Introduction to GPT-3 and Modern LLMs with Python

Artificial intelligence is transforming how we build software, but getting started with large language models can feel overwhelming. This text-based course guides you step-by-step through the process of understanding, accessing, and integrating GPT-3 and modern OpenAI models into your own Python applications. You will transition from a curious developer to a creator capable of building smart, text-driven tools. What you'll learn: - Understand the core concepts of large language models, prompt engineering, and tokenization. - Configure your Python development environment and securely manage API keys. - Build text generation, summarization, and translation tools using Python code. - Implement modern retrieval-augmented generation patterns for more relevant model responses. - Apply error handling, rate limiting, and cost optimization strategies in your code. - Practice structuring clean, modern Python scripts with type hints and virtual environments. Your journey begins with a solid foundation in AI terminology, explaining how these powerful models work under the hood. From there, you will progress through structured text-based lessons that show you how to write Python code to connect to the API, structure prompts, and parse responses. The course concludes with practical application patterns that you can immediately adapt for your own projects. This course is designed for beginner-to-intermediate Python developers who want to enter the world of AI engineering. No prior experience with machine learning or artificial intelligence is required. Start reading today to unlock the potential of language models in your Python projects.