LlamaIndex
Develop the skills to build a document retrieval workflow with citations through a learning path centred on LlamaIndex. Explore concepts, guided practice and an applied project.
Build practical LlamaIndex skills.
Skills and knowledge developed in this course.
- Data connectors
- Indexes and queries
- Retrieval refinement
- Workflow evaluation
- Applied project: Build a document retrieval workflow with citations
- LlamaIndex — validation and review
About this course
This course develops practical capability in LlamaIndex. Its course-specific content covers Data connectors, Indexes and queries, Retrieval refinement, Workflow evaluation, followed by an applied project focused on build a document retrieval workflow with citations. The lessons include concrete configuration, design, testing or operational decisions appropriate to the subject.
Who this is for
Administrators, developers and practitioners who work with LlamaIndex or plan to take on responsibilities in this area.
Before you start
Basic computer literacy and a foundational understanding of artificial intelligence & generative ai. Prior experience with the named product helps with the practical exercises.
Build a document retrieval workflow with citations
Deliver build a document retrieval workflow with citations. 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.
01Data connectors
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- Documents, nodes and ingestion
- Metadata and incremental indexing
Practical exerciseApply data connectors to the build a document retrieval workflow with citations and capture the validation evidence.
02Indexes and queries
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- Vector stores and retrievers
- Query engines and response synthesis
Practical exerciseApply indexes and queries to the build a document retrieval workflow with citations and capture the validation evidence.
03Retrieval refinement
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- Filters, reranking and query transformation
- Citation and source-node inspection
Practical exerciseApply retrieval refinement to the build a document retrieval workflow with citations and capture the validation evidence.
04Workflow evaluation
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- Retrieval datasets and answer checks
- Access-aware queries and ingestion recovery
Practical exerciseApply workflow evaluation to the build a document retrieval workflow with citations and capture the validation evidence.
05Applied project: Build a document retrieval workflow with citations
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- Define inputs, assumptions and acceptance criteria for: Build a document retrieval workflow with citations.
- Implement the project using data connectors, indexes and queries, retrieval refinement, workflow evaluation.
Practical exerciseBuild a document retrieval workflow with citations.
06LlamaIndex — 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
Data connectors · Indexes and queries
Establish the LlamaIndex scope, baseline concepts and operating assumptions. - 02Learning milestone 2 In progress
Build the working skills
Retrieval refinement · Workflow evaluation
Apply the core LlamaIndex 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 build a document retrieval workflow with citations. - 04Learning milestone 4 In progress
Deliver the applied project
Complete build a document retrieval workflow with citations, 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 ↗