Integrated B.Sc.–M.Sc. in Computer Science(Data Science) – Industry Integrated Generative AI and Prompt Engineering Track in collaboration with IBM
About Program
The course covers statistics, machine learning, data visualization, and big data technologies. Students work on real datasets to build predictive models and decision-making tools relevant to industries like finance, healthcare, and business analytics.
Program Highlight
Program Outcomes (POs)
| POs | Description |
|---|---|
| PO1 | Fundamental Knowledge: Recognize the fundamental concepts of computers, including software, hardware, and computing technologies, and understand their evolution and applications. |
| PO2 | Design & Development of Solutions: Analyze, design, implement, and evaluate computing solutions such as software systems and web applications to address real-world problems. |
| PO3 | Problem Analysis: Apply principles of algorithms, computer science theory, and mathematical foundations to analyze and model computing problems. |
| PO4 | Analytical Abilities: Demonstrate critical thinking and analytical skills to evaluate situations and propose appropriate computing solutions. |
| PO5 | Modern Tools Usage: Select and apply appropriate techniques, resources, and modern computing tools such as modeling and predictive technologies while understanding their limitations. |
| PO6 | Ethics: Apply professional ethics, responsibilities, and standards while practicing computing technologies in an ethical and socially responsible manner. |
| PO7 | Technical Skills: Develop technical competencies to work as computing professionals or entrepreneurs and contribute productively to society. |
| PO8 | Teamwork & Individual Contribution: Function effectively as an individual and as a member or leader of diverse teams in multidisciplinary environments. |
| PO9 | Project Management: Apply technical and management skills to plan, organize, and execute computing projects and effectively document and present solutions. |
| PO10 | Communication: Communicate effectively with the technical community and society through reports, documentation, presentations, and clear technical explanations. |
| PO11 | Programming Knowledge: Understand and apply programming paradigms such as object-oriented and functional programming along with database technologies to develop software applications. |
| PO12 | Value Added Knowledge: Recognize societal, environmental, cultural, and health-related challenges and contribute computing solutions for sustainable development. |
Program Specific Outcomes (PSOs)
| PSOs | Description |
|---|---|
| PSO1 | Data Analysis and Decision-Making: Analyze and interpret large datasets using statistical, mathematical, and computational techniques for data-driven decision-making. |
| PSO2 | Predictive Modeling and Analytics Tools: Use tools such as Python, R, SQL, Power BI, and machine learning libraries to build predictive models and visual analytics. |
| PSO3 | Applied Data Science and Governance: Apply data science skills in business, research, and public domains while ensuring reproducibility, privacy, and data governance. |
Integrated B.Sc.–M.Sc. in Computer Science(Data Science) – Industry Integrated Generative AI and Prompt Engineering Track in collaboration with IBM - CURRICULUM
Semester 1
| Subject Name | L | T | P | C |
|---|---|---|---|---|
| Programming Fundamentals using C | 3 | 4 | 0 | 4 |
| Basic Electronics | 4 | 0 | 0 | 4 |
| Calculus and Ordinary Differential Equation | 3 | 0 | 1 | 4 |
| Intro to Computer Science | 3 | 0 | 1 | 4 |
| Professional Ethics-I | 2 | 0 | 0 | 2 |
| Introduction to Environmental Science | 2 | 0 | 0 | 2 |
| Hands on Project-I | 0 | 2 | 1 | 2 |
| Total | 17 | 6 | 3 | 22 |
Semester 2
| Subject Name | L | T | P | C |
|---|---|---|---|---|
| Object-Oriented Programming with C++ | 3 | 2 | 0 | 4 |
| Data Structure and Algorithms-I | 3 | 2 | 0 | 4 |
| Computer Organization and Architecture | 3 | 2 | 0 | 4 |
| Discrete Mathematics | 3 | 0 | 1 | 4 |
| Communication Skills | 2 | 0 | 0 | 2 |
| Indian Knowledge System | 2 | 0 | 0 | 2 |
| Hands on Project-II | 0 | 2 | 1 | 2 |
| Total | 16 | 8 | 2 | 22 |
L = Lecture,
T = Tutorial,
P = Practical,
C = Credits
