MSc Data Science Course
MSc Data Science is an interdisciplinary degree program which revolves around the major disciplines of Calculus, Descriptive Statistics and C-Programming in order to understand different phenomena with respect to a big set of real world data.
Students who have completed their Bachelors degree in either Statistics, Mathematics, Computer Science or Engineering can pursue Data Science Courses 2 year research-based program. It is an interdisciplinary field that includes the domains of computer science, statistics, mathematics, artificial intelligence and machine learning.
MSc Data Science is one of the most favoured masters courses in data science specialization because it includes all the necessary topics and structure which leads to skills required to become a successful data scientist or have a career in data science domain.
MSc Data Science Course Highlights
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Full Form
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Master of Science in Data Science
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Course Level
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Postgraduate
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Duration
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2 years
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Eligibility
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Atleast 50% in Bachelor program in either Computer Science, Statistics or Mathematics
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Admission Process
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Merit + University Entrance Test or Written Assessment Round, followed by Personal Interview or Counselling
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Job Positions
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Data Analyst, Data Engineer, Machine Learning Engineer, Data Scientist, Data Architect, Database Administrator, Data Solutions Analyst, Business Analyst, Data Mining Engineer, etc.
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Top Recruiting Companies
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Tredence Inc., Wipro Ltd., Oracle, Cartesian Consulting, TEG Analysis, Deloitte, GlobalAnalytics, IBM, Amazon, MuSigma, etc.
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MSc Data Science Eligibility
Common eligibility is atleast 50% aggregate marks from any recognized college/university in India or Abroad in one of the following Bachelor programs:
• Bachelor of Computer Applications (BCA)
• Any Bachelor program in Computer Science, Mathematics or Statistics
MSc Data Science Syllabus
The syllabus and course curriculum is inclusive of three main parts: Calculus, Descriptive Statistics and C Programming. Latest technologies like ML, DL, Python and Spark are taught thoroughly.
Following table shows the semester wise syllabus of MSc Data Science:
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Semester I
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Semester II
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Mathematics for Spatial Sciences
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Spatial Big Data and Storage Analytics
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Applied Statistics
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Data Mining and Algorithms
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Fundamentals of Data Science
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Machine learning
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Python Programming
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Advanced Python Programming for Spatial Analytics
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Introduction to Geospatial Technology
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Image Analytics
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Programming for Spatial Sciences
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Spatial Data Base Management
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Business Communication
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Flexi-Credit Course
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Cyber Security
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Integrated Disaster Management
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Semester III
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Semester IV
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Spatial Modeling
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Industry Project
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Summer Project
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Research Work
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Web Analytics
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Artificial Intelligence
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Flexi-Credit Course
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Predictive Analytics and Development
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MSc Data Science Jobs and Career
This course is perfect for students who want to make a career in the big data industry, computer science and IT industry. As we all know that the latest trends and technologies nowadays all revolve around data science, therefore right now is the best time to pursue this course for a better future in the technology sector.
The common employment areas that hire Data Science postgrads are tech companies, consultancies, market research companies, and energy sectors. If you want to go into teaching or research, you can get employed in research institutes, colleges or universities as well.
There are four major types of Data Science Jobs:
- Data Analyst
- Data Engineer
- Machine Learning Engineer
- Data Science Generalist
Apart from these, you also have other options which we have discussed below with the job description and the average salary offered:
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Job Profile
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Job Description
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Data Analyst
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The main role of a Data Analyst is to translate data into plain English so that big and profitable decisions can be made in business, sales pitch, logistics, market research, manufacturing, etc.
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Data Engineer
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A Data Engineer is responsible for various things like developing, constructing, testing and maintaining databases, large scale processing systems and much more. They also recommend and give ideas to improve data reliability and data quality.
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Data Architect
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A Data Architect plays a very important role in a company by maintaining all the database and identify different structural and installation solutions.
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Machine Learning Engineer
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An ML Engineer is responsible for understanding and transforming different prototypes of data science. They perform research, design and frame machine learning systems for efficiency and problem solving through model tests and experiments.
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Data Scientist
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Data Scientists perform statistical analysis and make sense to the data important for company business or for some other analysis.
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Statistical Programmer
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A Statistical Programmer develops and uses different analysis plans, validations plans and other related documents required to determine and research SAS software and related system maintenance issues.
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Data Developer
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A Data Developer makes sure that the data is gathered before the development of any database. They create management methods and systems in the IT domain.
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Data Science Teacher
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A Teacher or Professor of Data Science works in either college, university or institute to teach students different theory and practical subjects of data science and related fields.
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Data Mining Engineer
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A Data Mining Engineer usually enhances and creates statistical and predictive models and algorithms to analyze large sets of data, and derive valuable information and insights from it.
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Database Administrator
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Database Administrators used professional and specialized softwares for data storage and organization as per the need and to improve the quality.
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MSc Data Science Scope
Data Science is considered one of the trendiest courses in the world right now. Many students and working professionals are attracted to this course because it leads to the right skills and knowledge required to become a successful Data Analyst and Data Scientist.
This rapid boom in the data science field will not slow down anytime soon. The future and scope of data science will expand in the coming years because big data plays an important role in the day-to-day commerce and digital industry. This means that the need for skillful professionals to meet the challenges of data science, data analytics, and similar roles will not be going to stop.
Apart from earning, you get to interact and work with top IT Engineers and Data Scientists helping you to gain the required skills and knowledge. Other than this, you get to work on cutting edge technologies and exploiting it to solve different challenges and issues of the top companies.
Conclusion
Data science education is well into its formative stages of development; it is evolving into a self-supporting discipline and producing professionals with distinct and complementary skills relative to professionals in the computer, information, and statistical sciences.
You'll gain in-depth training in mathematics, statistics, and computer science compared to what you received in your undergraduate studies. You'll also develop critical thinking and quantitative, domain-specific skills likely to remain in demand even as this fast-paced field quickly evolves.