Skip to main content


My approach towards getting good at ML — and Data Science in general — is inspired by this response by Andrew Ng on Quora. Here's the TLDR-poster version of it:

This page is a work in progress; I'll eventually add descriptions to the courses.

Catalogue of MOOCs I've taken over the years; listed in reverse chronological order:

Intro to Self-Driving Cars Nanodegree

I'm highly interested in the field of autonomous driving. This is the first course offered by Udacity in the field. It sets up the fundamentals — Bayesian thinking, Kalman filters, A* search, working with matrices in C++, etc. — needed for the much more comprehensive course 2 (which I'll be taking in the near future).

Practical Deep Learning for Coders, v3, Part 1

  • Offered By:
  • Completed: Dec, 2018

Deep Learning Specialization

Sequence Models

Convolutional Neural Networks

Structuring Machine Learning Projects

Machine Learning for Coders

  • Offered By:
  • Completed: Sept, 2018

This was the first course that I took; solid practical introduction to ML.

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

Neural Networks and Deep Learning

Java Build Automation With Maven

Machine Learning & AI Foundations: Decision Trees

Statistics Foundations 1

pandas Essential Training

Artificial Intelligence Foundations Neural Networks

Building and Deploying Deep Learning Applications with TensorFlow

Neural Networks And Convolutional Neural Networks Essential Training

Serverless Machine Learning with Tensorflow on Google Cloud Platform

Serverless Data Analysis with Google BigQuery and Cloud Dataflow

Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform

Google Cloud Platform Big Data and Machine Learning Fundamentals

Interactivity With Javascript

  • Offered By:
  • Completed: Jan, 2016

6.00.2x: Introduction to Computational Thinking and Data Science

Algorithms: Design and Analysis

Using Databases with Python

Databases: JSON Data

Databases: SQL

Databases: XML Data

Relational Algebra

Internet History, Technology, and Security

Introduction to CSS3

  • Offered By:
  • Completed: Oct, 2015

Using Python to Access Web Data

  • Offered By:
  • Completed: Sept, 2015

Responsive Website Basics: Code with HTML, CSS, and JavaScript

  • Offered By:
  • Completed: Sept, 2015

Python Data Structures

  • Offered By:
  • Completed: Sept, 2015

This course comes from the great and powerful Professor Chuck Severance. He's one of the most relatable professors out there, and has single-handedly made learning Python easy — and fun — for thousands of people through his courses (they're available free of charge now!). Had the privilege of meeting him in October, 2018 at PyCon; super awesome guy.

Introduction to HTML5

6.00.1x: Introduction to Computer Science and Programming Using Python

This was the first ever CS MOOC I took, which engendered in me, an intense curiosity for the field. This is a solid introduction to Python, as well as the fundamentals of CS. Professor Eric Grimson is one of the finest teachers out there, period.