A working path from infrastructure to data science, in 26 parts, for the SRE, VMware admin or platform engineer who already runs production systems and wants the half of data science they do not yet have. It does not restart you at zero. It maps what you already know, Linux, Git, CI/CD, monitoring, capacity planning and on call, onto data pipelines, model serving, drift monitoring and MLOps, then closes the real gaps in statistics and machine learning, and has you build a portfolio from the telemetry your own systems already produce. It leans on the Data Science Series for the deep mechanics, the AI Engineering Series for LLM practice, and the Cloud FinOps Series for GPU cost, rather than repeating them.
Complete · all 26 parts published
Phase 1 · The Map and the Mindset
- 01What a Data Scientist Actually Does, Compared to Infra, SRE and VMware Work
- 02Skills You Already Have That Transfer, and the Gaps to Close
- 03Operations Mindset vs Data Science Mindset
- 04A Realistic Transition Roadmap and Timeline
Phase 2 · The Foundation You Half-Have
- 05Python Past Scripting, From Automation to Data Code
- 06Reproducibility You Already Practice, Applied to Data Work
- 07Your Infrastructure Telemetry as a Dataset
- 08Getting Data Into Python From SQL, APIs and Monitoring
- 09NumPy and pandas for People Who Know awk and jq
Phase 3 · Closing the Real Gap
- 10Statistics an Operator Cannot Skip
- 11Probability and Distributions for Real Systems
- 12Machine Learning Fundamentals, Framed for Infra Engineers
- 13Your First Model, From Metric Threshold to Trained Classifier
- 14Model Evaluation Without Fooling Yourself
- 15Feature Engineering on Operational Data
Phase 4 · Playing to Your Strength, MLOps
- 16MLOps Is the Operations You Already Know
- 17Serving a Model, Batch and Real Time
- 18Monitoring Models in Production, Because Drift Is Observability
- 19Pipelines and CI/CD for Machine Learning
- 20Experiment Tracking, Model Registry and Versioning
Phase 5 · Practice on Infra Data
- 21Anomaly Detection on Metrics and Time Series
- 22Capacity Forecasting From Your Own Telemetry
- 23Log Analysis and Clustering at Scale
- 24Incident Prediction and AIOps, Honestly Assessed
Phase 6 · Landing the Role
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