Explore a comprehensive Master of Science in Data Science syllabus: from data analysis and machine learning to ethics and advanced techniques.
The syllabus for a Master of Science in Data Science program typically covers a wide range of topics to provide students with a comprehensive understanding of data analysis, machine learning, and data-driven decision-making. Below is a sample syllabus that includes common courses found in such a program.
S.No |
1st Year Syllabus of M.Sc in Data Science |
1 | Data Science Programming |
2 | Data Mining and Warehousing |
3 | Econometrics |
4 | Construction Economy and Finance |
5 | Data Analytics Mathematics |
6 | Computational Linear Algebra |
7 | Data Analytics and Graphs |
9 | Empirical Research |
10 | Advanced-Data Analytics |
11 | Inferential Statistics |
12 | Stochastic Processes |
13 | Optimization Techniques |
14 | Software Engineering |
15 | Software lab in Python |
2nd Year OR 3rd and 4th Semester Syllabus of M.Sc in Data Science
S.No | Subjects |
1 | Machine Learning |
2 | Hadoop Programming |
3 | Big Data Analytics |
4 | Practicals |
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