TLP Program

Pillar: Artificial Intelligence and Machine Learning

Credits: 1

Elective

This course explains how modern computer systems work. Spanning introductory topics in computer architecture, assembly language, and operating systems, it shows how these building blocks at different levels synergistically work together to produce a complete computing system. It discusses how the design decisions at different levels are made to satisfy the requirements of speed, concurrency, hardware efficiency, and programmability.

Pillar: Artificial Intelligence and Machine Learning

Credits: 1.5

Core

This introductory course covers foundational concepts and also builds an understanding of data structure and algorithms in Python. Students become comfortable with space and time complexity to optimise code for efficiency of produced code.

Pillar: Artificial Intelligence and Machine Learning

Credits: 1.5

Core

This course aims to introduce mathematical concepts to develop a firm understanding of AI. The foundational course aims to support the students in building the right intuition for the importance of probability, linear algebra and calculus in data science related applications

Pillar: Design Thinking and Applications of Data Science

Credits: 1

Core

This is an introductory graduate-level module on human-computer interaction. The course introduces students to the field of HCI and gives them some experience in conducting experiments with human subjects. It introduces various techniques of evaluation of user interfaces and provides connections between Computer Science and other disciplines.

Pillar: Design Thinking and Applications of Data Science

Grand Challenge Lecture Series is a set of Masterclasses that focus on applying real-world technology applications to solve challenges facing the world. Taught by domain experts in the field, the lectures provide a lens on how societies are solving problems using emerging technologies like AI as well as navigating considerations around effectiveness, accessibility, justice, ethics etc.

The Masterclasses expose students to grand challenge themes via real-life projects. They create a sense of planet-conscious decision-making mindset, and Connect course learnings to real-world applications.

Pillar: Artificial Intelligence and Machine Learning

Credits: 1

Core

This introductory course on Artificial Intelligence gives students an overview while helping them understand how standard tools, techniques and algorithms are situated in this space. Students build a mental map of the field, its variability in terms of problem formulations, and standard techniques for different groups of problem formulations.

Pillar: Design Thinking and Applications of Data Science

Credits: 1

Core

This Design course teaches effective visualizations based on principles of graphic design, visual art, perceptual psychology, and cognitive science.

Pillar: Artificial Intelligence and Machine Learning

Credits: 1

Core

The class will help revise some foundational mathematical concepts in Probability and Matricial/Vectorial calculus, and show how they are applied to Machine Learning and other business aspects.Through practical sessions, students will take these concepts and build themselves some basic Machine Learning solutions in Python and run analysis.

Pillar: Design Thinking and Applications of Data Science

Grand Challenge Lecture Series is a set of Masterclasses that focus on applying real-world technology applications to solve challenges facing the world. Taught by domain experts in the field, the lectures provide a lens on how societies are solving problems using emerging technologies like AI as well as navigating considerations around effectiveness, accessibility, justice, ethics etc.

The Masterclasses expose students to grand challenge themes via real-life projects. They create a sense of planet-conscious decision-making mindset, and Connect course learnings to real-world applications.

Pillar: Understanding Self and Leadership

Credits: 1

Core

Technological innovations need to be in perpetual communication with the world it is building.The STEM fraternity needs cognitive, linguistic, and communicative capacities that are not directly part of a STEM curriculum. This course looks at 6 capacities that are going to enable engineers to communicate technological innovation to various stakeholders effectively.

Pillar: Design Thinking and Applications of Data Science

Credits:1

Core

This course offers hands-on project-based learning experience on the Design Thinking methodology. The topics covered include an introduction to Design Thinking, problem formulation, divergent and convergent thinking, idea generation, idea selection, prototyping, and testing. The course provides tools to support different aspects of Design Thinking.

Pillar: Artificial Intelligence and Machine Learning

Credits: 1

Core

This course lays the foundation for Machine Learning by introducing the students to classical machine learning models like linear regression, support vector machines, decision trees, and boosting algorithms among a few before venturing into basics of neural networks and clustering algorithms. It is paired with its lab that focuses on the applied aspects of Machine Learning.

Pillar: Artificial Intelligence and Machine Learning

Credits: 1

Core

This course helps students understand the implementation and application of popular Machine Learning algorithms (prior to deep learning). It also provides a comprehensive theoretical and applied understanding of the subject.

Pillar: Artificial Intelligence and Machine Learning

Credits: 1

Core

This course explains the specification and implementation of basic abstract data types and their associated algorithms including stacks, queues, lists, sorting and selection, searching, graphs, and hashing; performance tradeoffs of different implementations and asymptotic analysis of running time and memory usage

Pillar: Understanding Self and Leadership

Credits: 1

Core

"The goal of this course is to discover how and where students can best make their contribution to the world. This course will also increase their capacity to lead effectively throughout their career and will enhance their performance, course involves understanding and learning – through reflection on self experience and the feedback from others – about yourselves and about working successfully with others. These abilities are essential in meeting critical personal, interpersonal, and organizational challenges in India and throughout the world."

Pillar: Design Thinking and Applications of Data Science

Grand Challenge Lecture Series is a set of Masterclasses that focus on applying real-world technology applications to solve challenges facing the world. Taught by domain experts in the field, the lectures provide a lens on how societies are solving problems using emerging technologies like AI as well as navigating considerations around effectiveness, accessibility, justice, ethics etc.

The Masterclasses expose students to grand challenge themes via real-life projects. They create a sense of planet-conscious decision-making mindset, and Connect course learnings to real-world applications.

Pillar: Understanding Self and Leadership

Credits: 0.5

Core

This course helps students to acquire critical communication competencies. They learn to craft content, make a persuasive presentation, and engage and influence their audience.

Pillar: Design Thinking and Applications of Data Science

Credits: 1

Core

This course gives a hands-on experience of working on real-world data problems and applications. It looks at solving data problems end- to-end. It also showcases powerful tools from the Data Science toolbox to build and deploy models and systems end-to-end. The course focuses on utilizing standard Machine Learning algorithms.

Pillar: Artificial Intelligence and Machine Learning

Credits: 0.5

Core

This second course in a sequence of two courses is intended to extend the foundations built in Machine Learning I to Deep Learning and other more contemporary models. It is intended to be taken along with its associated lab which focuses on the applied aspects of Machine Learning.

Pillar: Artificial Intelligence and Machine Learning

Credits: 1

Core

This course is paired with Machine Learning II and teaches students the implementation and application of popular Machine Learning algorithms. It also provides a comprehensive theoretical and applied understanding of deep learning algorithms.

Pillar: Entrepreneurial Challenge Lab and Capstones

Credits: 1.5

Core

Challenge Lab is an experiential-learning course in entrepreneurship. Multidisciplinary student teams will work together on real world deliverables. Over the course of the semester, students work in small teams, validate their initial ideas with users, build and launch a working prototype, and develop and present a cogent business plan.

Pillar: Understanding Self and Leadership

Credits: 1

Core

This course addresses issues that are central to leadership: followership, wealth creation, wealth distribution, innovation, critical thinking, cross-sector collaboration, intra-group and inter-group dynamics, creating possibilities, organizational politics, shaping the future, abundance and scarcity. It builds on the thinking found in psychology, anthropology, sociology, management, politics, economics and philosophy.

Pillar: Design Thinking and Applications of Data Science

Credits: 1

Elective

This course highlights important concepts needed for productionizing Machine Learning models on the cloud. This would involve cloud basics, serverless deployment, deployment of models using containers, using AWS cloud and sage maker, model performance and monitoring, and more. The course follows a hands-on approach to build and implement end to end Machine Learning pipelines.

Pillar: Design Thinking and Applications of Data Science

Credits: 1

Elective

This Course is intended to be an application course in AI and Analytics techniques that will:
a) Introduce tools needed for complex problem solving at scale.
b) Enable the students to reframe a real-world problem and thereby utilize the appropriate set of tools and techniques to solve them.
c) Equip and motivate the students to build AI and Analytics systems to solve real world problems.
d) Provide students a chance to work on complex real-world problems solved by AI and Analytics Industry.

Pillar: Design Thinking and Applications of Data Science

Credits:

Elective

This course introduces students to the area of product management for technology powered products. During the course, the framework of product management is discussed along with product design and delivery techniques, followed by some practical exercises.

Pillar: Entrepreneurial Challenge Lab and Capstones

Credits: 1.5

Core

Pillar: Understanding Self and Leadership

Credits: 1

Core

This course helps develop in students the capacity to design and redesign their lives. It teaches them how to apply Design & Systems Thinking to observe and notice the world, imagine and design solutions to create change, and experiment with ideas to learn what works.

Pillar: Entrepreneurial Challenge Lab and Capstones

Credits: 4

Core

Students work on live, high quality AI-ML projects. These include industry or research projects or startup ideas, under the mentorship of industry leaders, over the span of 12 weeks.

Pillar: Design Thinking and Applications of Data Science

Credits: 1

Core

This course introduces systems theories for understanding the complex, problematic situations that result from the interaction of scientific and technological changes, values held by individuals and groups, and organizational and social structures. Students learn approaches applicable to the workplace and the public sphere, by addressing them in a way that benefits the people and the environment.

Pillar: Artificial Intelligence and Machine Learning

Credits: 1

Elective

This course takes students through the basics of Image Processing and Feature extraction that lays the foundation for algorithms like CNN. It introduces students to various topics within the field, such as image filters and pre-processing, traditional feature extraction, convolutional neural networks, and adversarial attacks. The focus is on providing a strong foundation of first principles in CV to allow students to apply them in other courses and their future careers.

Pillar: Design Thinking and Applications of Data Science

Credits: 0.5

Elective

This course provides even deeper hands-on experience by tackling real-world data problems and applications. The focus is on deploying and monitoring deep learning models and the complete Data Science pipeline.

Pillar: Design Thinking and Applications of Data Science

Credits: 1

Elective

This course provides an overview of Deep Reinforcement Learning, how it works, and its applications. It also focuses on deploying, productionalizing and implementing deep learning and Machine Learning models, using state-of-the-art tool suites.

Pillar: Entrepreneurial Challenge Lab and Capstones

Credits:

Elective

Pillar: Understanding Self and Leadership

Credits: 0.5

Core

In this course, students continue to acquire critical communication competencies. students will learn how to craft content, make a persuasive presentation, and engage and influence their audience.

Pillar: Design Thinking and Applications of Data Science

Credits: 1

Elective

This course enables students to bring Machine Learning from a business case to production, and develop a practical methodology for efficiently setting up product development cycles.Students learn to apply the Agile & Lean methodology to Machine Learning.

Pillar: Design Thinking and Applications of Data Science

Credits: 0.5

Elective

This course offers hands-on experience of working on real world data problems and applications. The focus is on deploying and monitoring deep learning models and the full data science pipeline.

Pillar: Artificial Intelligence and Machine Learning

Credits: 1

Elective

The course introduces the basic concepts and building blocks of NLP. It enables students to categorize a given NLP problem into its right class and utilize the appropriate set of tools and techniques to solve them. It also equips and motivate students to build NLP systems to solve real -world problems, demonstrate how to read, critique and implement state-of-the-art NLP research publications.

Pillar: Artificial Intelligence and Machine Learning

Credits: 1

Core