Computer & IT – Data Science

Introduction to course

Discover the possibilities within our M.Tech. program in Computer & IT – Data Science, where we immerse ourselves in the transformative world of data-driven solutions and advancements. Tailored for those with a passion for leveraging data to fuel innovation, this program offers a comprehensive journey into the realm of informed decision-making and strategic insights. Through an engaging curriculum, hands-on projects, and collaborations with industry pioneers, students delve into cutting-edge techniques in data analysis, interpretation, and application.

Mission

  • To provide an advanced and adaptive curriculum that integrates core computing principles with emerging digital technologies, equipping students to excel in a global technological landscape.
  • To foster a collaborative research environment where students and faculty address complex technological challenges, contributing to advancements in recent trends of the computer era.
  • To develop ethical and responsible leaders who are committed to making a positive impact on society through innovative technological solutions.
  • To build strong industry and community partnerships, offering students practical learning experiences and promoting entrepreneurship and sustainable technological practices.

Vision

To lead in the creation of digital innovators and ethical technologists who drive
sustainable development and societal advancement through excellence in
education, research, and industry collaboration

Course objective

  • Develop foundational knowledge in data science principles and methodologies.
  • Acquire proficiency in data pre-processing, analysis, and interpretation using statistical and machine learning techniques.
  • Master data visualization and communication to effectively convey insights.
  • Explore advanced topics such as deep learning, natural language processing, and big data analytics.
  • Apply data science techniques to real-world projects, demonstrating critical thinking and collaboration skills.

Course outcome

  • Proficiency in data acquisition, preprocessing, and transformation techniques for diverse data sources.
  • Ability to apply statistical analysis, machine learning, and data mining algorithms to extract insights and patterns from large datasets.
  • Competence in designing and implementing data-driven solutions for real-world problems across various domains.
  • Skill in developing scalable and efficient data processing pipelines using advanced tools and technologies.
  • Effective communication of data analysis results and findings to diverse stakeholders, alongside collaboration skills demonstrated in team-based data science projects.

Admission procedure

Check Eligibility (Physics + Maths + Chemistry / Computer)

Board

Category

Theory Marks

Theory + Practical Marks

GSEB

Open

135 / 300

180 / 400

GSEB

Reserve

120 / 300

180 / 400

Other Boards

Open

108 / 240

135 / 300

Other Boards

Reserve

96 / 240

120 / 300

Required Documents
  • SSC
  • HSC
  • GUJCET mark-sheet
  • Leaving certificate (applicable for all)
  • Income certificate
  • Caste certificate, NCL (if applicable)

Curriculum

  • Duration: 4 years
  • Fees: Rs. 70,000
  • Intake: 60
GTU Code Subject Theory(Hrs) Tutorial(Hrs) Practical(Hrs) Credits
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GTU Code Subject Theory(Hrs) Tutorial(Hrs) Practical(Hrs) Credits
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
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GTU Code Subject Theory(Hrs) Tutorial(Hrs) Practical(Hrs) Credits
3110000 Lorem Ipsum 0 0 0 0
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3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
GTU Code Subject Theory(Hrs) Tutorial(Hrs) Practical(Hrs) Credits
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
GTU Code Subject Theory(Hrs) Tutorial(Hrs) Practical(Hrs) Credits
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
GTU Code Subject Theory(Hrs) Tutorial(Hrs) Practical(Hrs) Credits
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
GTU Code Subject Theory(Hrs) Tutorial(Hrs) Practical(Hrs) Credits
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
3110000 Lorem Ipsum 0 0 0 0
GTU Code Subject Theory(Hrs) Tutorial(Hrs) Practical(Hrs) Credits
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Faculty

Dr. Jignesh Patel
Dr. Hemant Patel
Dr. Sweta Panchal
Prof. Bhoomi Bangoria
Mrs. Monika Hirenbhai Lathiya
Prof. Mayur Jani
Prof. Ami Mehta
Prof. Janvi Maheta
Prof. Sweety Dhabaliya
Miss. Mayuri vaishnav
Miss. Drashti Shaileshbhai Sevara
Miss. Punita P. Chapla
Prof. (Dr.) Rukhsar M.Hala
Mr. Khuman Ravi Kalubhai
Prof. Nilam Parmar
Prof. Sweta Katariya
Milan Jagdishbhai Raiyani
Prof. Heena Goswami
Prof. Janvi Patoliya
Prof. Tulsi Bhalani
Prof. Rishit Kantariya
Prof. Nutan Vanvi
Prof. Chirag Kaneria
Prof. Nita J. Sapara
Prof. Santosh Chaudhri
Mr. Kalpesh Jalu
Mr. Alpesh B. Dobariya
Mr. Ravi Bhatt

Labs and facilities