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React JS Masterclass: Zero To Job Ready With 10 Projects View File File Name: React JS Masterclass: Zero To Job Ready With 10 Projects Content Source: https://www.udemy.com/course/complete-reactjs-masterclass/ Genre / Category: Premium courses Password: Original Price: $49 Language: ENGLISH For Paid User Without URL Shortener: Download : GO TO SINGLE CLICK DOWNLOAD PAGE ABOUT THE COURSE: Welcome to React JS Masterclass, one single course to start your React journey as a beginner step-by-step. This course touches on each and every important topic through concept explanation, documentation, and implementation. The entire course is designed for beginners with one goal in mind, to learn concepts and build React projects. Throughout the course, we will explore the most important React topics step-by-step: JSX and components State and props Event handling Built-in hooks (e.g. useState, useEffect, useCallback, useRef) Working with forms, validations, and handling form data. Client-side routing with React Router Work with multiple API and handle data for projects Integrating with other libraries and frameworks (e.g. Redux) Testing and debugging React applications using popular libraries like Jest, RTL and React DevTools. DOM manipulation and manipulating the Virtual DOM Server-side rendering Optimizing the performance of React application Best practices for structuring and organizing React projects Building and deploying production-ready React applications, including code splitting and optimization techniques. Other Concepts: Building and using advanced Custom Hooks Styling with Tailwind CSS Integrating Context & Reducers Building mock backend with JSON Server & JSON Server Auth Integrating Firebase storage as well as authentication Project deployment on Netlify using Git & Github Integrating external libraries: Toastify & React Skeleton Why this course? Complete course is focused on the concept learning approach, you learn every concept through a logical and visual learning approach. Learn all important concepts in the simplest possible way with examples and real-life projects. You need HTML, CSS and JavaScript knowledge, we will cover everything about React step-by-step from scratch. The course is designed for developers who have some experience with JavaScript and web development and want to learn how to build dynamic, responsive user interfaces using React. ------------------ After completing this course you will be ready to work as an Intern, Fresher, or Freelancer and you will also be able to implement everything yourself! Most importantly you will have the potential to build, test and deploy your own projects. Submitter S A N Submitted 06/26/2026 Category Courses Sale page https://www.udemy.com/course/complete-reactjs-masterclass/

View File Context Engineering File Name: Context Engineering Content Source: https://www.manning.com/books/context-engineering Genre / Category: E-Books Language: ENGLISH Price: $35.99 ABOUT THE E-BOOKS The responses from large language models (LLMs) are more accurate, consistent, and explainable when you provide specific relevant information, or context, to support your prompts. Context engineering is the discipline of selecting, organizing, updating, compressing, and prioritizing the precise context a model needs to generate accurate responses. This book shows you how to combine well-designed prompts with smart search, content filtering, and advanced RAG techniques incorporating many types of stored data to create reliable responses in your AI applications. Because context engineering is typically implemented programmatically, automation is essential as applications evolve from simple prompts to workflows, agents, and agentic systems. Context engineering is particularly critical with the rise of autonomous agents and context windows that can take in a million or more tokens. Irrelevant or poorly selected context raises the chance of hallucinations, brittle agents, and unpredictable outputs. In Context Engineering, author Boni García helps you design an AI’s information environment with the same rigor as your codebase. It unifies every part of the context stack—including RAG, memory, and harness engineering—into one coherent discipline. The book takes you hands on with the entire context engineering stack. You'll learn how to use tools such as DSPy, LangChain, CrewAI, and LlamaIndex to build context-aware AI applications with frontier models from OpenAI, Anthropic, and Google. Because each chapter builds intuition first and ends with a practical hands-on section grounded in real tools, you’ll come away thinking like a system designer who knows exactly what enters the context window, what stays out, what gets retrieved just in time, and what becomes persistent memory or state. what's inside Design instructions and agent skills to govern model behavior Ground responses with RAG and external knowledge retrieval Integrate tools and the Model Context Protocol (MCP) Manage memory and state in agents and agentic systems Orchestrate multi-agent coordination and interoperability Deliver production-ready AI systems through evaluation, observability, governance, and operations Submitter S A N Submitted 06/25/2026 Category E-Books Sale page https://www.manning.com/books/context-engineering  

View File Codex CLI - Agentic Engineering from First Principles File Name: Codex CLI - Agentic Engineering from First Principles Content Source: https://leanpub.com/codex-cli Genre / Category: E-Books Language: ENGLISH Price: $19.99 ABOUT THE E-BOOKS Codex CLI: Agentic Engineering from First Principles is the most comprehensive guide to agentic software engineering with OpenAI's command-line coding agent. Across 28 chapters in six parts, you'll move from first principles to production workflows and team-scale practice: prompting and AGENTS.md configuration, approval modes and kernel-level sandboxing, model selection, context and cost management, MCP servers, hooks, skills, sub-agents and orchestration, worktrees, CI/CD integration, security hardening, and enterprise deployment. Later chapters cover debugging and testing agentic workflows, AI code review, practical engineering guides (codebase migration, backend, frontend, and infrastructure as code), and the bigger picture: benchmarks, competing tools, harness engineering, and how to structure an agentic engineering team. Whether you're a solo developer looking to multiply your output or an engineering lead rolling out agentic workflows across a team, this book gives you the mental models and practical techniques to work effectively with AI coding agents. Written by Daniel Vaughan and drawing on real-world experience and community insights, it equips every chapter with learning objectives, worked examples, and hands-on exercises. Submitter S A N Submitted 06/25/2026 Category E-Books Sale page  

View File AWS Bootcamp: Build AI Apps with AWS Bedrock File Name: AWS Bootcamp: Build AI Apps with AWS Bedrock Content Source: https://zerotomastery.io/courses/learn-aws-bedrock/ Genre / Category: Coding Courses Language: ENGLISH Original Price: $249 ABOUT THE COURSE: AWS Bedrock is Amazon Web Services' fully managed platform for building Generative AI applications. It lets you work with powerful foundation models while abstracting away infrastructure complexity. This course will take you from zero to building production-ready AI applications...even if you're completely new to Generative AI! Projects will integrate AWS Bedrock with API Gateway, AWS Lambda, S3, AgentCore, Postman, and other essential AWS services. Why This AWS Bedrock Course? Well, because it's the best, most up-to-date, and practical AWS Bedrock course online that lets you get hands-on by building six AWS Bedrock projects so that you can actually use your skills in the real-world. But of course we're biased. So here's some more details about what you'll learn in this AWS Bedrock course so that you can make up your own mind: 1. AWS Bedrock & Generative AI Foundations Understand what AWS Bedrock is, how it fits into the Generative AI ecosystem, and how modern AI applications are built using managed foundation models — explained in a beginner-friendly way. 2. Large Language Models (LLMs) Learn how LLMs work, what they excel at, and where their limitations lie. Explore real-world use cases including document understanding, chat systems, and code generation using Bedrock-hosted models. 3. Fine-Tuning & Reinforcement Fine-Tuning (RFT) Go beyond basic prompting. Learn how models can be improved using fine-tuning and RFT with human feedback, when and why to use these techniques, and how they fit into modern AI workflows. 4. Prompt Management & Optimization Design, manage, version, and optimize prompts for consistent, reliable results. Learn why prompt management becomes critical as applications scale and evolve. 5. Intelligent Model Routing Discover how to route requests intelligently between different models based on task type, cost, or quality — choosing the right model at the right time. 6. Batch Inference & Data Automation Process large volumes of data efficiently using batch inference, and automate document and data workflows using AWS Bedrock for scalable AI processing. 7. Image Generation with Diffusion Models Explore image generation concepts using diffusion models — including how to generate, control, and deploy image-based AI features at scale. 8. AI Safety, Evaluation & Watermark Detection Evaluate your LLMs for quality, accuracy, and toxicity. Understand AI safety concepts including watermark detection and responsible AI usage. 9. Serverless Deployment & Scaling Deploy Generative AI applications using a fully serverless stack — AWS Lambda, API Gateway, S3, and Bedrock — and scale AI applications without managing any servers. 10. AgentCore: From Prototype to Production Take your agents beyond local development. Learn what Amazon Bedrock AgentCore is, deploy agents on AgentCore Runtime, and monitor every tool call and decision with built-in observability — no servers to manage, production-ready from day one. 11. Agent Memory — Short-Term & Long-Term Give your agents the ability to remember. Implement short-term memory using get_last_k_turns so agents track conversation context within a session. Then add long-term memory with extraction strategies that automatically capture semantic facts, user preferences, and session summaries — so your agents personalize every interaction, even across sessions. 12. Guardrails & Responsible AI Learn how to use Amazon Bedrock Guardrails to add safety controls, filter harmful content, reduce risk, and enforce responsible AI behavior across your applications. 13. Model Comparison Compare different foundation models based on quality, speed, cost, capabilities, and use case fit so you can choose the right model for each task. 14. AWS Model Usage Quotas Understand AWS Bedrock model usage quotas, request limits, throttling, and how quotas affect real-world production applications. 15. Inference Profiles Learn how inference profiles work in Amazon Bedrock and how they help with scalable, reliable, and cross-region model invocation. 16. Marketplace Models on AWS Bedrock Explore Amazon Bedrock Marketplace Models and learn how to access additional foundation models beyond the default Bedrock catalog. 17. Advanced Bedrock Features Go beyond basic prompting and deployment by working with more production-focused AWS Bedrock capabilities used in real AI systems. Submitter S A N Submitted 06/25/2026 Category Paid Coding Courses Sale page https://zerotomastery.io/courses/learn-aws-bedrock/  

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