The Ultimate SQL & Snowflake Data Analysis Bootcamp - 2026

If you are a developer, data scientist, or AI enthusiast who wants to build and run large language models (LLMs) locally on your system, this course is for you. Do you want to harness the power of LLMs without sending your data to the cloud? Are you looking for secure, private solutions that leverage powerful tools like Python, Ollama, and LangChain? This course will show you how to build secure and fully functional LLM applications right on your own machine.In this course, you will:Set up Ollama and download the Llama LLM model for local use.Customize models and save modified versions using command-line tools.Develop Python-based LLM applications with Ollama for total control over your models.Use Ollama's Rest API to integrate models into your applications.Leverage LangChain to build Retrieval-Augmented Generation (RAG) systems for efficient document processing.Create end-to-end LLM applications that answer user questions with precision using the power of LangChain and Ollama.Why build local LLM applications? For one, local applications ensure complete data privacy—your data never leaves your system. Additionally, the flexibility and customization of running models locally means you are in total control, without the need for cloud dependencies.Throughout the course, you’ll build, customize, and deploy models using Python, and implement key features like prompt engineering, retrieval techniques, and model integration—all within the comfort of your local setup.What sets this course apart is its focus on privacy, control, and hands-on experience using cutting-edge tools like Ollama and LangChain. By the end, you’ll have a fully functioning LLM application and the skills to build secure AI systems on your own.Ready to build your own private LLM applications? Enroll now and get started!

Games should be exciting, full of secrets and special features! Let me take you step by step though my creative process and show you how I build unique game worlds for players to have adventures in. I will explain every line of code as we write it. Let's practise object oriented programming and use HTML, CSS and plain vanilla JavaScript to build a game. There will be no frameworks and no libraries, because we want deep understanding of how things work under the hood.Let's explore an alien planet and it's mechanical life forms in a steampunk themed 2D side scroller. We will learn how to implement:Sprite animationParallax backgroundsCollision detectionPower upsDifferent enemy types that alter the gameplayand many other features of 2D game developmentIf you are a beginner front end web developer curious about game development, creative coding web animation, come join me and learn how to create beautiful visuals for your games, and how to implement unique game features that will make your project stand out. Have fun!(In this class I am giving away a lot of free game art assets for characters, environments and props. These were created by me or artists I hired, there is no copyright. Feel free to use them for any of your personal projects if you want. )

Are you a Python enthusiast looking to expand your skills into the exciting world of mobile app development? Or perhaps you're a seasoned developer wanting to leverage Python's versatility for creating cross-platform mobile applications? Look no further!This hands-on, project-based course is meticulously designed to guide you through the entire process of developing real-world mobile applications using Python. You'll not only learn the fundamental concepts of mobile UI/UX design but also gain practical experience in building, testing, and even deploying your applications.What you'll learn:Python Fundamentals for Mobile DevelopmentMobile UI/UX PrinciplesBuilding Interactive User InterfacesImplementing App LayoutsNavigation and Screen ManagementWorking with MultimediaData Handling and StoragePlatform-Specific ConsiderationsBuilding 8+ Real-World Mobile ApplicationsPackaging and DeploymentBest Practices for Mobile App DevelopmentWho this course is for:Anyone interested in creating cross-platform mobile applications using a single codebase.By the end of this course, you will have:The skills to design and build visually appealing and functional mobile applications.A portfolio of 8+ mobile applications to showcase your abilities.The confidence to tackle your own mobile app ideas using Python.Enroll now and start your journey into the exciting world of Python mobile app development!

Vagrant is a open source tool for working with virtual environments. Vagrant acts as a wrapper and sits on top of the virtualization solution (VMware, Hyper-V ,Virtual Box or libvirt) and provides a simple command line interface to manage the VM's with the custom configuration. In this course students will learn the following : Introduction to VagrantBenefits of using VagrantInstallation and Configuration of VagrantDownloading the Vagrant BoxsBasics Administration of VagrantWorking with Ansible ProvisionerPerforming Vagrant AdministrationTroubleshooting and Maintenance

In this course, you will go from creating a bot, discovering all possible settings to exposing all power of Bot API and creating a real-world application. The course presents basic and advanced components of bots and has a lot of quizzes. His main feature that it is based not only on theory but also on questions from the beginner's bot developers.

You might have optimal machine learning algorithm to solve your problem. But once you apply it in real world soon you will realize that you need to train it on more data. Due to lack of large dataset you will try to further optimize the algorithm, tune hyper-parameters or look for some low tech approach. Most state of the art machine learning models are trained on large datasets. Real world performance of machine learning solutions drastically improves with more data. Through this course you will learn multiple techniques for augmenting text data. These techniques can be used to generate data for any NLP task. This augmented dataset can help you to bridge the gap and quickly improve accuracy of your machine learning solutions.