I will add bullet points in descending date order of some things I am doing (besides applying for jobs) in 2025
Updated: 5th March 2025
Bootcamps
- (ongoing) Jan 27th - Mar 16th - I am doing Maria Vechtomova and Başak Eskili’s End-to-end MLOps with Databricks boot camp (got as a Christmas present 😆)
- (finished) Jan 6th - Mar 2nd - I am doing Zach Wilson’s Data Engineering boot camp (won my spot by being an active member and helper in Zach’s free DE boot camp)
Other studies
- (ongoing) reading Alex Xu’s System Design Interview (Vol. 1)
- (ongoing) covering the study materials for Certified Kubernetes Applications Developer (CKAD)
- (ongoing) reading through ByteByteGo’s ML System Design book
- (ongoing) leetcode’s DSA course + blind 75/150 from neetcode
- (ongoing) covering Stanford’s MLSys seminar series
- (Mar) covering Stanford’s CS149 - Parallel Computing
- (Feb) read ML for Tabular data by Mark Ryan and Luca Massaron
- (Feb) covered MIT’s Intro to Algorithms Spring 2020
- (Feb) Finished an example project for a MLOps 101 mini-course I will teach to my university club
- (Feb) Finished a full-stack voice-to-voice app that lets users interact with their finances through an AI agent
- (Feb) Finished my capstone for Zach Wilson’s bootcamp - Using voice data to extract insight from team communication
- (Jan) read Clean Coder, The: A Code of Conduct for Professional Programmers by Robert C. Martin
- (Jan) read Refactoring Guru’s design patterns
- (Jan) read Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin
- (Jan) reading Chip Huyen’s ML Interviews book
- (Jan) finished all SQL questions in Data Lemur (also ML and Stats)
- (Jan) re-watched CS50’s lectures on Data Structures, Algorithms, C
- (Jan) covered a practical Kubernetes course (really good!)
- found podcasts episodes with MarvelousMLOps’ Maria and Başak and read through a lot of MarvelousMLops’ posts
- (Jan) did a conceptual, logical (+physical in Neo4j) graph data model for EU AI Act data
- (Jan) read Machine Learning Engineering with Python - Second Edition
- (Jan) read through Software Engineering for Data Scientists