Fellowship | Program

Program

TLF Program Experience

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

Data-X Coursework

Series of courses in Artificial Intelligence and Machine Learning, Design and Systems thinking to learn to apply technology to build holistic solutions.

Real-world Projects

12 week Challenge Lab to identify a need, market test, build a prototype, pitch to investors. 12 week Industry/ Research Capstone project, AI/ML centric (includes 8 weeks onsite).

Guest Sessions

Grand Challenge Lecture Series by domain experts on real-world AI/ML applications. Radical thinkers and global leaders share their ideas and walk you through their journey.

Leadership and mentoring

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

Data-X Coursework

Foundation

  • Review of math prerequisites: Linear algebra, Probability and Statistics, Calculus
  • Essentials in Computer Science including cryptographic elements

AI and ML Core

  • Data Science and Machine Learning I
  • Data Science and Machine Learning I Project Lab
  • Data Science and Machine Learning II including Neural Networks and Natural Language
  • Data Science and Machine Learning II Project Lab
  • AI systems: Data tools, distributed systems, cloud computing, performance management

Design & Systems thinking

  • Design thinking
  • UI Design and Development plus Lab: Apply by developing a web / mobile app
  • Human Computer Interaction
  • Engineering Ethics
  • Design Cyber Physical systems for Safety

* The list is indicative not exhaustive

Real-world Projects

Challenge Lab

  • Duration: 12 weeks
  • Hands-on, team based project (4-5 students each) to create products or start-up ideas
  • Identify a real-world opportunity, develop a working prototype, hone your storytelling skills and make a pitch to a panel of investors
  • Mimics real world technology venture creation
  • Learning by doing, peer learning and self-reflection is central to pedagogy

Industry or Research Capstone

  • Duration: 12 weeks with 8 dedicated weeks onsite
  • Intense AI/ML centric capstone projects (in teams of 3-5) structured as any of:
    • Industry sponsored project
    • Research project supervised by a scientist/ researcher
    • Teams may bid to work on a start-up (subject to approval of Capstone Committee)
  • Each team will have 1 industry mentor and 1 faculty mentor
  • Capstone Committee to oversee interim milestones and final presentation

Guest Sessions: Grand Challenge Lecture Series



    • Domain experts in areas such as Air, Water, Agriculture, Health, Future Mobility, Political Science walk you through their journey of applying AI, ML and Data Science in industry and society.
    • Radical thinkers, inventors and entrepreneurs share their ideas and walk you through their journey of creating impact.

Leadership and mentoring

Structured coursework

Self reflection, Goal setting, Critical thinking, Storytelling, Group dynamics and Agile methods, delivered in a structured format over the year. Our coursework will help you discover your leadership potential and motivate you to take on big challenges.

Personal mentoring

Choose your personal mentor among CXOs, academicians or entrepreneurs. Have free-wheeling discussions on life, career and philosophy. This is an opportunity to build lifelong relationships.

ACADEMIC CALENDAR

The inaugural edition of the Plaksha Tech Leaders Fellowship
will run from August 2019 to June 2020.

Orientation

Aug 1 - Aug 4

Term 1

Aug 5 - Aug 30

Term 2

Sep 2 - Oct 11

Term 3

Oct 14 - Nov 22

Break

Nov 25 - Nov 29

Term 4

Dec 2 - Jan 10

Term 5

Jan 13 - Feb 21

Term 6: Capstone

Feb 24 - Apr 17

Career Week I

Apr 20 - Apr 24

Term 7

Apr 27 - May 22

Career Week II

May 25 - May 29

Term8

Jun 1 - Jun 26

Orientation

Aug 1 - Aug 4

Term 1

Aug 5 - Aug 30

Term 2

Sep 2 - Oct 11

Term 3

Oct 14 - Nov 22

Break

Nov 25 - Nov 29

Term 4

Dec 2 - Jan 10

Term 5

Jan 13 - Feb 21

Term 6: Capstone

Feb 24 - Apr 17

Career Week I

Apr 20 - Apr 24

Term 7

Apr 27 - May 22

Career Week II

May 25 - May 29

Term8

Jun 1 - Jun 26

Note: The dates mentioned here are indicative and subject to minor adjustments.

Have questions?