What you'll learn:
- Understand Generative AI & LLMs – Gain a solid foundation of how Generative AI and Large Language Models work, including their core concepts, architectures,
- Apply AI in Real-World Scenarios – Learn how to use AI for content generation, code assistance, automation, and industry-specific case studies.
- Hands-On Practical Skills – Build and experiment with models through weekly labs, covering tools, frameworks, and fine-tuning techniques.
- Evaluate Ethics & Future Opportunities – Explore AI ethics, governance, and responsible innovation, while identifying emerging career and business opportunities
"This course contains the use of artificial intelligence in creating scripts, visuals, audio, and supporting content"
This 8-week course is a complete foundation in Generative AI and Large Language Models (LLMs), designed to help you build both conceptual understanding and practical skills. The program is structured to gradually move from the basics of generative models to advanced applications, customization, safety, and a capstone project that showcases your abilities.
The course begins with an introduction to Generative AI, where you will explore tokenization, attention mechanisms, and the transformer architecture that forms the backbone of modern LLMs. You will learn how text generation works, experiment with prompt design, and analyze the impact of model parameters like temperature and top-p on creativity and accuracy.
Building on this, the course dives into the foundations of large language models, exploring embeddings, perplexity, and context windows. You will also study core generative models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and diffusion models, gaining an intuitive understanding of how these models generate text, images, and structured data.
The practical modules allow you to apply Generative AI in practice, including summarization, creative writing, code generation, data augmentation, and image synthesis. You will use modern tools and frameworks like Hugging Face Transformers, LangChain, vector databases (FAISS, Pinecone), and deployment frameworks such as FastAPI and Hugging Face Spaces.
You will also learn fine-tuning techniques, including prompt engineering, LoRA (Low-Rank Adaptation), and domain-specific customization, so you can adapt LLMs to specialized tasks. In addition, a dedicated module on ethics, safety, and governance helps you understand and mitigate bias, hallucinations, and responsible AI risks.
The course concludes with a capstone project, where you will design, implement, and present a real-world Generative AI application, integrating the skills and frameworks covered throughout the program.
By the end, you will be equipped with hands-on experience, a portfolio-ready project, and the confidence to apply Generative AI and LLMs in business, research, and innovation.
