Machine Learning and Data Science - ML2


ML2: Machine Learning and Data Science Part 2

Welcome to the First Edition of ML-2(also called DS-2). This is the second foundational course in data science. It follows DS 1 and builds on them. It develops your ability to use generative models and clustering. We introduce you to tree based models, ensemble models and boosting. The course will introduce you to bayesian models and culminates with decision theory and model interrogation, and how to deal with imbalanced data situations.After you finish this module, you will be ready to run complex data science analyses on all kinds of data on your own, dealing with data imbalance, and finally being able to make decisions with the models. This page introduces you to the team, the basic instructions, the schedule, and various elements of our class.

Interested in joining?

If you would like to apply to this program, please go here.

The Team

Dr. Rahul Dave

Dr. Rahul Dave, former Data Science faculty at Harvard University, will be your instructor for Data Science 2. He was on the original team for Harvard’s famous Data Science course, cs109, and has taught machine learning, statistics, and AI courses, both at Harvard and at multiple conferences and workshops. You can read more about him here. In addition to the classes, you can schedule problem-solving classes with the faculty and mentors throughout the rest of the week.

The teaching assistants for the duration of this course are:

Anusha Sheth

Arya Mohan

The Coursework

We have very carefully designed the coursework to give you, the student, a wholesome learning experience.Each week shall include:

Before the session begins, students are expected to complete a pre-class reading assignment and attempt a quiz based on the same.A session will have the following pedagogy layout which will be repeated three times:

After the session, students are expected to complete a short post-class quiz based on the principal concepts covered in class and optional post-class reading will be provided.

Lab - What to expect

A lab is a TA driven one-hour session that is divided into 3 major parts. -

Course Syllabus

The Welcome Session

There will be a Welcome Session scheduled on 8th March 2021 at 9:00 PM IST for all registered students. Please check your mail for more information.

Course Schedule

NOTE: Below timings are in IST

Course Prerequisites

This is a part of ML-X Course, hence you should have completed ML-1 before this

Diversity & Inclusion

We actively seek and welcome people of diverse identities, from across the spectrum of disciplines and methods since Artificial Intelligence (AI) increasingly mediates our social, cultural, economic, and political interactions [1].We believe in creating and maintaining an inclusive learning environment where all members feel safe, respected, and capable of producing their best work.We commit to an experience for all participants that is free from – Harassment, bullying, and discrimination which includes but is not limited to:Offensive comments related to age, race, religion, creed, color, gender (including transgender/gender identity/gender expression), sexual orientation, medical condition, physical or intellectual disability, pregnancy, or medical conditions, national origin or ancestry.Intimidation, personal attacks, harassment, unnecessary disruption of talks during any of the learning activities.

Logistics

What you need to begin?

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