The Complete Dart Language Guide for Beginners[Arabic]

Master FastAPI — the modern, high-performance Python web framework — through 600 carefully crafted practice questions spanning everything from your first route to production deployment.This course is organized into six comprehensive practice tests, each with 100 multiple-choice questions. Every question includes a detailed explanation for all four answer options, not just the correct one, so you understand the reasoning behind each concept rather than simply memorizing answers.Test 1: FastAPI Fundamentals Routing — Path and query parameters, request/response handling, automatic OpenAPI documentation, middleware, and routing patterns.Test 2: Pydantic Models Data Validation — Field constraints, custom validators, nested models, serialization, and data integrity best practices.Test 3: Async Programming Dependency Injection — async/await, concurrency vs. parallelism, FastAPI's dependency injection system, background tasks, and resource management.Test 4: Authentication, Security Middleware — Password hashing, JWTs, OAuth2, RBAC, CORS, rate limiting, and common web vulnerabilities like IDOR and CSRF.Test 5: Databases, Testing Debugging — SQLAlchemy ORMs, migrations, transactions, pytest fixtures, mocking, and performance diagnosis.Test 6: Production, Deployment Microservices — Docker, Kubernetes, CI/CD, blue-green and canary deployments, circuit breakers, and observability.Whether you're learning FastAPI for the first time, preparing for a technical interview, or validating production-level knowledge, this course gives you a structured, thorough way to test and deepen your understanding.

Unlock the power of Artificial Intelligence, Machine Learning, Data Science, and Cloud Computing with this comprehensive hands-on course designed for beginners, students, software developers, data analysts, and IT professionals. Whether you are starting your AI journey or looking to enhance your existing skills, this course provides a step-by-step learning path from the fundamentals to advanced real-world applications.You will begin by learning Python programming for data science and machine learning, followed by data preprocessing, exploratory data analysis (EDA), feature engineering, data visualization, and statistical concepts. As you progress, you will implement popular machine learning algorithms for regression, classification, clustering, recommendation systems, anomaly detection, and dimensionality reduction using industry-standard Python libraries.The course also introduces modern Artificial Intelligence concepts, including deep learning, neural networks, computer vision, and natural language processing (NLP). Through practical coding exercises and real-world projects, you will gain the confidence to build intelligent applications that solve business problems.In addition to AI and machine learning, you will learn how to leverage Amazon Web Services (AWS) to build scalable, cloud-based AI solutions. You'll understand cloud fundamentals, data storage, model deployment, scalable inference, monitoring, and best practices for deploying machine learning models in production environments.Throughout the course, you will work on multiple hands-on projects that reinforce every concept and help you build a professional portfolio. By the end of the course, you will have the practical skills needed to analyze data, develop machine learning models, build AI-powered applications, and deploy them on AWS using industry best practices.Whether your goal is to become a Data Scientist, Machine Learning Engineer, AI Engineer, Python Developer, or Cloud AI Professional, this course provides

Unlock the power of Artificial Intelligence, Machine Learning, Data Science, and Cloud Computing with this comprehensive hands-on course designed for beginners, students, software developers, data analysts, and IT professionals. Whether you are starting your AI journey or looking to enhance your existing skills, this course provides a step-by-step learning path from the fundamentals to advanced real-world applications.You will begin by learning Python programming for data science and machine learning, followed by data preprocessing, exploratory data analysis (EDA), feature engineering, data visualization, and statistical concepts. As you progress, you will implement popular machine learning algorithms for regression, classification, clustering, recommendation systems, anomaly detection, and dimensionality reduction using industry-standard Python libraries.The course also introduces modern Artificial Intelligence concepts, including deep learning, neural networks, computer vision, and natural language processing (NLP). Through practical coding exercises and real-world projects, you will gain the confidence to build intelligent applications that solve business problems.In addition to AI and machine learning, you will learn how to leverage Amazon Web Services (AWS) to build scalable, cloud-based AI solutions. You'll understand cloud fundamentals, data storage, model deployment, scalable inference, monitoring, and best practices for deploying machine learning models in production environments.Throughout the course, you will work on multiple hands-on projects that reinforce every concept and help you build a professional portfolio. By the end of the course, you will have the practical skills needed to analyze data, develop machine learning models, build AI-powered applications, and deploy them on AWS using industry best practices.Whether your goal is to become a Data Scientist, Machine Learning Engineer, AI Engineer, Python Developer, or Cloud AI Professional, this course provides

Step into the next generation of artificial intelligence by mastering Agentic AI, where intelligent AI agents can reason, plan, use tools, retrieve information, and complete complex tasks autonomously. This comprehensive course is designed to help learners build production-ready AI agents using modern frameworks, large language models (LLMs), and real-world development practices.You'll begin by understanding the fundamentals of Agentic AI, including how autonomous AI agents differ from traditional AI applications. From there, you'll explore essential concepts such as prompt engineering, reasoning workflows, memory, planning, tool calling, Retrieval-Augmented Generation (RAG), multi-agent systems, and Model Context Protocol (MCP).Through hands-on projects, you'll learn how to build intelligent AI assistants that interact with APIs, databases, files, search engines, and external tools. You'll develop AI agents capable of solving real-world business problems, automating workflows, analyzing data, generating content, and collaborating with other AI agents to accomplish complex objectives.The course emphasizes practical implementation using Python and modern AI development frameworks, enabling you to design, test, deploy, and optimize scalable Agentic AI applications. Along the way, you'll gain experience with best practices for agent architecture, orchestration, evaluation, safety, and performance optimization.Whether you're a software developer, AI engineer, data scientist, automation specialist, cloud professional, or technology enthusiast, this course provides the skills and confidence to build intelligent, autonomous AI systems for real-world applications. By the end of the course, you'll have a portfolio of practical Agentic AI projects and the expertise needed to create the next generation of AI-powered solutions

Unlock the full power of Generative AI with this practical, beginner-friendly course on effective prompt engineering. Whether you’re using ChatGPT, Gemini, Claude, or any other modern AI system, the ability to write clear, structured prompts is now one of the most valuable skills in work and everyday life.In this course, you’ll learn a proven, easy-to-use prompting framework that helps you get better, more accurate, and more reliable results - even if you’re brand new to AI. We’ll start with the fundamentals of prompting, explore why prompting matters today, and then move into the core of the course: the T-C-R-E-I framework. You’ll learn how to define the Task, add Context, include helpful References, Evaluate AI outputs, and Iterate for improvement.Through real examples and step-by-step demonstrations, you’ll see how to refine responses, fix mistakes, and transform average outputs into great ones using structured iteration techniques. We’ll also explore image prompting, where you’ll learn how to control style, emotion, lighting, and composition to create better visuals. Then we expand into multimodal prompting, using images and other media to get richer, more precise results.You’ll also learn how to avoid common AI pitfalls such as hallucinations, vague answers, and misleading responses. A dedicated section on Responsible AI will help you use these tools safely and effectively in a workplace environment.By the end of this course, you’ll have a complete toolkit for working confidently with Generative AI - no technical skills required. You’ll understand how to think about prompts, structure them properly, iterate like a professional, and apply your new skills immediately in writing, research, planning, creativity, and more.Whether you’re a student, professional, creator, entrepreneur, or simply curious about AI, this course will help you w

Learn how to communicate more effectively with autistic clients using a practical, neurodiversity-affirming approach.If you’re a therapist, coach, or healthcare professional, you may have found that traditional autism approaches don’t always translate well into real conversations.This course helps you work more effectively in those moments — building trust, reducing misunderstandings, and supporting more authentic communication with autistic clients.Includes practical tools, scripts, and downloadable resources you can use immediately in your work.What this course isThe Autism Dialogue Approach Foundations Course introduces a practical framework for improving communication with autistic clients in therapeutic, coaching, and support settings.The Autism Dialogue Approach (ADA) has been developed over 10 years of clinical and coaching practice. It offers an alternative to behaviour-focused models by focusing on interaction, meaning-making, and the lived experience of autistic clients.Grounded in neurodiversity, lived experience, and social science, this course helps you move beyond surface-level techniques and develop a more responsive, relational way of working.Who this course is forThis course is designed primarily for:Therapists working with autistic clientsCounsellors and psychotherapistsCoaches supporting neurodivergent clientsMental health professionals and healthcare practitionersIt is ideal if you want to:Improve communication with autistic clientsWork in a more neurodiversity-affirming wayMove beyond behaviour-focused or deficit-based modelsBuild stronger therapeutic relationshipsAlso relevant for:Educators and group facilitatorsAutistic adults interested