Delve into the program's curriculum, covering advanced data analytics, machine learning, big data technologies, and data ethics, preparing students for careers in the dynamic field of Data Science.
Syllabus and subjects in M.Tech Data Science
A Master of Technology (M.Tech) program in Data Science typically offers an advanced curriculum that combines foundational and specialized coursework in data science and related fields. The syllabus includes core courses in data analysis, machine learning, statistical modelling, and data visualization. Students also delve into advanced topics such as big data technologies, deep learning, natural language processing, and data ethics. Additionally, the program often includes courses in programming, database management, and data engineering to provide a well-rounded skill set. Practical experience is gained through hands-on projects, research, and often a mandatory thesis or dissertation. Graduates of this program are well-prepared for careers as data scientists, data analysts, machine learning engineers, or data engineers, equipped to work with large datasets, extract valuable insights, and develop data-driven solutions across various industries and sectors, meeting the increasing demand for data expertise in today's data-driven world.
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1st Year Syllabus of M.Tech. in Data Science
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1 | Data Science Programming |
2 | Data Mining and Warehousing |
3 | Econometrics |
4 | Construction Economy and Finance |
5 | Data Analytics Mathematics |
6 | Laboratory |
7 | Data Analytics and Graphs |
9 | Empirical Research |
10 | Advanced-Data Analytics |
11 | Big Data |
12 | Project |
13 | Laboratory |
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2nd Year Syllabus of M.Tech. in Data Science
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1 | Project |
2 | Evaluation of project and Viva |
3 | Seminar |
4 | Training and Internship |