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Alumni-led Mini-Courses

Mini-Courses on additional topics like Productionization and Quantum Computing put together by our PhD alumni.

Note: You must be a member of our GitHub repository to access the GitHub lecture notes.


Kevin Nowland

Head of Alumni-led Programs


Ghanashyam Khanal

Quantum Computing


Learn about software engineering tools used to put data science into production. Write cleaner, well documented python code.


Here you'll find the 3-part mini-course put together by Kevin Nowland for Fall 2021.

Productionization Part 1

Part 1: Intro to the terminal. The command line and modern text editing​

Productionization Part 2

Part 2: Cleaner, documented code

Productionization Part 3

Part 3: Docker, flask, and exposing data science models


Quantum Computing

Learn about the basics of quantum computing with plenty of hands on material.

Videos will be added as we progress through the mini-course. 

QC Part 1

Part 1: Introduction to quantum computing, constructing quantum circuits, and visualization of quantum simulation using qiskit

QC Part 2

Part 2: Multiqubits & Entanglement, Running on a real quantum computer, Quantum Algorithms

QC Part 3

Part 3: Quantum Machine Learning



Learn the skills not taught in the boot camp that will help you jump in and succeed from your first day as a data scientist.

These are one-off lectures on special topics relevant to working in industry. Videos will also be added to the following talks once they are recorded.


March 8th 2022 - 12pm ET
Lorenzo Atriano
Sr Data Solutions Manager,

Agile Software Development

An introduction to agile software development practices that will focus on the roles of the people that data scientists and other software engineers commonly collaborate with. Learn about what exactly those product owners and business analysts are doing and how they help developers be more productive.


April 12th 2022 - 12pm ET
Benjamin Campbell
Sr Data Scientist,

Cloud-based Machine Learning 

A guide to making the transition from working locally on your own laptop to working with teammates using a cloud-based machine learning platform such as Amazon SageMaker. Come learn about the pros (and cons) of working in the cloud.

Cloud based ML
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