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Generative AI engineering with LLMs

Design, build, evaluate and secure production applications on large language models, from prompts to retrieval and agents.

No reviews yetTaught by Walnut Jobs course team
Level
Advanced
Language
English
Duration
30 hours
Lessons
16

Last updated 22 Oct 2026

What you'll learn.

  • Explain tokens, context windows, sampling and the trade-offs between model options.
  • Write structured prompts and obtain reliable, schema-valid output with tool use.
  • Build a retrieval-augmented generation pipeline with chunking, embeddings and hybrid search.
  • Design offline and online evaluations with golden data sets and graded rubrics.
  • Mitigate prompt injection, data leakage and excessive agency using OWASP guidance.
  • Operate LLM applications with sensible cost, latency, logging and fallback controls.

How this course is taught.

Every module comes to you in four parts, so you can watch, read, discuss and check what you have learned.

  1. Quadrant I

    e-Tutorial

    Watch a short video lecture for each module, with full text notes beside it so you can review or translate at your own pace.

  2. Quadrant II

    e-Content

    Download or print the reading material for each module, with key terms, case studies and links to further resources.

  3. Quadrant III

    Discussion forum

    Ask questions and clear your doubts with other learners. The course team guides the discussion and answers questions.

  4. Quadrant IV

    Assessment

    Check your understanding with quizzes, short and long-answer practice and FAQs, then take the final test.

Curriculum.

5 modules · 16 lessons
1How large language models work3 lessons · 48 mine-Content (notes)2Assessment1
  • Note: Tokens, transformers and context windows20 min
  • Note: Choosing a model and deployment option18 min
  • Quiz: Module 1 quiz10 min
2Prompt engineering and structured output3 lessons · 54 mine-Content (notes)2Assessment1
  • Note: Structured prompting techniques20 min
  • Note: Structured output and tool use22 min
  • Quiz: Module 2 quiz12 min
3Retrieval-augmented generation4 lessons · 1 h 15 mine-Content (notes)3Assessment1
  • Note: Embeddings and vector search20 min
  • Note: Building a RAG pipeline22 min
  • Note: Improving retrieval quality18 min
  • Quiz: Module 3 quiz15 min
4Evaluation and security3 lessons · 56 mine-Content (notes)2Assessment1
  • Note: Evaluating LLM applications22 min
  • Note: Security: prompt injection and data protection22 min
  • Quiz: Module 4 quiz12 min
5Agents and production operations3 lessons · 58 mine-Content (notes)2Final test1
  • Note: Workflows and agents20 min
  • Note: Cost, latency and operations18 min
  • Final test: Final assessment20 min

Your certificate.

This is the certificate you receive when you complete the course and pass its final test.

Certificate No.

WDT-WJGAE-2026-000000

Certificate of completion

Generative AI Engineering with LLMs

This is to certify that

Learner Name

has successfully completed the course and passed its assessment, and is recognised as a

Generative AI engineering with LLMs

5 modules16 lessons30 hours of learningOnline, on Walnut LMS

DD Month YYYY

Date of issue

Noida, India

Authorised Signatory

Walnut DataTech Private Limited

Verify this certificate at walnutdatatech.com/verify-certificate with certificate number WDT-WJGAE-2026-000000. Issued on Walnut LMS.

Specimen — not a valid certificate
Generative AI engineering with LLMsView full size

What you need to receive it.

Complete every lesson and pass the final assessment with at least 70%.

Every certificate carries its own number that anyone can check on the verification page.

About this course.

Companies everywhere are moving generative AI from demos to production: support assistants grounded in policy documents, contract review, code assistants and internal search. The engineers they hire must understand how models behave, how to ground them in company data and how to prove that an application is accurate, safe and affordable.

This advanced course is provider-neutral. The patterns apply whether your organisation uses a hosted model API, a cloud platform such as Amazon Bedrock, Azure AI Foundry or Vertex AI, or open-weight models served in-house. You will build a retrieval-augmented generation (RAG) pipeline, add tool use, design evaluations and harden the system against the OWASP Top 10 risks for LLM applications.

Who this is for

  • Software and data engineers building LLM features
  • ML engineers moving from classical models to generative AI
  • Solution architects who must choose models and designs responsibly
  • Candidates applying for generative AI, LLM application or RAG engineering roles

Skills this certificate proves: Generative AI (Advanced), LLM applications (Advanced), RAG (Proficient), Prompt engineering (Advanced).

Linked to Walnut Jobs: complete this course to earn the certificate employers ask for.

Your instructor.

Walnut Jobs course teamJob-ready courses designed with hiring companies

Learner reviews.

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Questions about enrolling.

Is this course really free?

Yes. Create an account and enrol with one click. There's no payment step.

How long can I access this course?

You keep access for as long as the course is offered on Walnut LMS.

Do I get a certificate?

Yes. The certificate section above shows the certificate and sets out what you need to receive it.

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