What Will You Learn?

• AI & ML Fundamentals: What Actually Happens: Understand the technology without the hype. How computers learn from data, the difference between AI, ML, and deep learning, and the history of breakthroughs that led to today's generative AI — the context that makes everything else make sense.
• Large Language Models: Inside ChatGPT & Gemini: Understand what makes GPT-4, Gemini, Claude, and Llama different from traditional software. Transformers, attention mechanisms, token prediction, and the training process — explained clearly for people who don't have PhDs.
• Prompt Engineering: Professional-Level Results: The highest-leverage skill in AI. Zero-shot, few-shot, chain-of-thought, and ReAct prompting techniques — learning to communicate with AI systems to consistently produce professional-quality outputs.
• LangChain: Building AI Applications: The framework that connects AI to the real world. Build chains, agents, and tools that automate complex multi-step AI workflows. Use LangSmith to debug and monitor AI applications — moving from AI user to AI builder.
• Vector Databases & RAG Architecture: Build AI that knows your data. Embeddings, vector search, Retrieval-Augmented Generation — the architecture behind AI assistants that answer questions about documents, databases, and private knowledge bases.
• Python for AI Workflows: Write the code that connects AI systems. API calls, data processing, automation scripting, and integration code — taught at the level this course requires, not the full software engineering curriculum.
• OpenAI API: GPT-4 & Function Calling: Build with the world's most powerful language model. API authentication, prompt construction, function calling for structured outputs, streaming responses, and cost management — production-ready OpenAI integration.
• Image Generation: Stable Diffusion & DALL-E 3: Explore the visual frontier of AI. Understand diffusion models, use Stable Diffusion for customisable image generation, and integrate DALL-E 3 for AI-generated visuals in applications — opening creative and commercial possibilities.
• Hugging Face: Open-Source AI Models: The world's largest AI model repository. Use open-source models for text, image, audio, and video tasks through the Inference API — accessing powerful AI capabilities without the cost of commercial APIs.
• AI App Deployment: Streamlit & FastAPI: Ship your AI applications. Build interactive UIs with Streamlit, create robust AI APIs with FastAPI, and deploy them for the world to use — the deployment skills that turn experiments into products.
• AI Ethics, Safety & Responsible Use: Use AI responsibly. Understand bias in AI systems, hallucination problems, data privacy implications, GDPR compliance for AI applications, and frameworks for responsible AI deployment — the professional standard.
• Capstone: Build & Deploy a GenAI Application: Create a complete generative AI application — a domain-specific chatbot, document intelligence system, or AI content platform — deployed and publicly accessible. A portfolio piece that demonstrates genuine AI development capability.