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Free Download Linkedin - AI-Driven Business Model Innovation Released 04/2025 With Ross Dawson MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 35s | Size: 111 MB Discover how to adapt your business models to seize emerging opportunities in the age of AI. Course details AI is transforming how value is created in the economy, offering new opportunities to evolve business models. In this course with thought leader Ross Dawson, business strategists and entrepreneurs will explore six key areas where AI's rapid development impacts business models and value creation. Through clear analysis and real-life examples, Ross provides guidance on how to seize these emerging opportunities. He covers not only the more well-known areas such as scalable efficiency and enhanced value propositions, but also delves into customer value co-creation, restructuring value delivery, shifts in platform models, and the rise of AI as a customer. By the end of this course, you'll have a more thorough understanding of AI's impact and the tools needed to design and implement effective business models in the AI era. Homepage https://www.linkedin.com/learning/ai-driven-business-model-innovation [b]AusFile[/b] https://ausfile.com/3uc9a1xteyfn/dueii.Linkedin..AIDriven.Business.Model.Innovation.rar.html Fileaxa https://fileaxa.com/fbr4lvppnb7b/dueii.Linkedin..AIDriven.Business.Model.Innovation.rar TakeFile https://takefile.link/ca33iq57tsno/dueii.Linkedin..AIDriven.Business.Model.Innovation.rar.html Rapidgator http://peeplink.in/8d0424d947b8 Fikper Free Download https://fikper.com/FiNQxdFxSx/dueii.Linkedin..AIDriven.Business.Model.Innovation.rar.html No Password - Links are Interchangeable

Free Download Udemy - Train Like a Fitness Model! by Catherine Bradshaw Published: 3/2025 Created by: Catherine Bradshaw MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Beginner | Genre: eLearning | Language: English | Duration: 28 Lectures ( 2h 2m ) | Size: 3.8 GB Movement Mastery What you'll learn Train Like a Real Life Fitness Model: Learn my secrets to achieving the elite athlete look even with a busy schedule. Boost Your Confidence: Feel empowered and self-assured as you work out, whether at the gym or at home, by mastering proper form and avoiding common mistakes. Maximize Your Workout Efficiency: Get the most out of every workout session by optimizing your techniques, leading to better results in less time. Achieve Your Health Goals: Focus on improving strength, posture, and overall movement, helping you feel better about your body. Requirements No experience needed. All you need is a yoga mat or towel. OPTIONAL: You will need access to gymnastics rings or a TRX system for the Ring Rows module. Description Welcome to Movement Mastery: Train Like a Fitness Model!Embark on a transformative fitness journey with our comprehensive Movement Mastery course. Enjoy a lifetime of access, allowing you ample time to revisit each module, master techniques at your own pace, and confidently progress with ongoing support and guidance.Movement Mastery presents nearly 2 hours of engaging, informative video content curated to seamlessly fit into your schedule while maximizing value in perfecting exercise techniques. With this course, you'll unlock the skills needed to perform foundational movements-including the Hollow Hold, Plank, Push-Up, Squat, Lunge, and Ring Row-with precision and confidence.Our focus is on mastering proper form, integrating mindful breathing, and building confidence in every move. Each section offers detailed, step-by-step instructions to guide you through these essential exercises. You'll learn to identify and correct common mistakes and explore progressions and variations tailored to suit your unique fitness journey.The course covers comprehensive video instructions on these six fundamental movements:1. Hollow Hold2. Plank3. Push-Up4. Squat5. Lunge6. Ring RowsEach lesson is thoughtfully divided into three sections:1. Step-By-Step Instructions2. Common Mistakes and Corrections3. Progressions and VariationsJoin Movement Mastery and refine your exercise techniques to enhance your fitness experience! Who this course is for 1. You want to start working out and don't know how to get started. 2. You want to feel confident when you're working out. 3. You want to get the most out of your workouts. 4. You want to workout safely and avoid injuries as much as possible. 5. You have limited time and need to learn at your own pace. 6. You want to start prioritizing their health by dedicating more time and energy to their fitness. Homepage: https://www.udemy.com/course/train-like-a-fitness-model/ [b]AusFile[/b] https://ausfile.com/n9yjbx5yq41d/qnnio.Train.Like.a.Fitness.Model.part1.rar.html https://ausfile.com/98ud5cr4ekxl/qnnio.Train.Like.a.Fitness.Model.part2.rar.html https://ausfile.com/esjzqge5jxb8/qnnio.Train.Like.a.Fitness.Model.part3.rar.html https://ausfile.com/o2avwacayow9/qnnio.Train.Like.a.Fitness.Model.part4.rar.html Rapidgator https://rg.to/file/467516e0fa8e6c23228c1c39e62667f9/qnnio.Train.Like.a.Fitness.Model.part1.rar.html https://rg.to/file/40ce6b46dbf6bc8978d7fe1125779959/qnnio.Train.Like.a.Fitness.Model.part2.rar.html https://rg.to/file/f91c4904ac8b63889df8a288322fe8ed/qnnio.Train.Like.a.Fitness.Model.part3.rar.html https://rg.to/file/162b3f55e8ab09a84fa242da831254cf/qnnio.Train.Like.a.Fitness.Model.part4.rar.html Fikper Free Download https://fikper.com/AuHF9cWoBz/qnnio.Train.Like.a.Fitness.Model.part1.rar.html https://fikper.com/2O2mgIIb5P/qnnio.Train.Like.a.Fitness.Model.part2.rar.html https://fikper.com/9gyeh9Gjlq/qnnio.Train.Like.a.Fitness.Model.part3.rar.html https://fikper.com/LjmF8oNRF3/qnnio.Train.Like.a.Fitness.Model.part4.rar.html No Password - Links are Interchangeable

Free Download Udemy - MCP - Model Context Protocol Quickstart Published: 3/2025 Created by: Kartik Marwah MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Beginner | Genre: eLearning | Language: English | Duration: 12 Lectures ( 45m ) | Size: 467 MB Build your own MCP Client & Server from Scratch using Python, Google Gemini API on MacOS. Connect server to Claude App What you'll learn Basics of Model Context Protocol (MCP) Build your own MCP Server using Python on MacBook, Connect it to Claude Desktop Get Free API Key for Google Gemini Build your own MCP Client using Python, Google Gemini API on MacBook Use your MCP Client with your MCP Server Requirements Basic Python Basic familiarity with LLMs like Google Gemini/Claude Code WalkThroughs Included, no in-depth experience needed Course Recorded using MacOS. Windows Users can follow at their discretion Description In this hands-on course, you will gain a solid foundation in the Model Context Protocol (MCP) and its bidirectional client-server architecture. We begin by exploring the fundamentals of MCP, equipping you with the conceptual understanding needed to work confidently with this powerful protocol.Next, you will implement your own MCP server in Python, hosted on a MacBook. This server will be connected to Claude Desktop, showcasing how you can interact with external tools. As part of this quick start, you'll build and test a tool that executes terminal commands via MCP using Claude Desktop.Building on this foundation, we'll guide you through developing your own MCP client in Python, integrating it with Google's Gemini API. With a free Gemini API Key from Google, you'll connect your client to your MCP server and perform tool invocations just like Claude Desktop.By the end of this course, you will:Understand the basic architecture and flow of MCPLearn to build and run an MCP server using PythonConnect your custom MCP server to Claude DesktopObtain and configure a free Google Gemini API KeyDevelop your own Python-based MCP client powered by Google GeminiTest the interaction between your client and server to run real commandsWhat This Course Does Not Cover:Advanced MCP primitives beyond tool-calling (for now, we focus only on tool invocation)Windows-specific setup: While many steps are applicable across platforms, this course uses a MacBook for demonstrations. Windows users may follow along at their discretion.Important Notes:This course uses tools, APIs, and services provided by third-party companies and open source projects. We do not offer any warranties or guarantees related to these services. Learners are responsible for understanding and agreeing to the terms and policies of each provider.While many resources exist in fragments across the web, this course brings everything together in a streamlined, tested, and learner-friendly format based on real-world implementations.Whether you're a developer, tinkerer, or AI enthusiast, this course will empower you to build practical systems using cutting-edge AI and modern protocol design. Join us and build your own MCP client and server from scratch! Who this course is for AI Agent Developers Software Engineers Entrepreneurs looking for a QuickStart on MCP Homepage: https://www.udemy.com/course/modelcontextprotocol/ [b]AusFile[/b] https://ausfile.com/0nxybg1y0knr/xcwsu.MCP..Model.Context.Protocol.Quickstart.rar.html Rapidgator https://rg.to/file/bac621f0ebddc10f1f009fa8f34d93b3/xcwsu.MCP..Model.Context.Protocol.Quickstart.rar.html Fikper Free Download https://fikper.com/WXzpwXeQqb/xcwsu.MCP..Model.Context.Protocol.Quickstart.rar.html No Password - Links are Interchangeable

Free Download Udemy - Deploy ML Model in Production with FastAPI and Docker Published: 3/2025 Created by: Meta Brains,Skool of AI MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 57 Lectures ( 3h 57m ) | Size: 1.7 GB Learn ML deployment using FastAPI, Docker, CI/CD, and Cloud platforms What you'll learn Deploy machine learning models in production using FastAPI and Docker. Create APIs for ML models using FastAPI with optimized endpoints. Containerize ML applications with Docker for scalable deployments. Set up CI/CD pipelines for automated deployment and testing. Train, evaluate, and save ML models, focusing on real-world datasets. Deploy ML models to cloud platforms like Heroku and Microsoft Azure. Build and integrate a simple frontend for ML model APIs. Implement logging, error handling, and request handling in APIs. Requirements Basic knowledge of Python programming. Familiarity with machine learning concepts and workflows. A computer with internet access for software setup. Willingness to learn and experiment with new tools like Docker and FastAPI. Description Stop building models that live and die in notebooks. It's time your ML creations actually see the light of day.Transform your machine learning projects from academic exercises to production-ready applications with this comprehensive, hands-on course. Master the entire ML deployment pipeline using industry-standard tools that employers are actively seeking.In this practical journey, you'll build real-world ML systems that deliver actual business value. Starting with fundamental ML concepts, you'll quickly progress to crafting robust APIs with FastAPI, containerizing applications with Docker, and deploying scalable solutions across multiple cloud platforms including Heroku and Microsoft Azure.What sets this course apart:Project-Based Learning: Build 4 complete end-to-end ML applications including score prediction, wine quality classification, and iris species identificationProduction-Level Skills: Learn industry best practices for API development, containerization, error handling, and latency optimizationFull-Stack Integration: Connect your ML models to both backend systems and user-friendly frontendsCI/CD Implementation: Establish automated testing and deployment pipelines used by professional development teamsCloud Deployment Mastery: Deploy your solutions to multiple cloud providers with monitoring and scaling capabilitiesWhether you're a data scientist looking to operationalize your models or a developer wanting to integrate ML into production applications, this course provides the missing link between experimental machine learning and deploying systems that create real business impact.By completion, you'll have a portfolio of deployed ML applications and the confidence to implement end-to-end ML systems that showcase your capabilities to potential employers.Don't just be another data scientist with models trapped on your hard drive. Become the invaluable engineer who makes ML work in the real world. Who this course is for Aspiring data scientists seeking to learn model deployment. Machine learning engineers aiming to enhance deployment skills. Software developers interested in integrating ML into applications. Tech enthusiasts curious about Docker, FastAPI, and cloud deployments. Professionals transitioning into MLops or AI engineering roles. Students with basic Python knowledge looking to build end-to-end ML projects. Homepage: https://www.udemy.com/course/deploy-ml-model-in-production-with-fastapi-and-docker/ [b]AusFile[/b] https://ausfile.com/86gi0rvgbtcq/uqjrg.Deploy.ML.Model.in.Production.with.FastAPI.and.Docker.part1.rar.html https://ausfile.com/plh2xwlc51h3/uqjrg.Deploy.ML.Model.in.Production.with.FastAPI.and.Docker.part2.rar.html Rapidgator https://rg.to/file/77a51c1ba7cd4dda47336b94d5b82619/uqjrg.Deploy.ML.Model.in.Production.with.FastAPI.and.Docker.part1.rar.html https://rg.to/file/eaf0780f05b76785f46301c3f01dd63d/uqjrg.Deploy.ML.Model.in.Production.with.FastAPI.and.Docker.part2.rar.html Fikper Free Download https://fikper.com/LQ54Jjc9LJ/uqjrg.Deploy.ML.Model.in.Production.with.FastAPI.and.Docker.part1.rar.html https://fikper.com/s2VR54mbx7/uqjrg.Deploy.ML.Model.in.Production.with.FastAPI.and.Docker.part2.rar.html No Password - Links are Interchangeable

Free Download Udemy - Business Model Pitch Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 393.14 MB | Duration: 0h 50m Mastering the Essentials of Entrepreneurship: From Value Propositions to Investor Pitching What you'll learn Understand the components and significance of a business model. Conduct market analysis to identify target audiences and competitors. Develop value propositions and revenue streams for business growth. Design effective marketing strategies and operational plans. Assess funding Requirements and create compelling pitches for investors. Requirements Basic understanding of business concepts and terminologies. Description Welcome to "Business Model Pitch," a comprehensive introduction to the fundamentals of creating and presenting successful business models. This course is designed for aspiring entrepreneurs and business professionals who wish to master the art of crafting compelling business pitches. In today's dynamic market environment, understanding and effectively communicating your business model is key to attracting investment and driving business success. Our program covers essential topics, including the definition and types of business models, market analysis, value proposition development, and revenue generation strategies. With structured lessons on marketing strategies, operational planning, and funding Requirements, this course offers a holistic approach to building viable business models.By the end of this course, you will have the skills needed to analyze market opportunities, develop customer-centric value propositions, and create investor-ready business pitches. Whether you're seeking to start a new venture or enhance your existing business acumen, this course will provide you with the tools and knowledge necessary for success.Join us on this journey to elevate your understanding and presentation of business models, and take the next step in your entrepreneurial journey.1. Introduction to Business ModelsDefinition and Key ComponentsImportance and Evolution of Business ModelsTypes of Business Models: Product, Service, and Subscription Models2. Market AnalysisUnderstanding the Target MarketConducting Market Segmentation and Identifying Customer NeedsMarket Size and Growth PotentialCompetitive Analysis and Unique Selling Proposition (USP)3. Value PropositionProblem Solving Approach and Benefits to CustomersDifferentiation Strategy and Delivering ValueRole of Customer Experience, Quality Assurance, and Feedback4. Revenue StreamsIdentifying Revenue Generators and Pricing StrategyExploring Additional Revenue Sources and Sales ForecastsFinancial Metrics, Break Even Analysis, and Long-Term Projections5. Marketing StrategyDeveloping a Go-To-Market Strategy and Marketing ChannelsCrafting Promotional Tactics and Brand PositioningTracking Success through Key Performance Indicators (KPIs)6. Operational PlanStructuring Core Operations and Supply Chain ManagementUtilizing Technology and Infrastructure for EfficiencyStaffing Needs, Risk Management, and Crisis Management Plan7. Funding RequirementsAnalyzing Capital Needs and Startup CostsOperational Expenses and Contingency FundInvestment Opportunities, Pitching to Investors, and Structuring Deals8. Conclusion and Call to ActionSummary of the Business ModelHighlighting Unique Attributes and Request for SupportFollow-Up Procedures, Setting Up Meetings, and Next Steps Aspiring entrepreneurs and business students seeking to sharpen their skills in establishing and growing a business. Homepage: https://www.udemy.com/course/business-model-pitch/ [b]AusFile[/b] https://ausfile.com/i0yf9c7megs8/hqusn.Business.Model.Pitch.rar.html Rapidgator https://rg.to/file/509fb20a07c7fda9dc314f6154a26e17/hqusn.Business.Model.Pitch.rar.html Fikper Free Download https://fikper.com/1XDOyXuclR/hqusn.Business.Model.Pitch.rar.html No Password - Links are Interchangeable

Free Download Linkedin - Model Context Protocol (MCP) Hands-On with Agentic AI Released 03/2025 With Morten Rand-Hendriksen MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 55m 11s | Size: 97 MB Use the Model Context Protocol (MCP) to build a universal interface connecting data, services, and custom tools to AI agents. Course details The Model Context Protocol (MCP) allows developers to add agent behavior to LLMs by providing a universal protocol providing context to language models so they can interface with data and applications in a consistent way. MCP servers expose resources (data), tools (actions), and prompts (instructions) for the LLM and the user to use in performing more complex operations. In this course you'll explore how the MCP works in Claude Desktop to extend its functionality, and you'll build your own MCP servers using Python and TypeScript to give LLMs new capabilities to do things on the computer, connect with external APIs, and perform advanced multi-step actions. Homepage: https://www.linkedin.com/learning/model-context-protocol-mcp-hands-on-with-agentic-ai [b]AusFile[/b] https://ausfile.com/imsjmd1r49kl/wjjme.Model.Context.Protocol.MCP.HandsOn.with.Agentic.AI.rar.html TakeFile https://takefile.link/baajtesmgxv7/wjjme.Model.Context.Protocol.MCP.HandsOn.with.Agentic.AI.rar.html Rapidgator https://rg.to/file/f5308fc785bc63711eca47c49aa32587/wjjme.Model.Context.Protocol.MCP.HandsOn.with.Agentic.AI.rar.html Fikper Free Download https://fikper.com/ouFWZQMKFf/wjjme.Model.Context.Protocol.MCP.HandsOn.with.Agentic.AI.rar.html No Password - Links are Interchangeable

Free Download LLM Apps - Prototyping, Model Evaluation, and Improvements Published: 3/2025 Created by: Dan Andrei Bucureanu MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Expert | Genre: eLearning | Language: English | Duration: 69 Lectures ( 5h 53m ) | Size: 3.25 GB Design, Test, and Benchmark LLM Apps: Fast Prototyping and Smart Evaluation for Optimal Performance What you'll learn Understand the tech landscape of LLM powered APPs When to use GEN AI and when to use Weak AI Setup the tools to integrate AI into your standard APP Get the basics of ai in module Introduction to AI Overview of Machine Learning Types Data Lifecycle - how data evolves with your ML Model Foundation Model lifecycle Fine Tunning of models through data Fine Tunning of models through prompt Fine Tunning of models through hyperparameter Using Huggingface models for work Agentic Frameworks as: Autogen, Browser User, Flowise AI Understand RAG and how to evaluate it Evaluate the LLM With RAGAs benchmarking Framework Understand the Confusion Matrix: accuracy, Recall, F1 score GLUE Benchmarking Framework Retrain and fine tune a computer Vision model Requirements Some AI Experience Experience with Prompting Some coding experience with Python Laptop abele to run VS code and some python apps LLM Api key 7-8 Hours and the will to improve Description Unlock the full potential of Large Language Models (LLMs) by understanding prototyping, model evaluation, and benchmarking. This hands-on course takes you through every stage of LLM development-from building and selecting models to fine-tuning, testing, and benchmarking them with industry-standard tools. Whether you're an AI beginner or a professional looking to enhance your expertise, this course provides the skills needed to create high-performing AI applications.What you'll learn: Set Up Your AI Development EnvironmentLearn how to prepare a powerful AI workspace with Python, VS Code, NPM, and essential AI libraries, ensuring a seamless development experience.Understand AI & Machine Learning BasicsExplore key concepts in AI, Machine Learning, and Deep Learning, including supervised vs. unsupervised learning, model training phases, and how LLMs process and generate responses.Selecting the Right AI Model for Your Use CaseDiscover how to choose the best pre-trained AI models for NLP, vision, and multi-modal applications. Learn when to use classification, clustering, and regression models and understand model complexity, speed, and accuracy trade-offs. Harness the Power of Retrieval-Augmented Generation (RAG)Enhance your AI applications with RAG, a technique that combines retrieval-based search with LLM responses for more accurate and context-aware AI outputs.Leverage the Hugging Face AI CommunityTap into the Hugging Face ecosystem-explore model repositories, learn about tokenizers and transformers, and contribute to the open-source AI movement.Fine-Tune Models for Maximum PerformanceExperiment with temperature settings, top-K and top-P sampling, and hyperparameter tuning to optimize LLM responses and efficiency.Supercharge Your AI with Data-Driven InsightsImprove model accuracy with K-Fold Cross Validation, learn effective data-splitting techniques, and explore overfitting and underfitting detection methods.Benchmark Your AI Models Like a ProCompare your models against industry benchmarks like GLUE and Hugging Face Leaderboards. Learn how to evaluate NLP models using standard metrics and perform real-world GLUE benchmarking with Python.Evaluate Computer Vision AI ModelsGo beyond text-based models! Learn how to benchmark vision-based AI models using CIFAR-10 and interpret test results for advanced model evaluation. Understand Model Evaluation with Confusion MatricesMaster Confusion Matrix analysis to assess classification model performance. Learn how to interpret True Positives, False Positives, False Negatives, and True Negatives to optimize AI predictions and reduce errors.Who Should Take This Course? 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