Practical guides for moving into a new career, written for people who already have one. Every guide is free to read; no account needed.
Your experience does not disappear when you change careers. Start by listing the problems you solve today, not your job title, then map each one to the skills your target role asks for.
Read the guide: How to Change Careers Without Starting From ZeroEmployers ask for experience because it reduces risk. Realistic projects built on public data, reviewed by someone in the field and written up clearly, reduce the same risk.
Read the guide: How to Build Experience When You Have No ExperienceA certificate proves completion. Hiring managers want to know how you approach an unfamiliar problem. Pair every course with a piece of work you can talk through.
Read the guide: Why Certificates Alone Don't Guarantee a Career ChangeThree strong projects beat ten tutorials. Each should state the problem, your approach, what you would do differently, and evidence that someone checked it.
Read the guide: How to Build a Career PortfolioClear reasons for the move, current skills, evidence of finishing things, and domain knowledge they would otherwise have to teach.
Read the guide: What Employers Actually Look For When Hiring Career ChangersAI engineers build products on existing models; ML engineers train and serve their own. The first is the faster route for most career changers with some coding.
Read the guide: AI Engineer or Machine Learning Engineer: Which Suits You?Alert triage, learning the estate, writing clear tickets and asking good questions. Technical depth grows from there.
Read the guide: What a SOC Analyst Actually Does in the First 90 DaysLead with the problem you want to work on, connect it to what you already did well, then show the work that proves you can do the new job.
Read the guide: Explaining Your Career Change in an InterviewBring specific work and specific questions. The most useful feedback comes from something concrete to react to.
Read the guide: Getting the Most From a MentorBuild, evaluate and ship systems that use large language models and machine learning — from prompt design and retrieval to agents and deployment.
Read the pathway guideTurn raw data into decisions: SQL, analysis, statistics, visualisation, pipelines and the judgement to interpret results honestly.
Read the pathway guideProtect organisations and their AI systems: security operations, incident response, vulnerability management, AI security and governance.
Read the pathway guideDesign, build, test and ship software — full-stack or specialised — working effectively with AI coding tools, APIs and sound system design.
Read the pathway guidePlan, run and measure marketing that drives revenue: paid search and social, analytics, content and the AI tools now built into every marketing team.
Read the pathway guideDeliver change that works: plan and run projects, analyse how a business operates, and turn problems into requirements, including for AI and data projects.
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