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Loading image: For College Engineers - Verlin Labs AI training program…10-Day Program Structure
A 10-day intensive program for engineering students who want deep intuition for AI systems, hands-on API projects, and portfolio-ready work for internships and interviews.
10 days · 3 phases
Phase 1: AI Systems Deep Dive
1
LLMs, Tokens & Transformers
Build strong mental models for how large language models work - tokens, attention, and prediction - without getting lost in math.
Topics
- •Tokenization and embeddings
- •Transformer architecture intuition
- •Training vs inference
- •Model capabilities and limits
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2
APIs, Embeddings & Vector Basics
Understand the building blocks of modern AI applications - APIs, vector stores, and how data flows through AI systems.
Topics
- •REST APIs for LLM services
- •Embeddings explained practically
- •Vector similarity search
- •Cost and latency considerations
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3
Prompt Engineering & Tool Use
Master structured prompting, chain-of-thought, and function calling - the skills that separate hobbyists from engineers.
Topics
- •System prompts and few-shot learning
- •Structured outputs (JSON mode)
- •Function calling and tool use
- •Evaluation and iteration
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Phase 2: Building with AI
4
RAG Architecture
Design and implement Retrieval-Augmented Generation pipelines - the most common pattern in production AI apps.
Topics
- •Chunking and indexing strategies
- •Retrieval quality and reranking
- •Context window management
- •RAG evaluation metrics
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5
Fine-Tuning vs Prompting
Learn when to prompt, when to fine-tune, and when to use both - with clear decision frameworks.
Topics
- •Fine-tuning use cases
- •LoRA and parameter-efficient methods
- •Data preparation for fine-tuning
- •Build vs buy decisions
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6
Building with LLM APIs
Hands-on session building a real application using LLM APIs - from design to working prototype.
Topics
- •Project architecture
- •Streaming responses
- •Error handling and retries
- •Rate limits and caching
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7
Agents & Workflows
Explore multi-step AI agents, workflow orchestration, and when agentic patterns add value vs complexity.
Topics
- •Agent loops and planning
- •Tool orchestration patterns
- •LangChain / LangGraph concepts
- •Debugging agent failures
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Phase 3: Ship & Interview Prep
8
System Design for AI Apps
Apply system design mental models to AI-powered applications - scalability, reliability, and cost at scale.
Topics
- •Architecture patterns for AI apps
- •Caching and batching strategies
- •Monitoring and observability
- •Common interview system design questions
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9
Portfolio Project Sprint
Dedicated build day to polish your portfolio project with mentor feedback and code review.
Topics
- •README and documentation
- •Demo video creation
- •GitHub portfolio best practices
- •Code review session
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10
Demo Day & Interview Prep
Present your project, practice technical interview questions, and get a personalized career roadmap.
Activities
- •Project demo presentation
- •Technical Q&A practice
- •Resume and LinkedIn review
- •Mock interview round
- •Certificate and next steps
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About the instructors
Learn from Aman Munjal, founder of Verlin Labs
Live instruction, curriculum design, and corporate workshops - one educator across every track.
Loading image: Professional headshot of Aman Munjal, Founder and Lead Trainer at Verlin Labs…Aman Munjal
Founder & Lead Trainer
I started Verlin Labs because I was tired of watching smart people nod along to AI explanations they did not actually follow. I have spent over a decade as a PM working on AI and fintech products, and I kept seeing the same gap: people who could use the tools but could not reason about them. Every program here is built around mental models first, so what you learn still holds up after the session ends and the tool has changed.
- Founder, Verlin Labs
- Live instructor for free sessions & full programs