Prompt Engineering

Machine Learning for LLMs: Zero to Hero – Your Complete Roadmap with Resources

Large Language Models (LLMs) power tools like ChatGPT, revolutionizing how we interact with AI. This zero-to-hero guide takes you from foundational machine learning concepts to building, fine-tuning, and deploying LLMs, with curated link resources for hands-on learning.[1][2][3] Whether you’re a beginner with basic Python skills or an intermediate learner aiming for expertise, this post provides a structured path. We’ll cover theory, practical implementations, and pitfalls, drawing from top courses and tutorials. ...

Context Engineering: Zero-to-Hero Tutorial for Developers Mastering LLM Performance

Context engineering is the systematic discipline of selecting, structuring, and delivering optimal context to large language models (LLMs) to maximize reliability, accuracy, and performance—far beyond basic prompt engineering.[1][2] This zero-to-hero tutorial equips developers with foundational concepts, advanced strategies, practical Python implementations using Hugging Face Transformers and LangChain, best practices, pitfalls, and curated resources to build production-ready LLM systems.[1][7] What is Context Engineering? Context engineering treats the LLM’s context window—its limited “working memory” (typically 4K–128K+ tokens)—as a critical resource to be architected like a database or API pipeline.[2][5] It involves curating prompts, retrievals, memory, tools, and history to ensure the model receives the right information at the right time, enabling plausible task completion without hallucinations or drift.[1][4][6] ...

OpenAI Cookbook: Zero-to-Hero Tutorial for Developers – Master Practical LLM Applications

The OpenAI Cookbook is an official, open-source repository of examples and guides for building real-world applications with the OpenAI API.[1][2] It provides production-ready code snippets, advanced techniques, and step-by-step walkthroughs covering everything from basic API calls to complex agent workflows, making it the ultimate resource for developers transitioning from LLM theory to practical deployment.[4] Whether you’re new to OpenAI or scaling AI features in production, this tutorial takes you from setup to mastery with the Cookbook’s most valuable examples. ...