Technology track
Generative AI & LLM Apps internship
Build useful products on top of large language models. Courses from SkillTank Academy, live tasks reviewed by KaizenSpark Tech mentors.
Prerequisites
- Python basics
- Curiosity about AI tools
Tools you’ll use
OpenAI APILangChainVector databasesPython
Roles it prepares you for
- Generative AI intern
- LLM application developer
- AI product engineer
Syllabus
The Generative AI & LLM Apps track, week by week.
Shown for the 3-month internship. The 1-month internship covers the first phase in depth; the 6-month internship extends each phase with a specialisation course and module ownership.
Weeks 1–2 · Foundations
- How LLMs work and their limits
- Prompt engineering patterns
- Calling LLM APIs
Weeks 3–6 · Build
- Embeddings and vector search
- Retrieval-augmented generation
- Structured outputs
Weeks 7–10 · Own
- Agents and tool use
- Evaluation sets and guardrails
- Cost and latency
Weeks 11–12 · Graduate
- Shipping an AI feature
- Monitoring answers
- Demo and write-up
Deliverables
What you’ll hand in.
Every deliverable is reviewed and rated on the 1–5 quality rubric, and approved work is added to your record.
- A RAG assistant grounded in real documents
- An evaluation set with results
- A short technical write-up
Competencies assessed
- Prompt engineering
- Retrieval-augmented generation (RAG)
- LLM APIs and agents
- Evaluating AI output
Sample project
Build a document-grounded assistant with RAG and an evaluation set.
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Apply for the Generative AI & LLM Apps track.
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