Module 1: Foundations of AI and Generative AI

➢ What is Artificial Intelligence?
➢ AI vs. Machine Learning vs. Deep Learning
➢ Brief history and milestones of AI
➢ Generative AI and Large Language Models (LLMs) explained simply
➢ Tokens, context windows, and how models generate answers
➢ Capabilities, limitations, and hallucinations
➢ How AI is transforming different fields: education, healthcare, business, engineering, law, media, and more

Module 2: The AI Tools Landscape and Choosing the Right Tool

➢ Categories of AI tools: text, image, audio, video, data, coding, and automation
➢ Leading AI assistants overview: ChatGPT, Claude, Gemini, Microsoft Copilot, DeepSeek, and others
➢ Free vs. paid plans and model tiers
➢ Criteria for evaluating and comparing tools: quality, cost, privacy, language support, and integrations
➢ Building a personal AI toolkit for your profession
➢ Staying current: how to follow and test new tools

Module 3: Working with AI Chat Assistants

➢ Account setup, interface tour, and conversation management
➢ Uploading and analyzing files: PDFs, Word, Excel, images, and screenshots
➢ Voice mode, vision, and multimodal interaction
➢ Web search and live information inside assistants
➢ Memory, personalization, and custom instructions
➢ Working in Arabic and English: translation, bilingual output, and dialect handling

Module 4: Prompt Engineering Fundamentals

➢ Anatomy of an effective prompt: role, task, context, constraints, and format
➢ Being clear, specific, and structured
➢ Providing context, examples, and reference material
➢ Controlling tone, length, style, and output format (tables, lists, JSON, emails)
➢ Iterating and refining: follow-up prompts and feedback loops
➢ Common prompting mistakes and how to fix them
➢ Hands-on practice with real tasks from different professions

Module 5: Advanced Prompting Techniques

➢ Zero-shot, one-shot, and few-shot prompting
➢ Step-by-step reasoning and thinking models
➢ Prompt chaining: breaking complex tasks into stages
➢ Role-playing, personas, and expert simulation
➢ Self-review, critique, and verification prompts
➢ Prompt templates, variables, and building a personal prompt library
➢ Prompt safety: avoiding sensitive data and prompt injection basics

Module 6: Custom Assistants, Projects and Reusable Workflows

➢ Projects and workspaces: organizing knowledge and chats
➢ Custom GPTs, Claude Projects, and Gemini Gems
➢ Writing system instructions and uploading knowledge files
➢ Designing assistants for specific roles: tutor, analyst, writer support agent
➢ Sharing assistants with teams and managing versions
➢ Hands-on: build a custom assistant for your own field

Module 7: AI for Research and Learning

➢ AI-powered search and answer engines: Perplexity, Gemini, and ChatGPT search
➢ Deep research tools and generating sourced reports
➢ NotebookLM and document-based research: summaries, study guides, and audio overviews
➢ Reading and summarizing papers, books, and long reports
➢ Fact-checking, source verification, and spotting fabricated citations
➢ AI as a personal tutor: learning plans, quizzes, flashcards, and explanations at any level
➢ Translation and cross-language research

Module 8: AI for Writing and Business Communication

➢ Drafting emails, reports, proposals, and policies
➢ Editing, proofreading, rewriting, and tone adjustment
➢ Summarizing meetings and generating minutes and action items
➢ Writing CVs, cover letters, and professional profiles
➢ Marketing and social media content creation
➢ AI inside Microsoft 365 and Google Workspace: Copilot and Gemini
➢ Maintaining your own voice and quality control for AI-written text

Module 9: AI for Spreadsheets and Data Analysis

➢ Using AI to write and explain Excel and Google Sheets formulas
➢ Data cleaning, formatting, and restructuring with AI
➢ Uploading datasets for analysis: trends, summaries, and insights
➢ Creating charts and visualizations with AI
➢ Copilot in Excel and Gemini in Sheets
➢ Introduction to AI-assisted dashboards and reporting
➢ Checking AI analysis for accuracy and avoiding misleading conclusions

Module 10: AI for Presentations and Documents Design

➢ Generating slide decks from an outline or a document: Gamma, Copilot in PowerPoint, Canva, and others
➢ Structuring a story and key messages with AI
➢ Designing professional layouts, infographics, and one-pagers
➢ Creating branded templates and consistent visuals
➢ Converting documents between formats and repurposing content
➢ Reviewing, polishing, and presenting AI-generated material

Module 11: AI Image Generation and Editing

➢ How image generation models work
➢ Text-to-image tools: Midjourney, DALL·E / ChatGPT Images, Adobe Firefly, Gemini, and others
➢ Writing effective image prompts: subject, style, lighting, composition, and aspect ratio
➢ Editing existing images: background removal, retouching, object replacement, and upscaling
➢ Creating logos, product mockups, social media graphics, and illustrations
➢ Maintaining consistency and brand identity across images
➢ Licensing, copyright, and commercial use considerations

Module 12: AI for Audio and Video

➢ Speech-to-text: transcription and subtitles
➢ Text-to-speech and voice generation: ElevenLabs and similar tools
➢ Podcast and audio content creation and enhancement
➢ Text-to-video and image-to-video tools: Runway, Veo, Sora, Kling, and others
➢ AI avatars and presenters: HeyGen and Synthesia
➢ AI-assisted video editing: CapCut, Descript, and auto-captioning
➢ Scripting, storyboarding, and producing a short video end to end
➢ Deepfakes, consent, and disclosure of AI-generated media

Module 13: Workflow Automation with AI

➢ Identifying repetitive tasks suitable for automation
➢ Automation platforms overview: Zapier, Make, and n8n
➢ Triggers, actions, and data mapping
➢ Connecting AI models to email, spreadsheets, forms, calendars, and chat apps
➢ Building automated workflows: lead capture, document processing, reporting, and notifications
➢ Testing, monitoring, and error handling
➢ Cost and reliability considerations

Module 14: AI Agents and Building with AI

➢ What are AI agents? Assistants vs. agents
➢ Agentic tools: browsing agents, computer-use agents, and deep research agents
➢ Model Context Protocol (MCP) and connecting AI to your apps and data
➢ Vibe coding: building websites, tools, and simple apps from natural-language descriptions
➢ Tools for builders: Claude Code, Cursor, GitHub Copilot, Lovable, and Bolt
➢ Reading, explaining, and debugging code with AI, even without a programming background
➢ Hands-on: build and publish a small working tool or landing page

Module 15: Responsible AI: Ethics, Privacy and Security

➢ Bias, fairness, and transparency in AI systems
➢ Data privacy: what you should never paste into an AI tool
➢ Confidentiality, client data, and organizational AI policies
➢ Copyright, intellectual property, and ownership of AI outputs
➢ Misinformation, deepfakes, and scams powered by AI
➢ Security risks: prompt injection, data leakage, and account safety
➢ AI regulation and emerging standards
➢ Environmental impact and responsible use of AI

Module 16: Capstone Project and Personal AI Strategy

➢ Selecting a real project from your own field or workplace
➢ Planning the solution and choosing the right tools
➢ Implementing the project end to end: content, data, visuals, and automation
➢ Measuring time saved and quality gained
➢ Presenting the final project
➢ Building your personal AI adoption roadmap and continuous-learning plan