Pillar 01
AI-ML & Data Science
Foundational Coursework and Lab work in Statistics, Mathematics and Programming
Pillar 02
ML and Projects & Applications of Data Science
Gaining expertise in implementing AI-ML solutions in practical scenarios
Pillar 03
Design Thinking and HCI
Concepts of ideation, problem-solving, product, and software design practices
Pillar 04
Entrepreneurial Challenge Lab
Ideation to Pitch; Learn to build an entrepreneurial venture
Pillar 05
Capstone Projects
Applying data science techniques to solve practical, real-world problems using real data sources
Pillar 06
Self & Leadership
Cultivate leadership skills, fostering self-discovery and innovation mindset
TLF academic calendar
| Orientation | - | - |
- Leadership for Innovators Bootcamp
| Term 1 | - | 5 weeks |
- Python Fundamentals: An Introduction to Programming
- Probability and Statistics for AI and Data Science
- Introduction to Data Engineering and Data Science
- Data Science Lab - 1
- Foundations of Leadership
| Term 2 | - | 5 weeks |
- Data Structures and Algorithms
- Mathematics for AI
- Data Mining and Advanced Data Analysis
- Data Science Lab
- Introduction to Artificial Intelligence
| Term 3 | - | 5 weeks |
- Fundamentals of Machine Learning
- Design Thinking (AI and data science)
| Term 4 | - | 5 weeks |
- Human Computer Interaction
- Machine Learning (NLP and Computer Vision)
- Projects and Applications of Data Science
| Term 5 | - | 6 weeks |
- Data Communication
- Product Management
- Entrepreneurial Challenge Lab
- AI and Business
| Term 6 | - | 8 weeks |
- Capstone Projects
- Persuasive Presence Bootcamp
- Design Thinking for Data Driven Products
| Term 7 | - | 6 weeks |
- Advanced Topipc Courses
- AI and the World Series
- Masters of Innovation: Crafting Tomorrow's Tech
- Designing our Lives
| Term 8 | - | 6 weeks |
- Design Thinking: Cycle of Data Driven Products for Maximizing Business Outcome
- Projects and Applications of DS (NLP focus)
- Natural Language Processing (NLP)
- Ethics for AI
- Masterclass in Leadership
TLF coursework
Term 1
| Introduction to Data Engineering and Data Science | Prof. Subhasis Ray |
Credits: 1
| Probability and Statistics for AI and Data Science | Prof. Nandini Kannan |
Credits: 1
| Foundations of Leadership | Prof. Dwight Jaggard |
Credits: 2
| Python Fundamentals: An Introduction to Programming | Raghav Awasty |
Credits: 1
| Data Science Lab - 1 | Prof. Srikant Srinivasan |
Credits: 1
Term 2
| Data Structures and Algorithms | Prof. Sandeep Manjanna |
Credits: 1
| Mathematics for AI | Prof. Vivek Deulkar and Prof. Shashikant Pawar |
Credits: 1
| Data Mining and Advanced Data Analysis | Prof. Subhasis Ray |
Credits: 1
| Data Science Lab | Raghav Awasty |
Credits: 1
| Introduction to Artificial Intelligence | Prof. Deepak Khemani |
Credits: 1
Term 3
| Fundamentals of Machine Learning | Prof. Siddharth |
Credits: 3
| Design Thinking for Data Science & Artificial Intelligence | Prof. Jitesh Panchal |
Credits: 2
Term 4
| Human Computer Interaction | . |
Credits: 1
| Machine Learning (NLP and Computer Vision) | . |
Credits: 3
| Projects and Applications of Data Science | Prof. Alexander Fred Ojala |
Credits: 1.5
Term 5
| Data Communication | . |
Credits: 1
| Product Management | Ananda Sengupta |
Credits: 1
| Entrepreneurial Challenge Lab | Mark Searle and David Law |
Credits: 4
| AI and Business | . |
Credits: 1
Term 6
| Capstone Projects | . |
Credits: 4
| Persuasive presence Bootcamp | Mr. Amit Kumar |
Mandatory Pass Requirement
| Design Thinking for Data Driven Products | Prof. Sebastien Foucaud |
Credits: 1
Term 7
| Advanced Topic Courses | . |
Credits: 1
| AI and the World Series | . |
Credits: 0.5
| Masters of Innovation: Crafting Tomorrow's Tech | . |
Credits: 1
| Designing our Lives | Prof. Rachel Dzombak |
Credits: 1