Data, AI & Machine Learning
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45 lessons
Math, statistics, ML, data engineering, intelligent data platforms, decision science and MLOps.
Market Basis: Amazon/Microsoft data, BI, data science, ML and data-platform roles
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Representative Roles
Enrichment
- Mathematics, probability & statistical reasoning — BASIC: Vectors + Linear Algebra — 3Blue1Brown
- Mathematics, probability & statistical reasoning — INTERMEDIATE: Bayes Theorem — StatQuest
- Mathematics, probability & statistical reasoning — ADVANCED: Bias, Variance + Regularization — Stanford CS229
- SQL analytics & query engineering — BASIC: SQL Full Database Course — freeCodeCamp
- SQL analytics & query engineering — INTERMEDIATE: SQL Beginner -> Advanced — Alex The Analyst
- SQL analytics & query engineering — ADVANCED: SQL for Data Engineering — Luke Barousse
- Data modeling, warehousing & lakehouse architecture — BASIC: Lakehouse Architecture + Security — Databricks
- Data modeling, warehousing & lakehouse architecture — INTERMEDIATE: Data Modeling 101 for Lakehouse — Databricks
- Data modeling, warehousing & lakehouse architecture — ADVANCED: What's Wrong with Medallion? — Databricks
- Pipelines, orchestration, Spark & streaming — BASIC: Apache Kafka Fundamentals — Confluent
- Pipelines, orchestration, Spark & streaming — INTERMEDIATE: GCP + Kafka + PySpark + Airflow — End-to-End Build
- Pipelines, orchestration, Spark & streaming — ADVANCED: Airflow + Databricks + Kubernetes — Platform Build
- Machine learning, features & model evaluation — BASIC: Gentle Intro to Machine Learning — StatQuest
- Machine learning, features & model evaluation — INTERMEDIATE: Cross Validation — StatQuest
- Machine learning, features & model evaluation — ADVANCED: Evaluation Metrics — Stanford CS229
- Deep learning, computer vision & NLP — BASIC: But What Is a Neural Network? — 3Blue1Brown
- Deep learning, computer vision & NLP — INTERMEDIATE: Introduction to Deep Learning 2026 — MIT 6.S191
- Deep learning, computer vision & NLP — ADVANCED: Build GPT from Scratch — Andrej Karpathy
- Experimentation, forecasting, causal & operational analytics — BASIC: Hypothesis Testing — StatQuest
- Experimentation, forecasting, causal & operational analytics — INTERMEDIATE: Online Controlled Experiments — Ron Kohavi
- Experimentation, forecasting, causal & operational analytics — ADVANCED: Introduction to Causal Inference — Brady Neal
- Production ML, governance & intelligent data platforms — BASIC: MLOps Explained — IBM Technology
- Production ML, governance & intelligent data platforms — INTERMEDIATE: Data Governance Explained — IBM Technology
- Production ML, governance & intelligent data platforms — ADVANCED: Microsoft Fabric Deep Overview — John Savill