Begin with this role orientation, then the embedded Python course. Continue through software, data, and AI application foundations before the customer-delivery modules. The roadmap teaches the technical prerequisites instead of sending beginners directly into discovery terminology.
Use a simulated support-team engagement throughout the later stages. Build a local document processor first, then an authenticated knowledge service, then a customer pilot with acceptance tests and an operational handoff. Label simulated business results clearly. Real customer data is not required to learn the process.
Everything is self-paced. Experienced engineers can use the foundation exit checks to skip what they can already demonstrate. Beginners should follow the sequence and revisit gaps before adding AI or enterprise complexity.
Exercise: create a portfolio folder for the problem brief, architecture, code, evaluation results, user feedback, and runbook. Write down your starting skills without inflating them.
Check: you know why programming and AI foundations come before integration and delivery, and which artifact will demonstrate each stage.