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The four-year undergraduate program program in Data Science and Analytics is designed to equip students with the skills needed to analyze and interpret complex data. These programs typically blend mathematics, statistics, computer science, machine learning, and business intelligence to prepare students for careers in data-driven industries.
Our institution proudly offers a comprehensive four-year Under-Graduate program in Data Science and Analytics. This innovative curriculum encompasses Applied Statistics, Data Science, and Data Analytics as the major subjects, complemented by Mathematics as a minor, aligning seamlessly with the vision outlined in the National Education Policy (NEP) of 2020. The primary focus of this programme is to provide a thriving ecosystem to develop data-driven technological solutions based on statistical techniques.
This programme is designed towards lifelong learning by imbibing our ancient and prominent knowledge system in education through the type of courses as — multi-disciplinary, value-added, ability and skill enhancement courses etc. Internships and industry projects are important components included in this program which will cater for advanced industry-required 21st-century analytical skills.
Trained human resource development in the areas of applied Statistics and Data Science who can be further trained expeditiously for advanced applied statistical techniques for data analytics is a major goal of this program. Program will enable students for better employability in industries like IT, manufacturing, education, finance, healthcare, legal and governance, academics etc.
Graduates can pursue roles such as Data Analyst, Data Scientist, AI Engineer, Business Intelligence Analyst, and more.
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| Semester I |
|---|
| Programming for Problem Solving |
| Programming for Problem Solving Practical |
| Minor Course (Opted from the Pool Course offered by University) |
| Ability Enhancement Course (Opted from the Pool Course offered by University) |
| Skill Enhancement Course (Opted from the Pool Course offered by University) |
| Value Added Course (Opted from the Pool Course offered by University) |
| Value Added Course (Opted from the Pool Course offered by University) |
| Multi-Disciplinary Course (Opted from the Pool Course offered by University) |
| Semester II - Course Name |
|---|
| R Programming |
| R Programming Practical |
| Minor Course (Opted from the Pool Course offered by University) |
| Ability Enhancement Course (Opted from the Pool Course offered by University) |
| Ability Enhancement Course (Opted from the Pool Course offered by University) |
| Skill Enhancement Course (Opted from the Pool Course offered by University) |
| Value Added Course (Opted from the Pool Course offered by University) |
| Multi-Disciplinary Course (Opted from the Pool Course offered by University) |
| Semester III - Course Name |
|---|
| Mathematical Expectations & Probability Distributions |
| Introduction to Data Science |
| Introduction to Data Science Practical |
| Data Structures |
| Data Structures Practical |
| Minor Course (Opted from the Pool Course offered by University) |
| Ability Enhancement Course (Opted from the Pool Course offered by University) |
| Skill Enhancement Course (Opted from the Pool Course offered by University) |
| Multi-Disciplinary Course (Opted from the Pool Course offered by University) |
| Semester IV - Course Name |
|---|
| Inferential Statistics |
| Indian Mathematics and Astronomy |
| Database Management Systems |
| Database Management Systems Practical |
| Introduction to Computer Organization |
| Minor Course (Opted from the Pool Course offered by University) |
| Semester V - Course Name |
|---|
| Sampling Theory |
| Regression Analysis |
| Artificial Intelligence and Machine Learning |
| Artificial Intelligence and Machine Learning Practical |
| Data Security and Compliance |
| Data Security and Compliance Practical |
| Major Course (Choose one from a pool of Elective Courses I) |
| Minor Course (Opted from the Pool Course offered by University) |
| Semester VI - Course Name |
|---|
| Multivariate Data Analysis |
| Statistical Simulation |
| Statistical Simulation Practical |
| Data Warehousing & Data Mining |
| Data Warehousing & Data Mining Practical |
| Major Course (Choose one from a pool of Elective Courses II) |
| Minor Course (Opted from the Pool Course offered by University) |
| Internship/ Apprenticeship |
| Semester VII - Course Name |
|---|
| Time Series, Forecasting and Index Number |
| Time Series, Forecasting and Index Number Practical |
| Count Data and Survival Analysis |
| Data Scientist Toolbox |
| Data Scientist Toolbox Practical |
| Text Analytics |
| Text Analytics Practical |
| Major Course (Choose one from a pool of Elective Courses III) |
| Minor Course (Opted from the Pool Course offered by University) |
| Semester VIII - Course Name |
|---|
| Data Visualization Techniques |
| Data Visualization Techniques Practical |
| Deep Learning and Big Data Analytics |
| Deep Learning and Big Data Analytics Practical |
| Internet of Things |
| Internet of Things Practical |
| Major Course (Choose one from a pool of Elective Courses IV) |
| Minor Course (Opted from the Pool Course offered by University) |
| Project |
| Semester II - Course Name |
|---|
| Engineering Mathematics-II |
| Applied Chemistry |
| Semester II - Course Name |
|---|
| Engineering Mathematics-II |
| Applied Chemistry |
Acquire in-depth scientific knowledge of their discipline both in theory and practical, demonstrate basic skills, investigate, apply, and solve the problems in a variety of contexts related to science and technology.
Develop skills to communicate effectively to diverse platforms and contribute meaningfully to different capacities as a leader, team member or individual.
Apply modern tools and techniques to carry out scientific experiments accurately, record, analyze and predict the result for valid conclusion with clear understanding of limitations.
Develop logical thinking and expertise with precision, analytical mind, innovative thinking, clarity of thought, and systematic approach for proving or disproving the facts after mathematical formulation.
Develop elementary computing and soft skills to prepare students for industry, entrepreneurship and higher education with precision, analytical mind, innovative thinking, clarity of thought, expression, and systematic approach.
Able to recognize different value systems and ethical principles; and commit to professional ethics, norms, and responsibilities of the science practice and act with informed awareness to participate in civic life activities.
Enhance ability to elicit views of others and understand the impact of various solutions in the context of societal, economic, health, legal, safety and environment for sustainable development.
Acquire fundamental knowledge for lifelong learning to participate in the extensive context of socio-technological change as a self-directed member and a leader.
PSO 1: Apply computing theory, languages and algorithms, as well as mathematical and statistical models, and the principles of optimization to appropriately formulate and use data analysis.
PSO 2: Apply the principles and techniques of database design, administration, and implementation to enhance data collection capabilities and decision-support systems.
PSO 3: Ability to critique the role of information and analytics in supporting business processes and functions.
PSO 4: Apply the knowledge of data sciences and analytics to develop innovative and inclusive understanding to real-world issues.
PSO 5: Acquire the skills necessary to think critically and communicate effectively about data sciences and analytics and allied domains.
