M.Tech in Data Science Syllabus - Guru Nanak University (GNU, Hyderabad)

  • Years 2 Years
  • Type Course Post Graduate
  • stream Engineering
  • Delivery Mode
Written By universitykart team | Last updated date Jul, 07, 2024

The Master of Technology (M.Tech.) Data Science syllabus at Guru Nanak University (GNU), Hyderabad is designed to provide overall knowledge to the students with a strong foundation. Master of Technology (M.Tech.) Data Science faculty at Guru Nanak University (GNU) specially focus on in-depth learning to relevant subjects. At first semester syllabus of Master of Technology (M.Tech.) Data Science at Guru Nanak University (GNU), students learn the basics of programme. A strong foundation is very important for comprehensive learning. Master of Technology (M.Tech.) Data Science syllabus at Guru Nanak University (GNU), Hyderabad maintains a balance between theoretical knowledge and practical knowledge.

Master of Technology (M.Tech.) Data Science first year students at Guru Nanak University (GNU) are introduced with core subjects. Then they are encouraged to explore other area for a broader perspective. Guru Nanak University (GNU), Hyderabad also provides practical training sessions, workshops, projects, and case studies to enhance student skills. Master of Technology (M.Tech.) Data Science syllabus at Guru Nanak University (GNU), Hyderabad is also frequently updated to give industry relevant training and knowledge to students. Guru Nanak University (GNU) strives to provide a nurturing environment where students can learn new skills. The hands-on training sessions at Guru Nanak University (GNU) enable Master of Technology (M.Tech.) Data Science students to apply knowledge and skills in a controlled environment and get required experience.

According to syllabus of Master of Technology (M.Tech.) Data Science progress, students learn advanced topics and complex concepts. The Master of Technology (M.Tech.) Data Science curriculum at Guru Nanak University (GNU), Hyderabad mainly focuses on analytical and critical thinking. As the Master of Technology (M.Tech.) Data Science course unfolds, students develop several important skills that increases their employability. As per syllabus of Master of Technology (M.Tech.) Data Science at Guru Nanak University (GNU) also includes real-life projects and internship programs. It helps students critical thinking and gives them real-world experience.

Master of Technology (M.Tech.) Data Science curriculum at Guru Nanak University (GNU) includes group discussions, guest lectures, case studies, and skill development workshops to enhance the learning experience. The Master of Technology (M.Tech.) Data Science syllabus at Guru Nanak University (GNU) aims to create well-rounded professionals equipped with the necessary skills and knowledge to succeed in their chosen fields.

Additional curriculum at Guru Nanak University (GNU)

  1. Workshops and Seminars - Regular sessions with industry experts help Master of Technology (M.Tech.) Data Science students at Guru Nanak University (GNU) to stay updated with current trends.
  2. Group Projects - Collaborative projects according to Guru Nanak University (GNU) syllabus develop teamwork and problem-solving skills.
  3. Case Studies - Master of Technology (M.Tech.) Data Science syllabus offers analysis of real-world scenarios to apply theoretical knowledge.
  4. Extracurricular Activities - Guru Nanak University (GNU) offers several activities like sports, clubs, societies, etc. to encourage overall development.

Note: Given below syllabus is based on the available web sources. Please verify with the Guru Nanak University (GNU), Hyderabad for latest Master of Technology (M.Tech.) Data Science curriculum.

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.

S.No 1st Year Syllabus of M.Tech. in Data Science
1Data Science Programming
2Data Mining and Warehousing
3Econometrics
4Construction Economy and Finance
5Data Analytics Mathematics
6Laboratory
7Data Analytics and Graphs
9Empirical Research
10Advanced-Data Analytics
11Big Data
12Project
13Laboratory


S.No 2nd Year Syllabus of M.Tech. in Data Science
1Project
2Evaluation of project and Viva
3Seminar
4Training and Internship


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