Fractal Analytics
Leadership Strategies for AI and Generative AI Specialization
Fractal Analytics

Leadership Strategies for AI and Generative AI Specialization

AI Adoption Strategies for Business Leaders. A CEO' Perspective for AI Adoption and Generative AI Implementation

Sray Agarwal
Rasesh Shah
Fractal Analytics

Instructors: Sray Agarwal

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4.8

(15 reviews)

Beginner level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.8

(15 reviews)

Beginner level

Recommended experience

1 month
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Evaluate potential applications of generative AI across diverse business domains.

  • Integrate generative AI into business operations effectively, considering data privacy and ethical implications.

  • Establish KPIs, interpret data-driven insights, and devise optimization strategies for generative AI initiatives.

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Taught in English
Recently updated!

May 2024

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Specialization - 4 course series

Generative AI for Business - A Leaders' Handbook

Course 18 hours4.7 (16 ratings)

What you'll learn

  • The definition and distinguishing features of generative AI and explore the core concepts of generative models including GANs and VAEs.

  • Comprehend the role of data and training in generating new content using Generative AI models.

  • Recognize and evaluate the potential applications of generative AI across various business domains and identify areas where it can add value.

  • Strategic framework for integrating GenAI into business operations, with data privacy, ethical implications, and potential risks at the center.

Skills you'll gain

Category: business solution
Category: Corporate Strategy

What you'll learn

  • Explain key components for driving desired outcomes from AI

  • Explain strategies for error reduction and accuracy improvement in AI

  • Gain insights into optimizing organizational effectiveness in AI adoption

Skills you'll gain

Category: Organizational Development
Category: AI Adoption
Category: Ethical and Responsible AI

Responsible AI - Principles and Ethical Considerations

Course 39 hours4.4 (11 ratings)

What you'll learn

  • Discuss responsible AI principles and their significance in technology, including ethical considerations, fairness, transparency, and accountability.

  • Apply techniques to identify, address, and mitigate bias in AI algorithms and data, promoting fairness and inclusivity in AI systems.

  • Interpret and explain AI decisions, balancing accuracy and explainability to foster trust and accountability in AI systems.

  • Discuss accountability, ethical AI governance, privacy considerations, security measures in the development & deployment of responsible AI systems.

Skills you'll gain

Category: responsible AI
Category: Critical Thinking
Category: Complex Problem Solving
Category: Data Ethics
Category: Data Principles

Structured Approach to Problem Solving

Course 415 hours4.8 (70 ratings)

What you'll learn

  • Explain the lifecycle of DS project and role of structured thinking in DS project.

  • Define a problem statement using the SMART framework. Explain the activities, best practices, and pitfalls in the implementation phase.

  • Construct MECE issue tree to break-down business problems into parts. Create a problem statement worksheet to scope business problems.

  • Explain the role of human centered design during solutioning of business problems.

Skills you'll gain

Category: Critical Thinking
Category: structured thinking
Category: Problem Solving
Category: Human Centric Design
Category: problem statement

Instructors

Sray Agarwal
Fractal Analytics
1 Course790 learners

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