data science job outlook

Data science is a field that touches on several other disciplines, including math, statistics and computer science. Data scientists work with large amounts of data and then use statistical techniques for pattern discovery and obtaining insights. Top companies like Wipro, Infosys, IBM, Tiger Analytics, etc are on the constant lookout for data scientists who can add value to organizations by making business-driven decisions. Here are some of the top data science roles.

Job role	Average salary
Data Architect	INR 26 LPA
Data Engineer	INR 17 LPA
Data Scientist	INR 14.4 LPA
Machine Learning Engineer	INR 11 LPA
Business Analyst	INR 8.4 LPA

Pursue an online data science course from MAHE

If you are seeking to build a strong career in this domain, you must strongly consider enrolling in the data science course at Online Manipal. Exclusively designed by MAHE, the course helps you acquire the necessary skills along with expert guidance. You will learn about big data, machine learning and artificial intelligence – all critical for success in the modern workplace.

In this course, you will gain a solid foundation in statistics, probability theory and linear algebra from your instructors at MAHE. You will also learn about various machine learning algorithms that can be used for predictive modeling, classification and regression analysis using Python programming.

You will get hands-on experience with real-world data sets by working through case studies and applying what you have learned in each unit. You will also have access to an exclusive job placement team that can help you find employment after graduation or help you land interviews if you are already employed but looking for a career change.

ALSO READ: Career path in Data Science

Bottom line

From the ability to make better decisions faster, to being able to predict what will happen before it does, data science has become a critical component of our society. The amount of data generated today will only continue to increase and become more complex. Therefore, it is important that you learn how to analyze and use this data in your life and career.

MAHE offers an online MSc in Data Science course at Online Manipal that can help you get ahead in this ever-changing world of data science. Experts in the field design our courses to be fun and engaging while still being informative. The best part is that they are all 100% online, so you don’t even have to leave your house!

Understanding marketing: Skills & knowledge required

Marketing jobs after BA

Pursue an online BA from Sikkim Manipal University

Conclusion

Understanding AI Engineering

Understanding Data Science

AI Engineer vs. Data Scientist: Key Differences

Career paths in AI Engineering and Data Science

Challenges and Future Outlook

MAHE is the best choice for both: AI Engineer or Data Scientist!

Conclusion

The red flags: Identifying fake universities

Beyond the checklist: Additional tips

Are online programs from Indian universities fake?

Additional resources:

Conclusion

Understanding business analytics

Why consider a career in business analytics after engineering?

Steps to transition into a business analytics career

Skill set required for transitioning to Business Analytics

Job roles and responsibilities in Business Analytics

Resources for further learning and development

Excelling in Business Analytics with MAHE

Conclusion

Why supply chain management in healthcare?

Benefits of supply chain management in healthcare

Challenges in healthcare supply chain management

Supply Chain Management SCM in healthcare – best practices

Supply chain job roles in healthcare

Read more: High paying jobs roles in supply chain management

Conclusion

Understanding the Scope of AI Engineering

Job Description of an AI Engineer

Skills Required for AI Engineers

Educational Background and Training

Salary Trends for AI Engineers

Career Growth and Opportunities in AI Engineering

Challenges and Ethical Considerations

How can MAHE help you realize your AI dream?

Conclusion

Understanding data science

Why consider a Data Science Career after Engineering?

Steps to Transition into a Data Science Career

Essential Skills for Data Scientists

Career Path Options in Data Science

Challenges and Considerations

Data Science with MAHE

Conclusion

Courses in data science

MSc in Data Science

Postgraduate certificate in Data Science

MBA in Data Science

How long does it take to learn Data Science?

Conclusion

What is an online degree course?

Online degrees vs regular degrees

Why get a bachelor’s degree vs a diploma?

What are the best online bachelor’s degrees in India?

How to choose the best online UG program?

How to get admission to an online bachelor’s degree programme?

Get a future-ready online bachelor’s degree from Online Manipal

Conclusion

Four pillars of data science

Domain knowledge

Math and statistics skills

Computer science

Communication and visualization

Essential skills for a data scientist

Data science job outlook

Pursue an online data science course from MAHE

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