;

TLP Program

TLP Program Structure

Spread over eight terms, each averaging four weeks, the program has four intertwined threads:

Artificial Intelligence
&
Machine Learning Core

Foundations in math and programming followed by 3 courses and labs in machine learning and artificial intelligence. Coursework is supplemented by labs and students work on live projects. Advanced technical courses in computer vision and natural language processing.

Design Thinking & applications of
data science

Students undergo a broad series of technical courses ranging from Design Thinking, Systems Thinking, Human Computer Interaction, Data Visualization and Product Management. Students also undertake courses in application of data science in digital health, cybersecurity and smart agriculture. These courses prepare students to design products and to understand applications of data science in the real world.

Entrepreneurial Challenge Lab
& Capstones

A 12 week Challenge Lab that takes them on a mini-entrepreneurial journey where students work in teams, identify a need, test the market, build a prototype, pitch to investors. Students develop the ability to work in teams, craft a venture and take it to market
12 week Industry/ Research Capstones, AI-ML centric (includes 8 weeks onsite).

Understanding Self
&
Leadership

Experiential courses involving goal setting, self reflection, group dynamics and leadership. Each student is also assigned a distinguished mentor who is an eminent business leader or entrepreneur.

TLP's global faculty talks about the coursework

TLP ACADEMIC CALENDAR 2022-2023

  • Introduction to Computing Infrastructure
  • Introduction to Python and Programming
  • Mathematics for DS and AI (Part 1)
  • Human Computer Interaction
  • Grand Challenge Lecture Series (Masterclass)

  • Introduction to AI
  • Data Visualisation
  • Mathematics for DS and AI (Part 2)
  • Grand Challenge Lecture Series (Masterclass)
  • Innovating Language: Effective Communication of Technology Leaders

  • Design Thinking
  • Machine Learning 1
  • Machine Learning Lab 1
  • Data Structures and Algorithms
  • Foundations of Leadership
  • Grand Challenge Lecture Series (Masterclass)
  • Persuasive Presence - 1

  • Projects and Applications of Data Science (Part 1)
  • Machine learning 2
  • Machine learning 2 lab
  • Introduction to Challenge Lab

  • Leadership and Group Dynamics
  • Productionizing ML on the cloud
  • ML for better business decisions
  • Social Entrepreneurship + Product Management (PM)
  • Challenge Lab Brainstorms

  • Designing our Lives
  • Capstones (Entrepreneurial or Industrial or Academic)

  • Systems Thinking
  • Computer Vision
  • Projects and Applications of Data Science
  • Machine Learning 3
  • Conclusion of Challenge Lab/Capstones
  • Persuasive Presence 2

  • 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

TLP Coursework

The world is in the midst of a dual crisis—health and economics—that threatens to disrupt nearly everything. One inevitable consequence is that entrepreneurial skills and innovation leadership have become critical to a successful career in tech. In this intensive bootcamp, students learn how Leadership is the key to success in all technology pursuits—from the corporate world to the startup journey .


Ken Singer

Managing Director
Sutardja Centre for Entrepreneurship
UC Berkeley


Moor Xu

Game Master
Sutardja Centre for Entrepreneurship
UC Berkeley

Term 1

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.

Dr. Rajeev Barua

University of Maryland, College Park


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.

Dr. Sudarshan Iyengar

Head, Department of Computer Science & Engineering
IIT Ropar


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

Dr. Sudarshan Iyengar

Head, Department of Computer Science & Engineering
IIT Ropar


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.

Dr. Sudheendra Hangal

CEO, Amuse Labs
Ph.D Stanford University


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.

Dr. Prashanth Suresh Kumar

Assistant Professor, Plaksha University

Term 2

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.

Dr. Saumya Jetley

Faculty at Plaksha University.


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.

Venkatesh Rajamanickam

Professor
Industrial Design Centre
IIT Bombay


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.

Dr. Sebastien Focaud

Executive Technologist, Palo Alto Strategy Group


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.

Dr. Vishal Garg

Professor, Plaksha University
Dean Academics


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.

Dr. Brainerd Prince

Faculty at Plaksha University.

Term 3

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.

Dr. Jitesh Panchal

Professor of Mechanical Engineering
Purdue University

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.

Dr. Vaneet Gupta

Professor of Industrial Engineering
Purdue University

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.

Dr. Vaneet Gupta

Professor of Industrial Engineering,
Purdue University

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

Dr. Aakash Tyagi

Professor of Practice
Texas A&M University
Computer Science and Engineering

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."

Dr. Dwight Jaggard

Chair, Faculty Senate
University of Pennsylvania

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.

Amit Kumar

Freelancer, Communications trainer, coach & consultant

Term 4

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.

Alexander Fred-Ojala

University of California, AI & Blockchain Director, Learn2Launch
CEO & Co-founder Predli & MasterExchange

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.

Mark Searle

Lecturer & Industry Fellow
Sutardja Center for Entrepreneurship
UC Berkeley

Term 5

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.

Dr. Kenwyn Smith

Professor of Organizational Behavior
University of Pennsylvania

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.

Ramesh Soni

Director of Technology, Nagarro

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.

Srikanth Velamakanni,

Co-founder, Group Chief Executive & Vice-Chairman,
Fractal Analytics

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.

Ananda Sengupta

Managing Director, Telecom BU, Nagarro

Pillar: Entrepreneurial Challenge Lab and Capstones

Credits: 1.5

Core

Mark Searle

Pillar: Entrepreneurial Challenge Lab and Capstone

Credits: 1.5

Core

Lecturer & Industry Fellow
Sutardja Center for Entrepreneurship
UC Berkeley

Term 6

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.

Dr. Rachel Dzombak

Digital Transformation Lead
Emerging Technology Center, Software Engineering Institute
Carnegie Mellon University

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.

Term 7

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.

Dr. Robert Kenley

Professor of Engineering Practice in Industrial Engineering
Purdue University

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.

Dr. Saumya Jetley

Faculty at Plaksha University

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.

Alexander Fred-Ojala

University of California, AI & Blockchain Director, Learn2Launch CEO & Co-founder Predli & MasterExchange

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.

Alexander Fred-Ojala

University of California, AI & Blockchain Director, Learn2Launch CEO & Co-founder Predli & MasterExchange

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.

Amit Kumar

Freelancer, Communications trainer, Coach & Consultant

Term 8

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.

Dr. Sebastien Focaud

Executive Technologist, Palo Alto Strategy Group

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.

Dr. Monojit Choudhury.

Principal Data and Applied Scientist, Turing India – Microsoft

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

Blog

How does Technology Leaders Program (TLP) Enhance Machine Learning and AI Experience Through Challenge Lab and Capstones?

TLP curriculum integrates coursework in Artificial Intelligence, Machine Learning, Design Thinking, Systems Thinking, applications of data science, entrepreneurship and an understanding of self and leadership. Experiential learning at TLP takes place via real-world projects. These include:

1. Capstones – 12 weeks

2. Challenge Lab – 12 weeks

Read More

How does Technology Leaders Program (TLP) Enhance Machine Learning and AI Experience Through Challenge Lab and Capstones?

What is Technology Leaders Program? How is TLP different from any other AI and ML programs?

What is Technology Leaders Program?

Technology Leaders Program (TLP) is a new-age postgraduate program, designed by a global community of CEOs, entrepreneurs, and academia, for a world that is being transformed by technology. The course is co-designed and co-delivered by UC Berkeley.

Read More

What is Technology Leaders Program? How is TLP different from any other AI and ML programs

Career opportunities after pursuing Technology Leaders Program from Plaksha University

Technology Leaders Program (TLP) is a new-age postgraduate program, designed by a global community of CEOs, entrepreneurs, and academia, for a world that is being transformed by technology. The course is co-designed and co-delivered by UC Berkeley.

TLP interweaves coursework in Artificial Intelligence, Machine Learning, Design Thinking, Systems Thinking, applications of Data Science,

Read More

Career opportunities after pursuing Technology Leaders Program from Plaksha University

Launchpad for Women in STEM

Women in STEM are going to be among the prime drivers of the projected USD 12 trillion GDP growth (USD 12 trillion could be added to global GDP by 2025 by advancing women’s equality, a McKinsey Global Institute report notes).

Plaksha University's Technology Leader Program (TLP) - co-delivered by UC Berkeley, India's only in-residence, one year PGP in AI-ML...

Read More

 Launchpad for Women in STEM

Plaksha’s Shark Tank - Challenge Lab

With innovations frequently disrupting the world (think healthcare, rideshare, ed-tech, travel and hospitality) it's evident that humanity is making a sure shift from the industrial age to a knowledge economy, with a digital-first approach at its core

The availability of manifold digital platforms, access to advanced yet affordable technologies, mentorship, and....

Read More

Plaksha’s Shark Tank - Challenge Lab

Life at Plaksha Campus

Campus life shapes the students in many ways. The place where we spend 2-4 years of our life is more than a living abode. At Plaksha, students enjoy a wholesome, joyful and meaningful campus experience with a variety of activities that invigorate the mind and body.

A mix of sports, social initiatives, green causes, talks and awareness campaigns, cultural and fun activities et al gives students...

Read More