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View File Complete Microservices with Go File Name: Complete Microservices with Go Content Source: https://www.udemy.com/course/complete-microservices-with-go/ Genre / Category: Coding Courses Language: ENGLISH Original Price: $99 ABOUT THE COURSE: In this project‑driven course, you’ll build the backend microservices system for a Uber‑style ride‑sharing app from the ground up—using Go, Docker, and Kubernetes. The course includes an introduction to Advanced Go mini-course, so you can expect the full package if you are new to Go. By the end, you’ll have a fully deployed, horizontally scalable ride‑sharing system that’s ready for real traffic. Plus, you’ll walk away with reusable template for building future distributed projects—accelerating your path to become a lead engineer. The project we'll build is composed of multiple services that are orchestrated with Kubernetes, you have this beautiful UI, where if you click on the map you’ll be able to preview a route to your destination and then by selecting the desired package, request a ride from a pool of available drivers. This course aims to provide you with the foundational knowledge required to build and understand distributed backend systems, implement industry best practices, and create production-ready microservices architecture that are scalable and maintainable. It is not just a step-by-step tutorial, but a comprehensive learning experience that prepares you for real-world scenarios. Submitter THEE DARK Submitted 05/31/2026 Category Paid Coding Courses Sale page https://www.udemy.com/course/complete-microservices-with-go/  

OpenClaw - Build Your 24/7 Personal AI Agents From Zero View File File Name: OpenClaw: Run Powerful & Autonomous AI Agents Securely Content Source: https://www.udemy.com/course/openclaw-course/ Genre / Category: Coding Courses Language: ENGLISH Original Price: $99 ABOUT THE COURSE: The fastest-growing open-source project in GitHub history — already past 350,000 stars — and it's a free, personal AI agent that actually works for you. If you're a freelancer — imagine waking up to competitor reports, client emails, and task updates already handled. If you're a business owner — imagine an agent that manages files, browses the web, sends emails, and runs on autopilot while you focus on growth. If you're a developer or tech enthusiast — imagine building your own mission control dashboard, second brain, and automated workflows with a real AI agent under your full control. That's exactly what OpenClaw gives you. And this course shows you how to set it up, secure it, and put it to work — from day one. OpenClaw is a free, open-source AI agent that lives on your own device — your computer, a VPS, or dedicated hardware. You message it through Telegram or WhatsApp like you'd message a friend, and it takes real action: managing files, browsing the web, sending emails, scheduling tasks, running commands, and connecting to all your favourite apps. In this complete, hands-on course, you'll learn how to install, configure, and secure OpenClaw the right way — even if you've never done anything like this before. This is not just another setup tutorial. You'll go from zero all the way to building real projects, real automations, and your own custom Mission Control Dashboard — step by step. By the end of this course, you'll have a fully working personal AI agent that runs for you every single day — handling tasks, delivering reports, managing your knowledge base, and saving you hours of repetitive work. You'll also get 100+ ready-to-use prompts, 10+ detailed PDF guides (including a full AI Models reference, a production deployment checklist, and a second brain setup guide), plus lifetime access to our private student community. What You'll Learn in This Course: Section 1: Course Introduction Understand what OpenClaw is, who built it, and why it matters in the personal AI space See how OpenClaw compares to Claude Code, Cowork, n8n, and other AI tools — and when to use each one Discover 6 real-world use cases that show what OpenClaw can do for you right now Get access to all the tools, links, and resources you need before diving in Section 2: Setting Up OpenClaw Choose where to run your agent — locally on Mac, Linux, or Windows, or on a cloud VPS — and set it up from scratch Install OpenClaw, connect it to Telegram, and launch your agent for the first time Get a full walkthrough of the gateway dashboard so you feel confident navigating everything Harden your agent's security and learn how to manage API costs from the start Section 3: Models & Cost Control Understand the different AI model tiers, their real costs, and how to pick the right one for your needs Set up smart model routing and free fallback models so your agent keeps running without burning through credits Run OpenClaw for free or near-free using local models and open-source alternatives Section 4: Everyday Features, Integrations & Skills Use voice mode, organise your Telegram with groups, and install Google Workspace to supercharge your agent Understand Skills — how they work, how to stay safe, and how they extend what your agent can do Build your first mini project: a full email automation powered by your agent Section 5: Real Projects with Your Agent Set up your agent's workspace files, memory, and identity so it remembers context and works the way you want Set up cron jobs and use sub-agents so OpenClaw handles bigger tasks on autopilot Build real projects: a landing page with sub-agents, an automated competitor watch report, and a daily intelligence digest Create a second AI brain with Obsidian and connect it to your agent for powerful knowledge management Section 6: Advanced Security Set up safe remote access to your server with SSH and Tailscale VPN Protect your agent against prompt injection attacks and keep all connections secure Get a production deployment checklist so you can trust your agent with real, sensitive work Section 7: Mission Control Dashboard Build your own personal command centre with a task board, calendar, projects, documents, and financial tracker Add a daily standup screen, team view, and memories panel — then customise it to fit your workflow Access Mission Control from your phone and optionally make it publicly available with Caddy Section 8: Keeping It Running & Moving Forward Handle updates, backups, snapshots, and recovery so your agent stays reliable long-term Troubleshoot common issues and migrate your setup when needed Find your own use cases, connect with the OpenClaw community, and keep building on what you've learned Now, why should we teach you this topic? Damian Danelczyk is an AI Engineer by education, with a degree in AI & Software Engineering and nearly 15 years of hands-on programming experience. He runs his own AI Automation Agency and works with these tools every day — building real systems for real clients. When it comes to OpenClaw, Damian brings the practitioner's perspective: security, architecture, and making things actually work in production. Krystian Wojtarowicz is an educator and course creator with 45+ courses and tens of thousands of students worldwide. He specialises in translating complex AI and automation topics into clear, step-by-step learning that actually sticks — so you never feel lost, even if this is your very first time working with an AI agent. Build your own personal AI agent, secure it properly, and put it to work on real tasks — every single day. Submitter THEE DARK Submitted 05/31/2026 Category Paid Coding Courses Sale page https://www.udemy.com/course/openclaw-course/  

View File OpenClaw: Run Powerful & Autonomous AI Agents Securely File Name: OpenClaw: Run Powerful & Autonomous AI Agents Securely Content Source: https://www.udemy.com/course/openclaw-run-powerful-autonomous-ai-agents-securely/ Genre / Category: Coding Courses Language: ENGLISH Original Price: $99 ABOUT THE COURSE: Stop renting AI. Start owning your digital workforce. You’ve used ChatGPT, Claude, Gemini, maybe also n8n, and you’ve seen AI agents. But have you ever had a true AI Employee that lives on your server, manages your files, codes itself, and pings you on Telegram when the job is done? Welcome to the OpenClaw Masterclass. This course is your blueprint for building a fully autonomous, privacy-focused AI ecosystem. Whether you want a local assistant running on your laptop or a 24/7 digital worker on a VPS, OpenClaw is the framework that makes it happen. We move beyond simple "chat" interfaces. You will learn to deploy OpenClaw, an agent with a Soul, a Heartbeat, and a distinct Identity. It doesn't just answer; it proactively works for you using tools and memory files that you control. You will learn how to orchestrate LLMs to hear you (Whisper), see your files, execute commands, and even manage other AIs (like Claude Code, OpenCode or Codex) to write software. What You’ll Get: Real-World Deployments: Set up OpenClaw locally (Windows/Mac/Linux) or as a remote VPS employee. The "Soul" Architecture: Deep dive into the configuration files (Soul, Identity, User) that make your agent unique. Custom Skills: Build agents that can send emails, generate images locally, browse the web, and manage your calendar. Cost-Saving Strategies: Learn smart model routing, prompt caching, and local model integration to run AI almost for free. Security Best Practices: Complete guides on firewalls, SSH hardening, and safe skill installation. What You’ll Learn in This Course: Foundations: The OpenClaw Ecosystem Start strong by setting up your command center. Universal Installation: Master the setup on Linux, macOS, Windows, or Docker. Onboarding: Configure Telegram, WhatsApp, iMessage or Slack to be your primary interface and control your AI from anywhere in the world. Hooks & Plugins: Configure Hooks so OpenClaw "remembers" you and proactively notifies you via Telegram when tasks are done. Designing the AI's Personality (The Core Files) Don't just build a bot—create a digital being. The Soul File: Learn to write the DNA of your agent. Define its core purpose, ethical boundaries, and personality traits. The Identity File: Give your agent a specific persona and tone. The User File: Teach the agent who you are. Store your preferences, bio, and working style so the AI adapts to you. The Agent File: The operational brain. Define how the agent processes information and prioritizes tasks. The Heartbeat: The rhythm that keeps your agent alive. Configure the Heartbeat file to trigger background tasks and autonomy. Local Power: Privacy, Voice & Vision Turn your local machine into an AI powerhouse. File System Mastery: Give OpenClaw the ability to access, organize, and modify your PC files remotely. Voice Input: Talk to OpenClaw naturally using Whisper and FFmpeg integration. Local Image Generation: Create custom Tools to trigger ComfyUI workflows directly from your chat. Agentic Coding: Watch OpenClaw modify its own settings and orchestrate tools like Claude Code or Codex for software development. Context Management & Cost Optimization Make your AI smarter while spending less. Ollama Integration: Run models offline, privately, and for free using your own hardware. Context Engineering: Master context files and sessions so your agent "remembers" complex projects without hallucinating. Smart Economics: Implement prompt caching, smart model routing, and "lean init" strategies to drastically reduce API bills. The VPS Employee: 24/7 Automation & DevOps Deploy a separate digital employee that works while you sleep. VPS Deployment: A step-by-step guide to hosting OpenClaw on a Virtual Private Server. Google Cloud & Email: Automate your inbox and integrate deeply with Google Services. Deep Research: Enable web fetching and browser automation (via Brave, Playwright & Perplexity) to have your agent scour the internet for you. Cron Jobs & Cronos: Set up complete automated schedules: Your agent wakes up, does the work, and reports back. Advanced Security & The Future Protect your digital asset and stay ahead. Server Security: Learn essential DevOps skills: Closing ports, configuring firewalls, and securing SSH to keep your agent safe. MoltBook: Discover the "New Internet for AI Agents" and how to leverage it. Skill Expansion: Learn the difference between safe and unsafe skill installation methods. Become the Architect of Your Own AI Force! By the end of this course, you won't just be using AI... You will be managing a robust, autonomous system that works for you. You will understand how to manipulate the Soul file to change behavior, how to use the Heartbeat to create autonomy, and how to secure your digital employee. Submitter THEE DARK Submitted 05/31/2026 Category Paid Coding Courses Sale page https://www.udemy.com/course/openclaw-run-powerful-autonomous-ai-agents-securely/  

View File Machine Learning A-Z [2026]: ML, DL, AI with AWS, Python & R File Name: Machine Learning A-Z [2026]: ML, DL, AI with AWS, Python & R Content Source: https://www.udemy.com/course/machinelearning/ Genre / Category: Coding Courses Language: ENGLISH Original Price: $99 ABOUT THE COURSE: This course has been designed by two AI & Machine Learning experts so that we can share our knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way. We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. This course can be completed by doing either the AWS tutorials, Python tutorials, or R tutorials, or the three of them - AWS, Python & R. Pick the ones you need for your career. This course is fun and exciting, and at the same time, we dive deep into Machine Learning. It is structured the following way: Part 1 - Data Preprocessing: Importing the dataset with pandas, Matrix of Features and Target Vector, Training & Test Sets, Imputing Missing Data, Encoding Categorical Variables, Feature Scaling Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification Part 4 - Clustering: K-Means, Hierarchical Clustering Part 5 - Association Rule Learning: Apriori, Eclat Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling Part 7 - Natural Language Processing: Bag-of-words model and algorithms for NLP Part 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural Networks Part 9 - Dimensionality Reduction: PCA, LDA, Kernel PCA Part 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost Part 11 - ML Data Preprocessing with AWS: Data types (Apache Parquet, JSON, CSV), Data Preparation with S3, ETL with AWS Glue, Data Wrangling with AWS Glue DataBrew & SageMaker Data Wrangler, Feature Engineering with SageMaker Part 12 - ML Model Development with AWS: XGBoost, LightGBM, CatBoost, Ensemble Models, Hyperparameter Tuning Techniques, Building Ensemble Models for Regression & Classification with Amazon SageMaker AI, Natural Language Processing with Amazon Comprehend, Computer Vision with Amazon Rekognition, Text to Speech with Amazon Polly, Speech To Text with Amazon Transcribe, Text Extraction with Amazon Textract, Machine Translation with Amazon Translate Part 13 - ML Model Deployment with AWS: Methods for Deploying Models in Production, Deployment in Amazon SageMaker AI, Serverless vs. Real-Time vs. Asynchronous Inference, Deployment Endpoints in Amazon SageMaker, SageMaker vs. ECS vs. EKS vs. Lambda Deployment Targets, CloudFormation & Cloud Development Kit (CDK), Elastic Container Registry (ECR), Elastic Container Service (ECS) & Fargate, Building Containers with Amazon ECR, ECS & EKS Part 14 - ML Workflow Automation (CI/CD Pipelines) with AWS: AWS CodePipeline, AWS CodeBuild, AWS CodeCommit, AWS CodeDeploy, Creating an ML pipeline with Amazon SageMaker Pipelines Part 15 - ML Solution Monitoring and Maintenance with AWS: Features of Responsible AI, Legal Risks of Generative AI, Tools for Responsible ML, Model/Data Quality and Bias Drift with SageMaker Clarify, Monitoring Models in Production with SageMaker Model Monitor, SageMaker Model Cards, SageMaker Inference Recommender, SageMaker Savings Plans Submitter THEE DARK Submitted 05/28/2026 Category Paid Coding Courses Sale page https://www.udemy.com/course/machinelearning/  

View File The AI Engineer Course 2026: Complete AI Engineer Bootcamp File Name: The AI Engineer Course 2026: Complete AI Engineer Bootcamp Content Source: https://www.udemy.com/course/the-ai-engineer-course-complete-ai-engineer-bootcamp/ Genre / Category: Coding Courses Language: ENGLISH Original Price: $99 ABOUT THE COURSE: AI Engineers are best suited to thrive in the age of AI. It helps businesses utilize Generative AI by building AI-driven applications on top of their existing websites, apps, and databases. Therefore, it’s no surprise that the demand for AI Engineers has been surging in the job marketplace. Supply, however, has been minimal, and acquiring the skills necessary to be hired as an AI Engineer can be challenging. So, how is this achievable? Universities have been slow to create specialized programs focused on practical AI Engineering skills. The few attempts that exist tend to be costly and time-consuming. Most online courses offer ChatGPT hacks and isolated technical skills, yet integrating these skills remains challenging. The Solution AI Engineering is a multidisciplinary field covering: AI principles and practical applications Python programming Natural Language Processing in Python Large Language Models and Transformers Developing apps with orchestration tools like LangChain Vector databases using PineCone Creating AI-driven applications Each topic builds on the previous one, and skipping steps can lead to confusion. For instance, applying large language models requires familiarity with Langchain—just as studying natural language processing can be overwhelming without basic Python coding skills. So, we created the AI Engineer Bootcamp 2025 to provide the most effective, time-efficient, and structured AI engineering training available online. This pioneering training program overcomes the most significant barrier to entering the AI Engineering field by consolidating all essential resources in one place. Our course is designed to teach interconnected topics seamlessly—providing all you need to become an AI Engineer at a significantly lower cost and time investment than traditional programs. The Skills 1. Intro to Artificial Intelligence Structured and unstructured data, supervised and unsupervised machine learning, Generative AI, and foundational models—these are familiar AI buzzwords; what exactly do they mean? Why study AI? Gain deep insights into the field through a guided exploration that covers AI fundamentals, the significance of quality data, essential techniques, Generative AI, and the development of advanced models like GPT, Llama, Gemini, and Claude. 2. Python Programming Mastering Python programming is essential to becoming a skilled AI developer—no-code tools are insufficient. Python is a modern, general-purpose programming language suited for creating web applications, computer games, and data science tasks. Its extensive library ecosystem makes it ideal for developing AI models. Why study Python programming? Python programming will become your essential tool for communicating with AI models and integrating their capabilities into your products. 3. Intro to NLP in Python Explore Natural Language Processing (NLP) and learn techniques that empower computers to comprehend, generate, and categorize human language. Why study NLP? NLP forms the basis of cutting-edge Generative AI models. This program equips you with essential skills to develop AI systems that meaningfully interact with human language. 4. Introduction to Large Language Models This program section enhances your natural language processing skills by teaching you to utilize the powerful capabilities of Large Language Models (LLMs). Learn critical tools like Transformers Architecture, GPT, Langchain, HuggingFace, BERT, and XLNet. Why study LLMs? This module is your gateway to understanding how large language models work and how they can be applied to solve complex language-related tasks that require deep contextual understanding. 5. Building Applications with LangChain LangChain is a framework that allows for seamless development of AI-driven applications by chaining interoperable components. Why study LangChain? Learn how to create applications that can reason. LangChain facilitates the creation of systems where individual pieces—such as language models, databases, and reasoning algorithms—can be interconnected to enhance overall functionality. 6. Vector Databases With emerging AI technologies, the importance of vectorization and vector databases is set to increase significantly. In this Vector Databases with Pinecone module, you’ll have the opportunity to explore the Pinecone database—a leading vector database solution. Why study vector databases? Learning about vector databases is crucial because it equips you to efficiently manage and query large volumes of high-dimensional data—typical in machine learning and AI applications. These technical skills allow you to deploy performance-optimized AI-driven applications. 7. Speech Recognition with Python Dive into the fascinating field of Speech Recognition and discover how AI systems transform spoken language into actionable insights. This module covers foundational concepts such as audio processing, acoustic modeling, and advanced techniques for building speech-to-text applications using Python. Submitter THEE DARK Submitted 05/28/2026 Category Paid Coding Courses Sale page https://www.udemy.com/course/the-ai-engineer-course-complete-ai-engineer-bootcamp/