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    إدارة تقنية المعلومات
    20014

    Generative Artificial Intelligence

    29-11 To 03-12-2026
    Dubai
    it mgmt

    A practical, tool-agnostic program covering core models (LLMs, diffusion, transformers), prompt and workflow design, retrieval-augmented generation, lightweight fine-tuning, evaluation, and governance. Participants build hands-on skills to integrate gen-AI into day-to-day processes while managing risk, cost, and change.

    Date :
    From 29 Nov. Till 03 Dec. 2026
    City :
    Dubai
    Fees :
    4500
    • Date City Fees
    Date :
    From 29 Nov. Till 03 Dec. 2026
    City :
    Dubai
    Fees :
    4500
    • Date City Fees

    Overview

    Enable professionals to design, use, and govern generative AI safely and effectively—turning prompts, data, and workflows into reliable outcomes and measurable business value.

    A practical, tool-agnostic program covering core models (LLMs, diffusion, transformers), prompt and workflow design, retrieval-augmented generation, lightweight fine-tuning, evaluation, and governance. Participants build hands-on skills to integrate gen-AI into day-to-day processes while managing risk, cost, and change.

    Who Should Attend

    Target Group

    • Product, operations, and service leaders looking to deploy gen-AI
    • Data, analytics, and automation practitioners
    • Solution architects, software engineers, and citizen developers
    • Compliance, risk, security, and governance partners
    • Learning, communications, and support teams adopting AI in workflows
    • Understand how generative models work and where they add value in real processes
    • Design prompts, chains, and agent workflows that are reproducible and auditable
    • Apply retrieval-augmented generation with clean data pipelines and guardrails
    • Use adaptation methods (fine-tuning, instruction tuning, adapters) for domain tasks
    • Evaluate quality, safety, and cost with clear metrics and test sets
    • Establish governance for privacy, security, IP, bias, and change management
    • Use-case selection and value framing for gen-AI
    • Prompt engineering, chaining, and agent design
    • RAG pipelines, data readiness, and guardrails
    • Adaptation approaches and product integration
    • Evaluation design, safety practices, and governance setup

    Foundations of Generative AI

  • Model families and use-cases: LLMs, diffusion, transformers; strengths and limits
  • From input to output: tokenization, context windows, temperature, decoding strategies
  • Capability map: text, code, images, structured outputs, and tool use
  • Risks landscape: hallucinations, leakage, bias, prompt injection
  • Value framing: pick the right use-case with ROI, risk, and feasibility signals

    • Prompt Engineering & Workflow Design

  • Prompt patterns: role/task context, constraints, examples, evaluation rubrics
  • Structured outputs: JSON schemas, validation, and post-processing
  • Multi-step chains: summarization → planning → generation → QA
  • Agents and tools: calling search, databases, or internal APIs safely
  • Ops hygiene: prompt versioning, test cases, and replayable runs

    • Contact Us

    For each learning and development project we establish strong relationships and effective communication with partners.
    Don't hesitate to contact us.