Kshitij Joy (Cloud Alchemy)

Run Local LLMs with Ollama: From No-Code to Python Code

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This course offers a comprehensive, hands-on journey into the world of running large language models locally using Ollama. Led by Kshitij Joy of Cloud Alchemy, the curriculum expertly bridges the gap between no-code accessibility and advanced Python programming. Students begin by exploring foundational AI concepts, deep learning, and neural networks, before diving deep into the specifics of Meta Llama 3.2 and 3.3. Through step-by-step demonstrations, learners set up Ollama across various environments, including Linux, Mac, and Docker, and master the Ollama CLI. The course transitions smoothly from no-code interfaces like OpenWebUI to practical developer workflows, demonstrating how to integrate local models with VSCode, Jupyter Notebooks, and Google Colab. Advanced topics such as multimodal image analysis, LangChain integrations, OpenAI-compatible APIs, structured outputs, and function calling are thoroughly covered. This course is ideal for software developers, privacy-conscious tech enthusiasts, and no-code builders who want to harness the power of state-of-the-art open-source LLMs locally on their own machines without relying on expensive cloud APIs.

Mastering MCP: Beginner to Pro Across the AI Ecosystem

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Mastering MCP: Beginner to Pro Across the AI Ecosystem, created by Kshitij Joy (Cloud Alchemy), is the definitive guide to mastering the revolutionary Model Context Protocol (MCP). This course is designed for AI developers, software engineers, and system architects who want to seamlessly connect Large Language Models (LLMs) with external data sources, filesystems, and proprietary APIs. Throughout this hands-on curriculum, you will explore the core architecture of MCP, including JSON-RPC 2.0, transport layers like STDIO and SSE, and the integration with Claude Desktop. The course takes you through practical, step-by-step labs to build your own MCP servers and connect them with modern frameworks like LangChain, LlamaIndex, OpenAI SDK, Google ADK, and Gemini. By implementing real-world scenarios—such as linking SQLite databases, managing local filesystems, and interfacing with APIs like PayPal—you will acquire the skills needed to build robust, context-aware AI applications. Whether you are aiming to optimize enterprise workflows or develop cutting-edge AI agents, this comprehensive guide provides the practical knowledge to transition from beginner to pro in the rapidly growing Claude AI ecosystem.

Copilot Studio: Build Real-World Agents-Beginner to Pro

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Copilot Studio: Build Real-World Agents-Beginner to Pro is a comprehensive, hands-on masterclass designed to take you from a complete beginner to an advanced creator of intelligent AI agents. Led by Kshitij Joy of Cloud Alchemy, this course bridges the gap between theoretical artificial intelligence and practical, low-code deployment. Throughout this 6.5-hour journey, you will explore Microsoft's Copilot Studio ecosystem, mastering how to build, configure, and publish sophisticated agents without writing complex code. The curriculum emphasizes practical application with eight real-world projects, including a Study Scheduler, a Document Insights Agent, and an Invoice Scanner. You will dive deep into foundational concepts such as manual configuration modes, system versus custom topics, knowledge sources, and node types. Furthermore, the course teaches you how to integrate advanced backend tools like Azure SQL DB, Dataverse, and REST APIs, alongside Retrieval-Augmented Generation (RAG) and Power Automate Flows. Whether you are an IT professional, business analyst, or aspiring AI engineer, this course equips you with the in-demand skills needed to automate complex business workflows and deploy multi-agent systems across various enterprise channels.