Online Courses

List of online courses I’ve completed, including notes and projects.

• TODO: A practical guide to Kubernetes
• 2023 AWS Certified Solutions Architect
• 2023 Data Engineer Nanodegree by Udacity
• 2023 Udemy NoCode courses (bubble, zapier, figma, etc.)
• 2023 Grokking Modern System Design Interview (no notes)
• 2022 Cloud DevOps Engineer Nanodegree by Udacity
• 2022 Machine Learning Engineering for Production by Coursera
• 2022 AWS Cloud Technical Essentials by Coursera
• 2022 Spark and Python for Big Data with PySpark by Udemy
• 2022 SQL for Data Science by Coursera
• 2021 Full Stack Deep Learning by UC Berkley
• 2021 How to win a data science competition by Coursera
• 2020 Robotics: Perception by Coursera
• 2019 Self-Driving Car Engineer Nanodegree by Udacity

Code examples

Examples of publicly available code I’ve written.

• 2024 Elliptio: Saving files to a data lake with reproducibility and metadata
• 2024 Cachephant: Caching function output to disk
• 2024 Syncing local code to Kaggle (enefit energy prediction challenge)
• 2024 Beardataclass: Converting between Dataclasses and Dataframes
• 2022 Deploying an ML model with a REST API to AWS Lambda
• 2022 Identifiying named entities including entity-links using Huggingface
• 2022 Deploying a FastAPI or Streamlit App to Heroku
• 2021 Clustering job postings using BERT embeddings
• 2021 Developing inside (Kaggle) docker containers (ventilator pressure prediction challenge)
• 2021 Predicting future sales (Kaggle)
• 2020 Understanding Bayes, Kalman and particle filter
• 2020 Estimating a 3D world from 2D RGB images using SLAM and OpenCV
• 2020 Understanding the optimization algorithm ADAM
• 2020 Transferring an image style according to Gatys et al. using PyTorch
• 2019 Detecting cars and their 3D pose in 2D images (Kaggle)

Books

Books I’ve read or at least skimmed through.

Algorithms and Data structures

• Elements of Programming Interviews in Python by Aziz
• Cracking the Coding Interview by McDowell
• Data Structures and Algorithms by Bullinaria
• Algorithms: Explained and Animated by Ishida

Python

• Fluent Python: Clear, Concise, and Effective Programming by Ramalho
• Effective Python: 59 Specific Ways to Write Better Python by Slatkin

C++

• Effective Modern C++ by Meyers
• Effective C++ by Meyers
• C++ Primer 5th edition by Lippman

Computer Vision

• Multi View Geometry by Hartley
• Introduction to Autonomous Mobile Robots by Siegwart
• Computer Vision: Algorithms and Applications by Szeliski

Embedded Systems

• Embedded System Design - A Unified Hardware/Software Introduction by Vahid
• Digital Design by Vahid

Cloud

• AWS for Solutions Architects

Machine Learning

• Practical Statistics for Data Scientists
• Deep Learning by Ian Goodfellow
• Deep Learning with Python by Chollet
• Pattern Recognition and Machine Learning by Bishop

Design Patterns

• Design Patterns by Shvets
• Design Patterns - Elements of Reusable Object-Oriented Software by Gamma

Clean and Pragmatic Code

• TODO: The Passionate Programmer by Fowler
• TODO: The Clean Coder by Martin
• Software Engineering at Google by Winters
• Pragmatic Programmer by Thomas
• Programming Pearls by Bentley
• Code Complete by McConnel
• Clean Code by Martin

DevOps

• The DevOps Handbook by Kim
• Accelerate: The Science of Lean Software and DevOps by Forsgren

Architecture

• TODO: Books by Joel Spolsky
• Designing Data Intensive Applications by Kleppmann
• Clean Architecture by Martin
• Composing Software by Elliott
• Object-Oriented Analysis & Design by McLaughlin

Refactoring and Testing

• Unit Testing: Principles, Practices, and Patterns by Khorikov
• Art of Unit Testing by Osherove (dislike this one)
• Working Effectively with Legacy Code by Feathers

Web Development

• Building Microservices by Sam Newman
• Flask Web Develoment by Grinberg

Product Development

• TODO: Books by 37signals
• Shape Up by Singer
• The Lean Startup