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This three-day AI Readiness Program equips participants with practical knowledge and hands-on experience across the AI landscape. Starting with foundational concepts — AI, machine learning, deep learning, and how large language models work — the program quickly moves into real-world application. Participants will explore leading AI platforms including ChatGPT, Claude, Gemini, and Perplexity, as well as creative tools like RunwayML, Gamma, and Canva Pro. The program covers prompt engineering, AI-powered coding tools, app builders, and automation frameworks. Day three addresses advanced topics including running local models, APIs, AI agents, meeting AI tools, and the critical dimensions of AI ethics and governance. Each session features hands-on exercises, and the program culminates in a capstone project where teams build a fictional business using AI tools — from business plan to pitch deck.
Capital Market
Insurance
Financing
Artificial Intelligence and Data Management
Not Exist
Lecture
Case Studies +3
Lecture
Case Studies
Brainstroming
Practical Implementation
Dialogue and Discussions
Pre Assessment
Financial sector professi...
Managers and team leaders...
Any professional looking ...
Financial sector professionals seeking to understand and apply AI tools
Managers and team leaders responsible for digital transformation initiatives Managers and team leaders responsible for digital transformation initiatives
Any professional looking to build practical AI skills regardless of technical background
This provides you with the opportunity to select the available times that suit you best for participation in our program. These times represent slots during which we are ready to welcome you and provide assistance and guidance.
In Class Training
Core concepts: AI vs. Machine Learning vs. Deep Learning — definitions, differences, and real-world examples
Debate: Where is AI heading? Opportunities, risks, and societal impact.
Hands-on: Using ChatGPT and Perplexity for research, writing, and problem-solving.
How LLMs work: Tokens, training data, fine-tuning, and inference.
Arabic language AI: Capabilities and current limitations.
Voice AI and music generation tools.
Prompt engineering: Techniques for getting better results (zero-shot, few-shot, chain-of-thought, and role-based prompts).
AI pricing models: Subscription vs. token-based pricing.
Hands-on: Building Custom GPTs for specific use cases.
In Class Training
Model comparison: ChatGPT vs. Claude vs. Gemini vs. Grok — capabilities, strengths, and best use cases.
Deep dive: Perplexity Labs, Grok, Claude Desktop, Microsoft Copilot, and NotebookLM.
أدوات الذكاء الاصطناعي الإبداعية: RunwayML وGamma وCanva Pro وVeo.
AI-powered coding tools: Cursor, GitHub Copilot, and Replicate.
No-code app builders: Bolt.new, Lovable, Firebase Studio, and Manus.
Hands-on: Model comparison exercises — same prompt across multiple platforms.
Group challenge: Teams select and demonstrate an AI tool for a specific business problem.
In Class Training
Running local AI models: Ollama and GPT4All — benefits, setup, and privacy advantages.
APIs and Groq: Understanding AI APIs, fast inference, and integration patterns.
Hugging Face: Exploring open-source models and model repositories.
Automation and AI agents: n8n workflows, Model Context Protocol (MCP), and Agent-to-Agent (A2A) communication.
AI ethics and governance: Bias, transparency, responsible use, organizational policies, and regulatory considerations.
Post-test assessment.
Capstone project (1.5 hours): Teams build a fictional business using AI tools, including a business plan, competitor analysis, brochure, pitch deck, and bonus website.
Understand the core concepts of AI, machine learning, deep learning, and how large language models (LLMs) work including tokens, training, and inference.
Use leading AI platforms (ChatGPT, Claude, Gemini, Perplexity, Grok) and apply prompt engineering techniques to achieve effective results.
Explore and evaluate creative AI tools, AI-powered coding assistants, and no-code app builders for practical use cases
Run local AI models, use APIs, and build automation workflows using AI agents and integration frameworks.
Apply AI ethics and governance principles and develop integrated business solutions using AI tools in a capstone project.
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