LBS College of Engineering · Faculty Development Programme

Full Stack
& AI

Hi, I’m Gopi.

Founding Engineer at Ally for Mental Health Foundation.

Hand-drawn portrait of Gopikrishnan S

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Contents

Five chapters. Open a chapter to see its teaching route.

01 Introduction to Generative AI

Generative AI and foundation models
Self-supervised learning and model output
Evolution from task-specific AI
Generative vs discriminative models
Multimodality, impact, risks, and human control
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02 Large Language Models

Language models, tokens, embeddings, and context
Attention: query, key, value, and multi-head attention
Transformer encoder, decoder, masks, and inference
BERT, GPT, and encoder–decoder models
Capabilities and limitations
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03 Prompt Engineering Essentials

Prompt contracts and instruction/data separation
Context position and prompt consolidation
Target-language prompting
Zero-shot, few-shot, chain-of-thought, and ReAct
Structured outputs, experiments, and failure controls
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04 Hands-on with LLMs

Hosted provider and open-model families
Efficiency, balanced, flagship, and reasoning tiers
Model comparison and evaluation harnesses
Hugging Face, Ollama, and vLLM
Request parameters and model-selection workflow
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05 Integrating LLMs in Applications

Thin vertical slice and integration boundary
API/SDK adapters and application contracts
Retrieval, tool use, and structured output
Production pipelines, reliability, safety, and observability
Practical integration checklist
Open Chapter 05 →