The career field notes
Learn what matters.Build proof that counts.
Clear, practical guides for choosing your path, learning the right skills and turning your work into evidence employers can trust.
Practical reading, no filler
Start with the question in front of you.
Each guide ends with a concrete next step, so reading becomes a decision, a practice plan or a better piece of work.
01
Career direction
10 min readData analyst vs data scientist: choose by the work, not the title
Compare the questions, daily work, core tools and entry paths before deciding which role deserves your learning time.
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02
Skill playbook
11 min readA practical SQL roadmap for becoming an effective data analyst
Learn SQL in the order real analysis demands it: from reliable queries to reusable logic and decision-ready outputs.
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03
Portfolio playbook
9 min readBuild a data portfolio that recruiters can understand in 90 seconds
Turn project work into clear evidence by showing the problem, your decisions, the output and what changed because of it.
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04
Learning roadmap
13 min readThe honest AI engineer roadmap: learn systems, not just prompts
Build from Python and software foundations to retrieval, agents, evaluation and production reliability in the right order.
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05
Project playbook
10 min readYour first machine learning project should be simple and complete
Choose a clear decision, build a baseline, evaluate honestly and finish with a project you can explain without hiding behind jargon.
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06
Interview prep
8 min readHow to explain a data project in an interview without reciting it
Use a decision-first walkthrough that makes your contribution, judgement and learning easy for an interviewer to assess.
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Reading gives direction. Practice builds proof.