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A CS degree with a focus on full-stack ML engineering, 2020

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My CS Degree - Full-Stack ML Engineering (2020)

Being a machine learning software engineer with a background in Physics, I felt the lack of a CS degree had been a limiting factor in my long-term growth. To tackle it head-on, I designed this curriculum for myself with the best resources I found online, focusing on CS basics as well as full-stack development, deep learning and natural language processing.

There are general knowledge courses and project courses.

General knowledge courses are for indexing knowledge in the brain into an organized system. When facing a new problem, at least you know what relevant info to look for.

Project courses are the real learning process. Learning by doing is the only way to learn.

If you are interested in the philosophy of the creation of this curriculum, I wrote an article about it:

How I Designed My Own Full-Stack ML Engineering Degree

General knowledge courses

CS101. Computer architectures: general intro

CS102. Networking: general intro

CS103. Operating systems: general intro

CS201. Database: general intro

CS401. System Design

CS403. Design Patterns

  • Python Factory pattern and Message Queue
  • Book: Design Patterns by Gamma et al

CS405. Software Engineering Fundamentals

CS406 DevOps with Docker

CS501 Deep Learning with PyTorch by Yann LeCun & Alfredo Canziani: knowledge

CS504. Overview of Production Machine Learning and MLOps

CS505 Natural Language Understanding Stanford

CS507 Full Stack Deep Learning (Updated 2021)

CS511 MLOps with GitHub Action

CS513 Machine Learning System Design

CS514 Machine Learning Interview

Project courses

CS301. Coding Interview

  • EPI book

CS302 Python 3

CS303 Nature of Code youtube series

CS304 Weather Comparison App

  • Build API using FastAPI to get daily and hourly weather for cities
  • Frontend based on Streamlit, a Python framework for building UI for prototype projects

CS402 Full-Stack Web Development, ReactJS

CS404 AWS Services

  • Book: The Good Parts of AWS by Daniel Vassallo

CS407 iOS Development with Swift and SpriteKit

CS500 Deep Learning with FastAI & Pytorch: projects

CS502 NLP: projects

CS512 Applied ML in Production by MadeWithML

  • Quote the course description: "This course isn't just about ML. In fact, it's mostly about clean software engineering! We'll cover important concepts like versioning, testing, logging, etc. that really makes this a production-grade product."
  • course page
  • MadeWithML youtube channel

CS602 Open Source Contributions of Your Choosing