Suneel Chakravorty is co-founder of Simple Fractal, a consultancy that designs and develops apps for mobile, web and data. He studied Math and Mandarin at Harvard. In his free time, Suneel enjoys ballroom dancing, playing piano, and getting lost on Youtube.
Python for Data Science
Learn to use Python as a powerful tool for analyzing and exploring data.
Introduction to Python Programming
Learn all about Python, from how to get set up to writing your first script to learning what tools are available to build apps in Python.
Intermediate Python Workshop
In this workshop, you’ll build upon your existing Python foundation through data analysis problems.
Introduction to Python Pandas
A gentle but practical introduction to Pandas, a Python library designed to make your data processing work easier.
Introduction to Data Analytics (outdated)
An introductory overview of what data analytics is all about — what kinds of questions it answers, how different fields can benefit from it, and what tools are used.
Programming for Non-Programmers - The Basics
Are you a creative or entrepreneur that wishes you could speak tech with your web development team? Maybe you wish you could code a bit yourself?
Python Programming 101
In this class, you’ll how to get started with Python, what advantages and disadvantages Python provides as a programming language, and the essentials of programming in Python.
In this workshop series, you'll get a crash course on how to program with Python.
Talk Data to Me
This monthly speaker series brings together industry experts to discuss how data is changing the way businesses run and people live.
General Assembly's 'Product Lab'
In General Assembly's intensive four day "Product Lab", students will receive training on developing a business idea, concept ideation, and pitching a product for launch.
Data Science 101
This workshop will define what data science is, review some of the main tools used by data scientists today, and discuss how they can be implemented in real world work.
In this part-time course, students learn to build robust predictive models, test their validity, and clearly communicate resulting insights.