Generative AI Fundamentals
Develop the skills to prototype and evaluate a grounded text assistant through a learning path centred on Generative AI Fundamentals. Explore concepts, guided practice and an applied project.
Build practical Generative AI Fundamentals skills.
Skills and knowledge developed in this course.
- Generative models
- Application interaction
- Grounding workflows
- Evaluation and safety
- Applied project: Prototype and evaluate a grounded text assistant
- Generative AI Fundamentals — validation and review
About this course
This course develops practical capability in Generative AI Fundamentals. Its course-specific content covers Generative models, Application interaction, Grounding workflows, Evaluation and safety, followed by an applied project focused on prototype and evaluate a grounded text assistant. The lessons include concrete configuration, design, testing or operational decisions appropriate to the subject.
Who this is for
Learners starting in artificial intelligence & generative ai and professionals who want an organized foundation before more advanced work.
Before you start
Basic computer literacy and comfort using the relevant operating system. No prior production experience is assumed; any lab accounts or software are confirmed before training.
Prototype and evaluate a grounded text assistant
Deliver prototype and evaluate a grounded text assistant. Use the module outcomes to state requirements, demonstrate a working result, test an expected failure or boundary case, and document assumptions and follow-up work.
Course content
Course-specific syllabus and practical exercises. Lab release, access arrangements and final delivery scope are confirmed before enrolment.
01Generative models
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- Tokens, embeddings and transformers
- Training versus inference and sampling
Practical exerciseApply generative models to the prototype and evaluate a grounded text assistant and capture the validation evidence.
02Application interaction
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- Prompts and structured output
- Context limits and output variability
Practical exerciseApply application interaction to the prototype and evaluate a grounded text assistant and capture the validation evidence.
03Grounding workflows
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- Retrieval and cited context
- Tool use and workflow boundaries
Practical exerciseApply grounding workflows to the prototype and evaluate a grounded text assistant and capture the validation evidence.
04Evaluation and safety
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- Quality rubrics and hallucination checks
- Privacy, injection risks and human review
Practical exerciseApply evaluation and safety to the prototype and evaluate a grounded text assistant and capture the validation evidence.
05Applied project: Prototype and evaluate a grounded text assistant
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- Define inputs, assumptions and acceptance criteria for: Prototype and evaluate a grounded text assistant.
- Implement the project using generative models, application interaction, grounding workflows, evaluation and safety.
Practical exercisePrototype and evaluate a grounded text assistant.
06Generative AI Fundamentals — validation and review
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- Demonstrate the completed project against its acceptance criteria.
- Exercise an invalid-input or failure scenario and document the observed result.
Practical exercisepresent the project evidence, limitations and a repeatable handover.
Technical references
These primary vendor, project or standards sources inform this independent IT Purview outline. Reference pages checked 25 October 2026; current provider documentation and exam objectives take precedence when versions change.
From understanding to application.
Progress by learning milestone. The schedule is agreed around your starting level and learning goals.
- 01Learning milestone 1 In progress
Set the context
Generative models · Application interaction
Establish the Generative AI Fundamentals scope, baseline concepts and operating assumptions. - 02Learning milestone 2 In progress
Build the working skills
Grounding workflows · Evaluation and safety
Apply the core Generative AI Fundamentals techniques in the course lab and record the result. - 03Learning milestone 3 In progress
Validate and handle exceptions
Check expected behavior, investigate a failure case and capture evidence for prototype and evaluate a grounded text assistant. - 04Learning milestone 4 In progress
Deliver the applied project
Complete prototype and evaluate a grounded text assistant, explain key decisions and identify a practical next step.
Career outlook after this learning path
Typical roles this roadmap can support, with broad salary ranges by relevant work experience.
| Role | 0–3 years | 3–7 years | 7–12+ years |
|---|---|---|---|
| AI / ML Engineer | ₹10–17 LPA | ₹20–35 LPA | ₹38–62 LPA |
Ranges are indicative India-market compensation estimates in ₹ lakh per annum, not a salary promise. They reflect broad market guides and vary by location, employer, skills and role scope; the experience bands refer to relevant work experience, not time since training. Completing this course does not guarantee employment, a role, compensation or career progression. View market reference ↗