Generative AI Training
Generative AI is the fastest-growing field in tech. This course teaches you to build production-grade AI applications: master prompt engineering, design Retrieval-Augmented Generation (RAG) systems, fine-tune open models, and ship full-stack AI products with LangChain, vector databases and modern LLM APIs.
Generative AI is the fastest-growing field in tech. This course teaches you to build production-grade AI applications: master prompt engineering, design Retrieval-Augmented Generation (RAG) systems, fine-tune open models, and ship full-stack AI products with LangChain, vector databases and modern LLM APIs.
Syllabus
- LLM Foundations & Tokenization
- Prompt Engineering Patterns
- RAG Architecture
- Vector Databases
- Fine-tuning with LoRA
- LangChain & LlamaIndex
- AI Agent Foundations
- AI App Deployment
What you will learn
- Design and ship RAG applications
- Fine-tune open-source LLMs
- Build AI agents with tool use
- Deploy AI apps to real users
Tools you will use
- OpenAI API
- Anthropic Claude
- LangChain
- Hugging Face
- Pinecone / Chroma
- Streamlit
Projects
- Document Q&A chatbot with RAG
- Custom fine-tuned support assistant
- Multi-tool AI agent
- AI-powered SaaS MVP
Career paths
- GenAI Developer
- Prompt Engineer
- AI Solutions Architect
- AI Product Engineer
Who should join
- Developers entering AI
- Product managers shipping AI features
- Tech leads & founders
Prerequisites
- Basic Python helpful (we cover from scratch)
- High-school math
- Curiosity for problem-solving
Certificate
AI specialization certificate with deployed real-world AI projects in your portfolio.
Syllabus
- LLM Foundations & Tokenization
- Prompt Engineering Patterns
- RAG Architecture
- Vector Databases
- Fine-tuning with LoRA
- LangChain & LlamaIndex
- AI Agent Foundations
- AI App Deployment
Learning outcomes
- Design and ship RAG applications
- Fine-tune open-source LLMs
- Build AI agents with tool use
- Deploy AI apps to real users
Tools
- OpenAI API
- Anthropic Claude
- LangChain
- Hugging Face
- Pinecone / Chroma
- Streamlit
Projects
- Document Q&A chatbot with RAG
- Custom fine-tuned support assistant
- Multi-tool AI agent
- AI-powered SaaS MVP
Career paths
- GenAI Developer
- Prompt Engineer
- AI Solutions Architect
- AI Product Engineer
Who should join
- Developers entering AI
- Product managers shipping AI features
- Tech leads & founders
Prerequisites
- Basic Python helpful (we cover from scratch)
- High-school math
- Curiosity for problem-solving
Frequently asked questions
Is coding required?
Basic Python is needed — we cover everything else, including the latest LLM APIs and frameworks.
What roles can I apply for after finishing?
Common target roles are: GenAI Developer; Prompt Engineer; AI Solutions Architect; AI Product Engineer. Placement support covers resume building, mock interviews and referrals.
Which tools and technologies will I actually use?
You work hands-on with OpenAI API, Anthropic Claude, LangChain, Hugging Face, Pinecone / Chroma and Streamlit throughout the course, rather than only studying them in theory.