AI Application Development with Python: GUI, LLMs & Agents

About this course

Build real-world AI applications with Python — from graphical and voice interfaces to LLMs, RAG, AI agents, multimodal AI, automation, and deployment.

This comprehensive course takes you on a practical journey from Python foundations to building and deploying modern AI applications. Instead of focusing only on notebooks and theory, you will learn how to turn Python code into usable AI applications with professional interfaces, intelligent workflows, voice interaction, document intelligence, and autonomous agents.

You will begin with the foundations required to build AI applications, including Python programming, libraries, file handling, functions, modules, environments, and practical application development. You will then learn how to build graphical user interfaces using Tkinter and create voice-enabled applications using speech recognition and text-to-speech technologies.

Next, the course moves into the modern AI stack. You will learn the fundamentals of Generative AI and Large Language Models, including tokens, context windows, model parameters, transformers, temperature, prompt engineering, structured output, Python-based LLM integration, streaming responses, error handling, function calling, tool use, security, and cost considerations.

You will then build intelligent voice assistants that combine speech recognition, LLMs, conversation memory, text-to-speech, wake-word interaction, tools, and continuous conversation.

The course also introduces AI agents and Agentic AI systems. You will learn agent architecture, reasoning and planning, tool selection, memory, multi-step workflows, error recovery, safety, and how to build an AI agent capable of performing real tasks.

You will also master Retrieval-Augmented Generation (RAG), including embeddings, semantic search, document chunking, vector search, retrieval, context injection, document processing, and building applications that can interact with your own documents.

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