ANNOUNCEMENTS
The Four Year Under-Graduate Programme (FYUP) in Data Science (BSc Honours/BSc Honours with Research) have been designed in accordance with the National Education Policy (NEP) 2020 and the recent guidelines issued by the University Grants Commission with in-built options of Multiple Entry and Multiple Exit mapped with employability opportunities.
Eligibility
A Senior Secondary School Examination (10+2) certificate in any discipline or equivalent, from a recognized Board of Education with at least 50% marks in aggregate. There is no upper age bar.
Degree in Data Science: B.Sc./ B.Sc. (Honours)/ B.Sc.(Honours with Research)
Data science is an interdisciplinary, rapidly emerging branch of learning that facilitates extracting information from large datasets using scientific methods that combine mathematics, statistics, computer science, machine learning, artificial intelligence, deep learning, and domain-specific knowledge.
The proposed interdisciplinary FYUP in Data Science will provide formal training in various quantitative techniques, along with a unique blend of theory and practice interwoven in a qualitative matrix. The programme will facilitate a systematic amalgamation of widespread knowledge under a common platform.
The programme has been innovatively designed that will provide students to have in-depth study of interdisciplinary major in Data Science with an option to choose from interdisciplinary minors and skill-based courses relating to a chosen thematic area – environmental studies, climate science, geoinformatics, economics and management studies.
Admission Criteria
Admission to FYUP and FYIPP in Data Science shall be on the basis of merit of marks secured in 10+2 or equivalent examination in aggregate of best of three subjects and one language.
• Designed using multi- and inter-disciplinary approaches, embedded with community engagement and service, skill & ability enhancement, and value-added courses with an intent to provide holistic education.
• Interlinks data science with domain knowledge – Environmental Studies, Climate Science, and Geoinformatics.
• Provides systematic amalgamation of widespread knowledge under a common platform.
• Extensive use of technology in teaching and learning that encompasses sciences, social sciences, arts, and humanities.
• Skill-based human resource development under various thematic areas.
• Mapped with the application of data science to achieve all the Sustainable Development Goals (SDGs) and National Missions.
• Enriched from modern science to basic understanding and ancient Indian traditional knowledge and practices.
• Enables lifelong learning through Multiple Entry and Multiple Exit (ME-ME) options leading to – One-year UG Certificate, Two-year UG Diploma, Three-year UG Degree, Four-year UG Degree (Honours), Four-year UG Degree (Honours with Research)
Year | Courses | Credits | Duration* |
First Year | |||
1st Semester | 3 major courses of 10 credits, 1 minor elective course of 4 credits, 1 multidisciplinary course of 2 credits, 1 AEC of 2 credits, 1 SEC of 2 credits and 1 VAC of 2 credits | 22 | 15 weeks |
2nd Semester | 2 major courses of 6 credits, 1 major elective of 3 credits, 1 minor elective course of 3 credits, 1 multidisciplinary course of 3 credits, 1 AEC of 3 credits, 1 SEC of 2 credits and 2 VACs of 4 credits | 24 | 15 weeks |
Vocational course/ Summer internship project | To Exit with UG-Certificate in Data Science | 4a | 8 weeks |
UG - Certificate in Data Science | a. Students exiting the programme after securing minimum 40 credits will be awarded UG-Certificate in Data Science provided they secure additional 4 credits in work-based vocational courses offered during summer-term or internship/apprenticeship in addition to 6 credits from skill-based courses earned during 1st and 2nd semester. | ||
Second Year | |||
3rd Semester | 3 major courses of 9 credits, 1 minor elective course of 3 credit, 1 multidisciplinary elective course of 4 credits, 1 AEC of 3 credits, 2 SEC of 5 credits | 24 | 15 weeks |
4th Semester | 3 major courses of 12 credits, 1 major elective of 4 credits, 1 minor elective course of 4 credits | 20 | 15 Weeks |
Vocational course/ Summer internship project | To Exit with UG-Diploma in Data Science | 4b | 8 Weeks |
UG - Diploma in Data Science | b. Students exiting the programme after securing minimum 40 credits will be awarded UG-Diploma in Data Science provided they secure additional 4 credits in work-based vocational courses offered during summer-term or internship/apprenticeship in addition to 6 credits from skill-based courses earned during 1st or 2nd year. | ||
Third Year | |||
5th Semester | 3 major courses of 12 credits and 2 minor elective courses of 8 credits | 20 | 15 weeks |
6th Semester | 3 major courses of 12 credits and 2 minor elective courses of 8 credits | 20 | 15 Weeks |
Summer internship project | In case the student has not credited 4 credit summer internship during 1st and 2nd year, student has to earn 4 credit summer internship in 6th semester. | 4c | 8 Weeks |
B.Sc. in Data Science | c. Students exiting the programme after securing minimum 120 credits will be awarded 3-Years BSc Degree in Data Science provided they secure additional 4 credits in work-based vocational courses offered during first or second year summer-term or internship/apprenticeship in addition to 6 credits from skill-based courses earned during 1st and 2nd year. In case the student has not credited 4-credit summer internship during 1st / 2nd year / 3rd year, student has to earn 4-credit summer internship in 8th semester | ||
Fourth Year | |||
7th Semester | 3 major courses of 10 credits, 1 major elective courses of 4 credits, 2 minor elective courses of 6 credits | 20 | 15 weeks |
8th Semester | 5 major courses of 20 credits, 1 minor elective course of 4 credits in Data Science (Hons) | 24 | 15 Weeks |
Research Project/Dissertation | Students who secure 75% marks and above in the first six semesters and wish to undertake research at the UG level can choose a research stream in the fourth year by doing a research project or dissertation under the guidance of a faculty member of the University; the students who secure at least 160 credits, including 12 credits from a research project/dissertation can exit the programme with 4-year UG Degree (Honours with Research) in Data Science. | 12 | |
Summer internship project | In case the student has not credited 4-credit summer internship during 1st and 2nd year, student has to earn 4-credit summer internship in 6th semester. | 4d | 8 Weeks |
B.Sc. (Hons./Hons. with Research) in Data Science | Students exiting the programme after securing minimum 160 credits will be awarded 3-Years BSc Degree in Data Science provided they secure additional 4 credits in work-based vocational courses offered during first or second year summer-term or internship/apprenticeship in addition to 6 credits from skill-based courses earned during 1st and 2nd year. d. In case student not credited 4-credit summer internship during 1st / 2nd year / 3rd year has to earn 4-credit summer internship in 8th semester. |
AEC: Ability Enhancement Courses; SEC: Skill Enhancement Courses; VAC: Value Added Courses
Semester 1 | ||||||
Course No. | Course Title | Type | Number of Credits | No. of L-T-P | Course Coordinator | Course Offered |
AEC 101 | Communication Skills and Technical Writing | AEC | 2 | 0-0-0 | Yes | |
MDC 101 | Environment and Society | Multidisciplinary | 2 | 0-0-0 | Yes | |
MDC 103 | Data Science Fundamentals | Major | 2 | 0-0-0 | Yes | |
NDS 115 | Principles and Concepts of Sustainability | VAC | 2 | 0-0-0 | Yes | |
NDSXXX | Any one Minor Course from Environment/ Economics/ Management | Minor | 4 | 0-0-0 | Yes | |
SEC 101 | Fundamentals of Computers and Programming | SEC | 2 | 0-0-0 | Yes | |
UDS 101 | Statistics for Data Science | Major | 4 | 0-0-0 | Yes | |
UDS 103 | Mathematics for Data Science | Major | 4 | 0-0-0 | Yes | |
UES 101 | Ecology and Ecosystems | Minor | 4 | 0-0-0 | Yes | |
UES 103 | Earth and Earth Surface Processes | Minor | 4 | 0-0-0 | Yes |
Semester 3 | ||||||
Course No. | Course Title | Type | Number of Credits | No. of L-T-P | Course Coordinator | Course Offered |
NDS 201 | Data Wrangling and Visualization | Major | 3 | 0-0-0 | Yes | |
NDS 203 | Data Structures and Algorithm | Major | 3 | 0-0-0 | Yes | |
NDS 205 | Data Mining and Data Analysis | Major | 3 | 0-0-0 | Yes | |
NDS 215 | Modern Indian Language 2 | AEC | 3 | 0-0-0 | Yes | |
NDS 217 | Introduction to Geographic Information System | SEC | 3 | 0-0-0 | Yes | |
NDS 219 | Cybersecurity for Data Science | SEC | 2 | 0-0-0 | Yes | |
NDSXXX | Any one Minor Course from Environment/ Economics/ Management | Minor | 4 | 0-0-0 | Yes | |
NES 201 | Atmosphere and Global Climate Change | Minor | 3 | 0-0-0 | ||
NES 203 | Biodiversity and Conservation | Minor | 3 | 0-0-0 | Yes | |
NES 207 | Land and Soil Conservation and Management | Minor | 3 | 0-0-0 | Yes | |
NES 209 | Advanced Statistics | Multidisciplinary | 4 | 0-0-0 | Yes | |
NES 219 | Bioinformatics | Multidisciplinary | 4 | 0-0-0 | Yes | |
NES 221 | Linear Algebra and Discrete Mathematics | Multidisciplinary | 4 | 0-0-0 | Yes |
Semester 4 | ||||||
Course No. | Course Title | Type | Number of Credits | No. of L-T-P | Course Coordinator | Course Offered |
NDS 122 | Project Management | Minor | 4 | 0-0-0 | Yes | |
NDS 122 | Vocational course/ Summer internship project (8-weeks) to Exit with UG-Diploma | Vocational/ Internship | 4 | 0-0-0 | Yes | |
NDS 202 | Artificial Intelligence | Major | 4 | 0-0-0 | Yes | |
NDS 204 | Time Series Analysis | Major | 4 | 0-0-0 | Yes | |
NDS 206 | Object Oriented Programming | Major | 4 | 0-0-0 | Yes | |
NDS 208 | Computer Networks | Major (Elective) | 4 | 0-0-0 | Yes | |
NDS 210 | Business Analytics | Major (Elective) | 4 | 0-0-0 | Yes | |
NDSXXX | Any one Minor Course from Environment/ Economics/ Management | Minor | 4 | 0-0-0 | Yes | |
NES 204 | Natural Hazards and Disaster Risk Reduction | Minor | 4 | 0-0-0 | Yes | |
NES 210 | Water Resources Management | Minor | 4 | 0-0-0 | Yes |
Semester 5 | ||||||
Course No. | Course Title | Type | Number of Credits | No. of L-T-P | Course Coordinator | Course Offered |
NDS 301 | Machine Learning | Major | 4 | 0-0-0 | Yes | |
NDS 303 | Analysis and Design of Algorithms | Major | 4 | 0-0-0 | Yes | |
NDS 305 | Blockchain | Major | 4 | 0-0-0 | Yes | |
NDSXXX | Any one Minor Course from Environment/ Economics/ Management | Minor | 4 | 0-0-0 | Yes | |
NES 301 | Green Technologies | Minor | 4 | 0-0-0 | Yes | |
NES 303 | Solid and Hazardous Waste Management | Minor | 4 | 0-0-0 | Yes | |
NES 305 | Environmental Movement | Minor | 4 | 0-0-0 | Yes | |
NES 307 | Geoinformatics for Resource Management | Minor | 4 | 0-0-0 | Yes | |
NES309 | Business and Professional Communication | Minor | 4 | 0-0-0 | Yes |
Semester 6 | ||||||
Course No. | Course Title | Type | Number of Credits | No. of L-T-P | Course Coordinator | Course Offered |
NDS 302 | Big Data Technology | Major | 4 | 0-0-0 | Yes | |
NDS 304 | Natural Language Processing | Major | 4 | 0-0-0 | Yes | |
NDS 306 | Predictive Modelling and Analytics | Major | 4 | 0-0-0 | Yes | |
NDS 310 | Vocational course/ Summer internship project (8-weeks) to Exit 3-Years BSc Degree | Vocational/ Internship | 4 | 0-0-0 | Yes | |
NDS 310 | Digital Marketing Analytics | Minor | 4 | 0-0-0 | Yes | |
NDSXXX | Any one Minor Course from Environment/ Economics/ Management | Minor | 4 | 0-0-0 | Yes | |
NES 302 | Urban Ecosystem | Minor | 4 | 0-0-0 | Yes | |
NES 304 | Marine Ecology | Minor | 6 | 0-0-0 | Yes | |
NES 306 | Forest Ecology | Minor | 4 | 0-0-0 | Yes | |
NES 308 | Environmental Ethics | Minor | 6 | 0-0-0 | Yes |
Semester 7 | ||||||
Course No. | Course Title | Type | Number of Credits | No. of L-T-P | Course Coordinator | Course Offered |
NDS 401 | Soft - Computing | Major | 4 | 0-0-0 | Yes | |
NDS 403 | Data Warehousing and Data Pipeline | Major | 4 | 0-0-0 | Yes | |
NDS 405 | Internet of Things | Major (Elective) | 4 | 0-0-0 | Yes | |
NDS 407 | Research Methodology and Thesis Writing | Major | 2 | 0-0-0 | Yes | |
NDS 409 | Cloud Computing | Major (Elective) | 4 | 0-0-0 | Yes | |
NDS 413 | Principles and Concepts of Sustainability1 | VAC | 2 | 0-0-0 | Yes | |
NDSXXX | Any one Minor Course from Environment/ Economics/ Management | Minor | 4 | 0-0-0 | Yes | |
NES 401 | Ecosystem Processes | Minor | 3 | 0-0-0 | Yes | |
NES 409 | Earth and Environment | Minor | 4 | 0-0-0 | Yes | |
NES 411 | Energy and Environment | Minor | 4 | 0-0-0 | Yes | |
NES 417 | Atmospheric Science | Minor | 4 | 0-0-0 | Yes | |
NES 419 | Climate Change Impact on Natural Systems | Minor | 4 | 0-0-0 | Yes | |
NES 421 | Climate Change Mitigation Approaches | Minor | 3 | 0-0-0 | Yes | |
NES 423 | Principles of GIS & GNSS | Minor | 4 | 0-0-0 | Yes | |
NES 425 | Principles of Remote Sensing | Minor | 4 | 0-0-0 | Yes |
1. VAC Introduce in case students from other institutions have not opted for such courses in B.Sc.
Formal classroom instruction, workshops, hands-on practise, field excursions, case studies, field visits, quizzes, term papers, assignments, and tutorials will be among the pedagogical strategies used. Individual and group projects will be utilised to show specific environmental and social science challenges using a variety of spatial-temporal and time-series information. Interactive workshops and industrial training will be organised with data science and plan execution players and stakeholders from the government, business sector, entrepreneurs, and NGOs. Data science intersects with the environment, climate science, and related business sectors, as well as geoinformatics.
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