Topic outline

  • Objectives

    1. Recognise your understanding of deep learning and neural networks.

    2. Assess proficiency in computer vision and image recognition.

    3.Showcase the ability to implement AI solutions effectively.

    4. Validate knowledge of AI deployment and scalability.

    5. Assess comprehension of AI's impact on privacy.

    6. Demonstrate proficiency in AI project management.

    7. Showcase the ability to optimize AI algorithms

    8. Validate understanding of AI's role in automation.

    9. Assess comprehension of AI interpretability and explainability.

    • Syllabus

      1. The AI uprising: Trends, Tools, and Applications:

      • AI is important in today's business.
      • AI, machine learning, and deep learning fundamentals.
      • AI implementation and challenges.

      2. Customer experience and AI:

      • Customer experience (CxDNA) model for AI implementation
      • Use of AI to create demand, enable sales, and drive customer service.
      • Analyze customer segments and conversion rate optimization.

      3. Operation Management with AI:

      • How AI can be used to optimize your operating processes to increase agility, reduce costs, and enhance quality.
      • AI in the Ecosystem of Operations: Sourcing, Manufacturing, Storing, Routing, and Delivering Goods.

      4. AI for Business Support Functions:

      • AI for business support functions like Human Resource Management, Financial Management, IT Systems Management, and Risk Management.
      • AI-driven candidate screening.
      • AI-driven collections management.
      • AI-driven code development.
      • AI for fraud prevention.

      5. AI for different industries (Casestudies):

      • AI for Travel and Tourism.
      • AI for Healthcare.
      • AI for Automobiles.
      • AI for Banking.

      • Benefits

        • Establishes a strong foundation for advanced AI certifications.
        •  Enhances problem-solving skills with AI techniques.
        •  Improves understanding of AI's business applications.
        •  Increases employability in AI-driven organizations.
        •  Equips with practical knowledge of AI implementation.
        •  Enhances ability to contribute to AI-driven projects.
        •  Strengthens analytical skills for AI decision-making.
        •  Provides a competitive edge in data-driven industries.
        •  Boosts confidence in working with AI technologies.
        •  Enables effective collaboration with AI specialists.