Gen AI Course
Master the fundamentals of Generative AI with a focus on financial applications
Vivek Dhandapani
Researcher and practitioner specializing in Generative AI and Multimodal AI systems, with a focus on real-world applications in financial services and enterprise environments.
Connect on LinkedInNLP Foundations
From text to understanding - the bridge to modern AI
- Introduction to NLP & its evolution
- Text preprocessing, tokenization, and feature engineering
- Text representation: Bag of Words, TF-IDF, Word embeddings
- +5 more topics →
Foundation Models
Understanding the "engine" behind Gen AI
- What are Foundation Models (Transformers, attention mechanism - intuition only)
- Pre-training vs Fine-tuning vs RLHF
- Model landscape: GPT, Claude, Gemini, Llama, Mistral
- +4 more topics →
Prompt Engineering
The skill layer - getting reliable outputs
- Anatomy of a prompt (role, context, task, format, constraints)
- Techniques: Zero-shot, Few-shot, Chain-of-thought
- System prompts & guardrails
- +3 more topics →
Embeddings & Vector Stores
Building knowledge systems with your data
- What are embeddings (intuition + visualization)
- Text → Vector → Similarity search
- Vector databases: Pinecone, Weaviate, Chroma, FAISS
- +4 more topics →
AI Agents
Autonomous AI that takes action
- What are AI agents (perception → reasoning → action)
- Agent architectures: ReAct, Tool-use, Multi-agent
- Function calling & tool integration
- +4 more topics →
Governance, Ethics & Regulation
Deploying responsibly in regulated environments
- AI Transparency frameworks (IFATS!)
- Explainability requirements for financial AI
- Model risk management (SR 11-7 equivalent for AI)
- +3 more topics →
AI & GenAI Security
Securing LLM systems from attack to governance
- OWASP Top 10 for LLM Applications (2025) — all 10 risks with bank examples
- Prompt injection deep dive: attack techniques and 8-layer defenses
- Adversarial ML & MITRE ATLAS: evasion, poisoning, model extraction
- +5 more topics →
AI Frontier
State of the art — updated continuously
- Multimodal AI — the new default across text, vision, audio, video
- On-device AI: privacy-first architecture for sensitive financial data
- AI in production: evals, model routing, observability, cost accountability
- +4 more topics →
AI Observability, Evaluation & Tracing
Measure, monitor, and improve AI in production
- The three pillars: traces, metrics, and logs for AI systems
- Evaluation (evals): types, LLM-as-judge, golden sets, regression testing
- LangSmith: tracing, datasets, eval runs, annotation queues
- +5 more topics →
Ready to Transform Your AI Skills?
Dive deep into the world of Generative AI and discover how to leverage cutting-edge technologies in the financial sector.
Start Learning