Building Generative AI Applications with Python
Building Generative AI Applications with Python
This course immerses students in the world of generative artificial intelligence (GenAI) and covers high-level browser-based tools, emphasizing the Python code behind them.
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What you can learn.
right one for a given constraint set
techniques
LangGraph
portfolio
bottlenecks, and agent loop failures
About This Course
This 10-week hands-on course takes you from generative AI fundamentals to production-grade applications. You will build real systems using the same tools and frameworks used in industry: PyTorch, Hugging Face, LangChain, and modern LLM APIs, and leave with a deployable capstone project you can showcase on GitHub.
Topics span diffusion models, large language models (LLMs), multimodal AI, prompt engineering, agentic AI systems, and fine-tuning with LoRA/QLoRA. Each week pairs conceptual depth with a hands-on lab. The course is designed for working professionals who want immediately applicable skills in the fastest-moving area of technology.
A note on this course's philosophy: information about generative AI is freely available online. This course
teaches judgment, when to use which tool, what breaks in production, and how to make defensible
architectural decisions. Every week includes failure case analysis, role-specific scenarios, and graded written
reasoning components that cannot be answered by running code.