What next after bachelor’s? Grow your career with master’s in data science

Data Science helps extract just the relevant or important insides from a vast amount of available information by using various algorithms, statistical methods, and other data analysis systems. Data science came into existence because of technological development, mathematical operations, data mining processes, etc. It helps in determining the hidden patterns in the sample raw data available.

Pursuing a master’s in data science gives you lots of opportunities to grow your career in different fields. Data science is an area that many companies now widely utilise. As the industry transitioned to the Fourth Industrial Revolution, automation, artificial intelligence, and the Internet of Things began to shape our human lives. Data science has revolutionised all major industrial sectors such as banking, healthcare, entertainment, sports, and services.

Data science is focused on acquiring knowledge about data inference and exploration. A good data scientist has computer programming and statistics skills to understand the data and solve complex business problems. The best data science certification helps you acquire new skills and helps you tackle your business situation practically.

What will you study in a data science course?

To become a data scientist, you need strong analytical and computational skills to solve complex problems. Most universities consult with industry experts on curriculum preparation before making the curriculum available to students. You’ll have the opportunity to learn machine learning, data analysis, statistics, data modelling, business analysis, data visualisation, cloud computing, database systems, internet technology, and algorithms. If you’re lucky, some universities also cover programming languages.

How much will M.Sc Data Science cost?

Programme costs vary from university to university and, of course, from country to country. The most common factors that affect tuition fees include programme length, university rankings, and destination country. Many universities offer a wide range of scholarships based on academic performance. Therefore, it is advisable to consult with your advisor in advance to confirm your eligibility for scholarships. This will significantly reduce learning costs. You can check out the fee structure of online M.Sc. in Data Science at Manipal Academy of Higher Education (MAHE).

Benefits of earning a master’s degree in data science

Being a revolutionary and new field there are various students opting for a career in this field. Several institutes are providing bachelor’s degree in Data Science and master’s in Data Science India. A masters in data science opens up a large scale of future career paths.

With advances in new technologies and the emergence of the world of smart devices, data science is expanding as a career choice. A PG program in data science can be fruitful for anyone looking to build a good career in this area. The profession of data scientists has evolved into an essential profession for companies in various industries to use data for strategic thinking.

The need for this new business has helped promote this profession. Due to the high demand for data scientists, data science is currently one of the best disciplines. With an M.Sc. in the field of data science, you can improve your skills by giving yourself plenty of room. 

Here’s why you need to apply for a master’s degree in data science:

• Learn in-demand data science skills: Data science requires learning programming languages such as Python and R programming, as well as methods such as machine learning, data wrangling, and data visualisation. A postgraduate programme in data science with a professionally designed curriculum will succeed in the future by acquiring the skills to collect, aggregate, and analyse different types of data, identify patterns and trends in that data, and communicate results. These compensation skills are built into all course offerings, and you also have the opportunity to use them to draw conclusions from the actual dataset.  
• Earn a higher salary: With advanced skills and knowledge, you can get a good salary at work. The average salary of a data scientist in India is about INR Seven lakhs per year. You can expect INR Six lakhs a year for an entry-level experience, but you can achieve more than INR 10 lakhs for a mid-level experience. Also, as the demand for data scientists grows day by day, salaries could increase by 10% by  2025.
• Gain real-world business skills: This is an important part of a master’s degree in data science. Learning programming languages and other basic skills is important, but projects can apply education to real-world business problems. You have the opportunity to apply the skills and methods you have learned to find solutions from large amounts of data. Final year projects can also explore specific areas of interest to help identify your next career path. You will gain marketable career experience that you can use to look for new job opportunities and advance in your professional life. 
• Exposure to real-world situations: Universities provide students with the perfect balance of theory and practice. An M.Sc. in data science gives you real-time insight into possible business scenarios. Thus, you can easily deal with the actual business situation.
• Constantly evolving nature: Data science is evolving. What makes this field more attractive is its transforming nature. By enrolling in the master’s programme, you can learn new skills that will help you use data in your business scenarios to develop effective data-driven strategies to streamline operations. You can analyse data trends and create strategic plans for your business growth.
• To deepen your knowledge:  After completing the M.Sc. in Data Science course, you will have advanced knowledge and skills to apply in diverse situations. In data science, hire yourself more in this highly competitive world. According to a survey, about 88% have a master’s degree in data science, and 40%  have a Ph.D. Data Scientists are currently one of the fastest-growing professions in the world and require a high degree of knowledge and skills to stand out from others. Online data science programmes can help you develop these skills.

Basic concepts covered in data science masters course

As data science is such a huge and diverse concept, there are frequent updates and changes in the technique, but the core concepts remain unchanged; a few of them are:

• Statistics: Statistics is the most important concept of the Data Science phenomenon. It is the method of collecting, bifurcating and analysing the raw numerical data collected and obtaining the important or necessary details. Statistical data leads to a straight-to-point explanation and helps in the time saving of the user.
• Visualisation: The visualisation technique converts these numeric and huge data into visual representations. Visual representation is easy on the eye and easily accessible and understandable as it provides an on-point explanation.
• Machine Learning: Machine Learning explores the study and information and helps the company or user make predictions and plan the foreseeable future. These assumptions are not 100% accurate but a mere prediction based on the collected or previous data.

Methods followed in data science analysis

A basic procedure is followed for data science analysis to make the task more efficient. Its as follows;

• Discovery: collection and acquiring the data that seems useful for the research forms a part of the discovery stage of data science. This data is acquired from internal and external sources and any other liable source.

The data can be:

1. Government released data
2. Data gathered from social media
3. Data from Books and thesis written by authors 
4. Census datasets
5. Data collected by an authorised and trusted organisation
6. Data streamed from online sources using APIs

• Preparation: The collected data is raw and unorganised. Thus, in the initial stage, the useful data needs to be recognised to eliminate unnecessary data and save time. Thus, the data needs to be processed because the cleaner the data the better the prediction.
• Model Planning: After collection and processing, the data is collected, and important or useful data must be determined. Later, you can decide the method and technique of presenting and representing the data. You can make decisions regarding data modelling by using mathematical and statistical methods.
• Model Building: In this step, the procedure of building the actual modal begins. The collected data is now organised and represented into models. Different techniques such as association, classification, and clustering of data are applied to the available data set, thereby depicting and conveying all the important data.
• Operationalise: In this stage, all the studies and results are delivered. All the past data and reports are applied to the real-time information, and thereby a model representing the real-life scenario of the company is depicted. 
• Communicate Results: In this stage, all the important data is revised and converted into models, stats and diagrammatic representation are conveyed to the final users. Because communication of the result is the final and the main aim of this process.

Master data skills with an online M.Sc. in Data Science from Online Manipal

Online Manipal is now offering UGC-entitled online M.Sc. in Data Science from the prestigious Manipal Academy of Higher Education (MAHE). The programme from the Institute of Eminence covers all the advanced concepts in data science.

Graduates in Statistics/Mathematics/Computer Science [BSc/BE/BTech/BCA] or an equivalent degree studying the subjects for a minimum of two years from universities/institutions recognised by the Association of Indian Universities (AIU) with a minimum of 50% of marks or equivalent grade can enrol in this M.Sc. programme. The 100% online programme allows learners to study at their convenience using any device.

Conclusion

Studying data science requires a lot of preparation, and data science is focused on acquiring knowledge about data inference and exploration. Before signing up for the best data science course for beginners, we recommend taking online courses on Python, SAS, Hadoop, regression models, data exploration, hypothesis testing, and Spark. This will greatly help you improve your research and improve your employment and internship opportunities.