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Data Science

MBA Vs MSc in data science

Key takeaways:

  • Data science is a flourishing industry, revealing attractive domains and career opportunities for young aspirants.
  • Pursuing a master’s in data science allows individuals to work in a business-oriented workspace and make informed relevant decisions.
  • Even though master’s and doctorates in math and stat are normally sought-after qualifications, other prominent qualifications like MBA in data science and MSc in data science can also help build a lucrative career in the industry.

With 2.5 quintillion bytes of data produced every day across the globe, a well-qualified professional is required to organize substantial data whilst offering effective business solutions. The growing demand for data science-related roles are motivating young aspirants to pursue a master’s degree in data science.

So, what course do you plan to choose if you consider a career in data science? Whether it’s MBA or MSc in data science, the course should help you to gain hidden insights or patterns from the raw unstructured data. This will help you in the generation of critical business decisions. 

An MBA in data science helps students to convert data into key business insights and incorporate in-demand tools and technologies, preparing them for the modern business landscape. On the other hand, M.Sc in data science will equip the learners with tools and techniques, making them part of the current industry trends. 

Let’s take a deeper look at how MBA data science vs MSc data science helps in mastering data science and in progressing your career.

What is an MBA in data science? 

MBA in data science is a postgraduate course that deals with interpreting technical infrastructure data, designed to equip the candidates with data science skills including interpreting, research, processing, creating data, and more. The duration of the course is 24 months.

Eligibility Criteria

Manipal Academy of Higher Education offers an MBA program in Data Science on the Online Manipal platform to equip candidates with the latest and most in-demand skills and tools in the field of data science. 

Here are the eligibility criteria for the MBA in data science –

Educational QualificationIndian Candidates – 10+2+3 year graduate degree in Statistics / Mathematics / Computer Science / Engineering / Technology or any other discipline with a minimum of two years of learning Mathematics or statistics from a recognized university/institution with an equivalent qualification recognized by the Association of Indian Universities (AIU) International Candidates- Candidates must have completed a graduation degree certificate of equivalence from the Association of Indian Universities required from students with a foreign education to apply to any university in India.
Professional ExperienceWork experience is desirable

Curriculum 

Pursuing an MBA in data science requires a combination of robust technical knowledge and practical experience. It gives them a potential edge over other competitors in the field. The skills required to master data science are acquired from the below syllabus.

  • Database management

Database management offers an experiential learning opportunity to build basic and advanced programing skills. 

The subject covers the languages, applications, and programing used to develop and maintain business databases. In the database system, the emphasis is on developing the candidates’ skill sets in object modeling, relational data models, and the physical characteristics of databases.

  • Machine learning algorithms

Machine learning uses algorithms and mathematical models to develop machines that can solve problems like human minds. The Machine learning method has programing assignments for the candidates to practice and gain hands-on experience. Here, the math needed to better understand each algorithm is comprehensively explained, with calculus explanations and linear algebra.   

  • Probability and probability distribution

A substantial part of data science is learning about the behavior and properties of variables. In short, the probability and probability distribution show the way for the candidates to represent the specific values concerning the variable and the respective variability.

  • Statistical Inference

In data science, descriptive statistical inference explains the data to users without making any inference from the data. Simply put, inferential statistics aid in claiming conclusions from the sample data to analyze the parameters of the population. This subject will help the students understand the target variable’s behavior.

  • Applied data analytics

The section focuses on learning analytics software and techniques that must be implemented directly in the industry. The knowledge of analytic tools, along with the data mining and machine learning approaches, will be analyzed in the subject. This will help students to enhance their capacity to examine real-world challenges and understand the possibilities of applications.

Careers after MBA in data science 

MBA in Data science graduates offer immense job opportunities in various technology domains, bringing them better growth and a bright future. Some of the sought-after careers options for an MBA in data science are-

  • Data scientist

The role of a data scientist is to make value of the given data. They must proactively collect information from various sources and examine it for better understanding. It will aid in learning how the business works and building high-quality integration systems to develop effective solutions.

  • Machine learning engineer

The responsibilities of Machine learning engineers are to design and develop machine learning systems, run tests and experiments and implement appropriate algorithms. The primary role of the professional is to shape and develop accurate predictions.

  • Database developer

Database developers are responsible for the databases’ integrity, protection, and performance. They are involved in various tasks, including planning, developing and troubleshooting, managing, and maintaining the organizations’ databases. 

  • Marketing research analyst

The role of the marketing research analyst is to assist  the organization’s marketing activities. They have to implement specific strategies and campaigns organized by the department, gather data from research, examine the collected information, and maintain a database for reference. 

  • Application architect 

An application architect or software architect is an individual who operates within the scope of one’s system while understanding all the interactions. They have to work with clients on planning and designing the applications, addressing the coding or programing issues, and even overseeing a team of developers.

What is an MSc in data science?

MSc in data science is designed to provide opportunities for aspiring candidates who want to mark their career move in the industry with a data-centric approach. With this course, one can earn hands-on experience in handling data through coursework, projects, and in-depth analysis. The duration of the MSc Data Science program is 24 months.

MSc data science eligibility

If you are looking for the best MSc data science programs in India, Online Manipal is the place to go. The course on the Online Manipal platform, offered by Manipal Academy of Higher Education (MAHE) is for aspiring professionals who want to build a progressive career in data science, equipping them with technical and analytical skills. Here are the M.Sc data science eligibility criteria.

Educational QualificationGraduates (10+2+3) in any discipline from recognized universities/ institutions, or an equivalent qualification as recognized by the Association of Indian Universities (AIU) with a minimum of 50% of marks or equivalent grade.
Professional ExperienceOne year of work experience in reputed organizations

MSc data science syllabus

Each module in the course highlights the tasks, including storing, analyzing, and recording data for predicting future insights extracted from structured to unstructured data. Here’s an overview of the M.Sc in data science curriculum-

  • Computational mathematics

The computational mathematics section in data analysis deals with mathematical modeling, numerical analysis, and computational aspects to analyze and solve complex problems. It also helps students gain the knowledge and experience to implement the productive parallel algorithm to enhance performance.

  • Programing in SAS for analytics

SAS, also known as Statistical Analysis System, is the most productive and popular software needed for accurate data analysis. The section enables the candidates to follow a programmatic-based approach to access the analytical abilities of SAS, in every stage of the data life cycle, including discovery and deployment.

  • Applied data analytics

Applied data analytics in the course focuses on data analytics and applied areas to provide comprehensive details in concepts and techniques. It exposes the students to various tasks, including organizing, cleaning, analyzing, representing, and visualizing large amounts of data. Moreover, it also offers the opportunity to gain in-depth knowledge in computation and statistics.

  • Programing with R and Python

In data science, Python is a general programing language used to develop and deploy various projects. On the other hand, R is a statistical language that plays a significant role in analysis and visual data representation. The section expands candidates’ knowledge in data analysis, enabling them to stimulate better performance.

Read more: Why should you opt for MSc in data science?

Careers after MSc in data science 

The demand for candidates who have completed their master’s in data science is spiking in the current era. Below are some of the most lucrative career opportunities after an M.Sc in data science.

  • Business analyst

A business analyst plays a significant role in helping various organizations solve their problems. They have various roles in the industry, including communicators, facilitators, and more. In short, they act as flexible professionals who are always searching for a way to enhance the growth of the business.

  • Data scientist

A data scientist is a responsible individual who develops an effective and data-driven solution customized to meet an organization’s specific needs. An ideal candidate must run analytical experiments sequentially through appropriate data and project design.

  • Program manager 

A program manager’s primary responsibility is to help an organization  achieve its goals. They also play a key role in coordinating the effort between different projects and departments. In short, they oversee the entire program with solid attention to implementation in executing strategy.

  • Data engineer

A data engineer’s primary responsibility is gathering, managing, and converting raw data into useful insights. They must analyze various requirements and implement effective database techniques to build a robust database architecture. Their role also extends to support the data scientists by helping them with the mining, modeling, and production of data.

  • Risk analyst 

A risk analyst, also known as a risk assessor, helps an organization to examine financial risks from the investment to costs to identify and reduce the risks. In addition, they analyze the current scenario to make predictions regarding the future of the business without hampering productivity.

MSc in data science or MBA: What’s best for you?

Here’s a short comparison of both programs offered by MAHE on the Online Manipal platform to help you choose the right one that suits your needs. Moreover, the course should have the ability to accelerate your career, boost your earning potential and aid in ultimately achieving your goals..

CourseEligibilityDurationFeeScope
MBA in Data ScienceOne year of work experience in reputed organizations24 months (15-20 hours per week)INR 2,60,000INR 65,000 each semesterChallenging and quick paced curriculumContribute to better career opportunityGain a wider perspective in the field of data science
M.Sc in Data ScienceWork experience is desirable24 months (15-20 hours per week)
INR 2,60,000INR 65,000 each semester
Better career transition in analytical and managerial roles.Upskills in the latest tools and skills in the field.Makes space for professional development, by facing new challenges

Final thoughts 

Is a master’s in data science worth it? Yes, considering the upward swing of the industry, a career in data science is expected to grow for a long time in the near future. As data is invading our life and becoming inevitable, organizations will continue to demand the recruitment of skilled data scientists. 

Nonetheless, data scientists need to have a solid knowledge of certain concepts, including computer programing, data mining, artificial intelligence (AI), machine learning, predictive analysis, and more.

If you are looking for the best online data science courses, look no further than Online Manipal and kick-start your career in the flourishing field of data science. Simply put, data science is all about the present and future. Good knowledge and understanding of this specialized field will keep you up with the ever-evolving industry, opening doors for exciting and lucrative job opportunities.

Other related articles-

Grow your career with master’s in data science

Rising demand for data science in India

Data science career path

  • TAGS
  • data science
  • online degree

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