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Work through scenarios with business requirements, technical constraints and measurable outcomes relevant to Generative AI Engineer.
AI ENGINEERING AND ENTERPRISE ADOPTION
Generative AI Engineer
Build the generative-AI products users touch: grounded answers with citations, controlled text and image generation, safety and provenance controls, measured hallucination rates and defensible unit economics.
12 weeksLive instruction & enterprise practiceEvidence you can explain
BUILD YOUR NEXT CHAPTER
Your skills can evolve with the work.
Rapid progress in AI is expanding what teams can build. Enterprise value depends on people who can evaluate behavior, connect models to real workflows and manage security, reliability and cost. Practice the engineering decisions that turn a promising idea into a tested solution you can explain.
You bring your ambition and experience. Neriya gives you a structured path to turn learning into practical work: guided lessons, enterprise scenarios, purposeful feedback and opportunities to explain your decisions. Progress from understanding the concepts to applying them, investigating problems and presenting a solution with confidence.
Prepare to walk someone through your work: the business problem, your approach, the tools you used, the tests you ran and the outcome you achieved. Your portfolio becomes a record of assessed training work that you can use in interviews and professional conversations.
WHAT YOU WILL EXPLORE
A focused overview of your learning.
- Study and guided implementation
- Lab validation and portfolio evidence
- Learning unit 1: Python and reproducible engineering — design
- Learning unit 2: Python and reproducible engineering — applied lab
- Learning unit 3: LLM application foundations — design
- Learning unit 4: LLM application foundations — applied lab
This overview introduces the scope. Your complete lesson sequence, exercises, project briefs and execution guides are available inside the enrolled course.
QUESTIONS THAT MAKE THE LEARNING CONCRETE
From generated answers to inspected evidence.
When comparing this specialization, examine how source grounding, evaluation and application behavior fit together. A useful discussion can start with a synthetic knowledge assistant: where did an answer come from, when should it decline to answer, and how would you investigate an unsupported statement?
Bring questions about Python and API prerequisites, retrieval evaluation, permitted datasets, project review and practice-system costs. Our public RAG checklist illustrates an evidence standard; the confirmed enrolled syllabus defines your assignments.
PRACTICE WITH PURPOSE
Build enterprise skills. Make your progress visible.
Investigate
Practice troubleshooting, test your assumptions and document why your chosen approach works.
Prove
Demonstrate a working solution, test failure cases and defend evaluation and design choices. Present your contribution and answer practical reviewer questions.
Learning is designed to develop capability through practice and feedback. Course completion reflects assessed training skills; professional experience and employer requirements also shape your next career opportunity.
Your enrolled learning experience
Create and verify your learner account, complete payment, then open the paid course from My Learner Library. Your private course brings together detailed curricula, enterprise projects, live Google Classroom and Meet access, assignments, instructor feedback and published session recordings.
Classroom invitations, cohort schedules and recordings appear when assigned or published. Confirm instructor-led class dates and any required practice-system licenses with enrollment support before payment.
Open my enrolled courseMy Learner LibraryINVEST IN YOUR PRACTICAL SKILLS
Tuition & enrollment
$3,900 USDTotal course tuition · 12 weeks. Independent certification exams and separately quoted third-party licenses are excluded. Review the cohort schedule and payment terms before enrolling.
PRACTICAL GUIDANCE FROM NERIYA
Make an informed learning choice.
Use our public guides to examine prerequisites, project evidence and the support you need. Confirm the specific syllabus and cohort arrangements before enrolling.