Experience 2-weeks of Data Science training w/ Harvard Faculty • FREE

  • Attend 2 weeks of LIVE classes, labs & Q&A starting Jan 09
  • Learn from Dr. Protopapas, Director, IACS, Harvard University
REGISTER NOW

Audit Duration

2 weeks, part-time

Program Format

Live, Online

Timing

Evening sessions
$750

Fee

100% FREE

“We bring you the same world class learning that students at Harvard experience.”

Dr. Rahul Dave
Chief Scientist at Univ.AI

Former Lecturer, Harvard University

You learn LIVE from top professors and exceptional teaching assistants

As a audit student, you will get access to everything except exercises, homework and group projects.

Why audit a course?

You get to learn LIVE from Dr. Pavlos Protopapas, Scientific Director, IACS, Harvard University. He heads the Data Science department at Harvard. If you are considering a career in Data Science, or want to get a glimpse of the learning experience at Univ.AI, this is your chance to do so for FREE.

We will host 2 exclusive Q&A sessions with our CEO, LIVE online forums as well as mixer activities for audit students.

At Univ.AI, we bring you state-of-the-art learning at a highly accessible cost. For well-prepared learners, we offer an Income Sharing Agreement (ISA) with zero upfront tuition. We have also put together an array of tuition options to make our programs affordable to all. Learn more

Meet the Faculty

Working professionals & students from diverse backgrounds go on to sought-after career opportunities

Student Stories

Varshini Reddy

Incoming graduate student at Harvard University

"Univ.AI gave me a structured learning environment. The program helped me understand why one algorithm worked better than another for a given application. The quality of the peer group and the personalized time devoted by the professors are two things that I really helped me gain conceptual clarity”

Olga Graph

Phd Mathematics, Technical University, Munich

“The learning experience at Univ.AI is highly engaging, interactive and lively. It is most definitely on par with the best universities in the world. I especially enjoyed the teaching style of Dr. Protopapas and the high level of care and dedication displayed by the academic team.”

Padmaja Bhagwat

Data Scientist at Glance, Ex- VMware

“My growth has been tremendous! All the sessions and assignments that I've done as part of this course are extremely relevant in real world applications. In fact these skills, along with the amazing peers that I met in this course helped me in seemless transition from my Software Developer role at VMware to Data Scientist role Glance. My new role requires me to pick up new tools quickly, and I think its because of my training at Univ.ai that I can adapt with great ease."

Sakthisree Venkatesan

Machine Learning Lead at Metro Services

“The mentorship we got during the program was a perfect complement to learning from top faculty. The curriculum is challenging, but for the committed students the learning experience is exceptional.  I was surprised at the pace at which I was able to develop my expertise with Univ.AI.”

Move left
Move right

Courses covered in Master ML & AI

The Master ML & AI program prepares students for sought after jobs in AI & Data Science.
As an audit student, you will get access to the first 2-weeks of [AI-1].

Week 1:
KNN regression, linear regression, multi- and poly- regression, model selection using training/validation and cross validation.
Week 2: Inference in linear regression, regularisation: ridge, lasso and elastic net regressions

AI-1: AI Basics

You will become familiar with and gain expertise in Supervised Learning models including regression models (KNN, linear, multi, poly) and classification models (KNN, Logistic). You will then learn about Modern Neural Networks.

DS-1: Data Science Basics

You will learn how to get, clean, and process data from different sources. You will then gain skills in exploratory data analysis, visualization, and communication. You will learn to build classification and recommendation engines.

AI-2: Convoluted Neural Networks

Continue your data science journey with convolutional neural networks. Obtain a deeper intuition with network architecture choices, activation functions feed forward and auto encoders. At the end of this course, you will be able to run advanced machine learning models and apply them to practical image recognition problems.

AI-3: Language Models

This is an advanced course for developing proficiency with Natural Language Processing. You will start with the traditional language models, learn about word embeddings, attention and then move on to transformer models. At the end of this course, you will be able to build efficient language models, and tell how well they are performing.

DS-2: Data Science II

You will develop your ability to use generative models and clustering. You will learn about text and tree models, ensembles, recommendation systems, clustering, and Bayesian Statistics.

AI-5: Productionizing AI (MLOps)

This is a 8 weeks (plus 4-6 weeks of extended project) hands-on course on industrial AI concepts & practices. This advanced course is ideal for those who have completed AI-3, AI-4A or AI-4B, or have equivalent preparation to join this course directly. At the end of the course, you will be proficient at applying cutting-edge skills to solve real-world problems. You will be well prepared for top employment opportunities worldwide. We guarantee top-tier placements to exceptional performers in the program (who complete the program with an ‘A’ grade). Direct admission (for those who have not taken AI-3, AI-4A or AI-4B) to the course is through an application followed by an interview.

AI-4A: Reinforcement Learning(Elective)

This advanced course will provide a fundamental understanding of the concepts behind Reinforcement Learning and how to apply them to real-world problems. The course covers the basic concepts, dynamic programming, Q-learning and Policy Gradient Methods. At the end of this module, you will be able to efficiently work with reinforcement learning problems.

AI-4B: Generative Models(Elective)

This advanced course will give an overview of network building blocks, followed by a review of Generative Adversarial Networks and their applications. The course also touches on latent space interpretation. At the end of this module, you will be able to build effective generative adversarial networks.

What you will get

  • 10 LIVE sessions including classes, mentored labs and office hours
  • LIVE forums to interact with peers as well as mixer activities
  • 2 Q&A sessions with CEO

Who should register?

  • Students and working professionals seeking top careers in Data Science
  • Those considering switching careers and exploring Data Science as an option
  • Candidates considering enrolling for the next cohort of Master ML & AI at Univ.AI

Program fee

FREE for a 2-week audit

Full program fee: ₹3,00,000 or ZERO Upfront Fee Income Sharing Agreement

How to register?

To book your spot, please submit this registration form before 6pm (IST) on Jan 9.

The welcome session is at 7pm (IST) on Sun, Jan 9.