Fractal Analytics
Leadership Strategies for AI and Generative AI Specialization
1,744 enrolled
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

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(32 reviews)

Beginner level

Recommended experience

Flexible schedule
1 month at 10 hours a week
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Share your expertise with employers
Get in-depth knowledge of a subject

(32 reviews)

Beginner level

Recommended experience

Flexible schedule
1 month at 10 hours a week
Earn a career credential
Share your expertise with employers

Overview

  • 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.

What’s included

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Taught in English
41 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Fractal Analytics

Specialization - 4 course series

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: Key Performance Indicators (KPIs)
Category: Generative AI
Category: Data Ethics
Category: Business Technologies
Category: Corporate Strategy
Category: Strategic Leadership
Category: Business Ethics
Category: Business Leadership
Category: Business Strategy
Category: Business Transformation
Category: Artificial Intelligence

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: Data Quality
Category: Design Thinking
Category: Ethical Standards And Conduct
Category: Governance
Category: Strategic Decision-Making
Category: Artificial Intelligence
Category: Business Strategy
Category: Data Pipelines
Category: Organizational Effectiveness
Category: Business Transformation
Category: Goal Setting
Category: Data Governance
Category: Human Centered Design
Category: Organizational Development
Category: Technology Strategies
Category: Data Strategy
Category: Organizational Strategy
Category: Strategic Leadership

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: Ethical Standards And Conduct
Category: Data Ethics
Category: Data Governance
Category: Information Privacy
Category: Governance
Category: Complex Problem Solving
Category: Machine Learning
Category: Algorithms
Category: Personally Identifiable Information
Category: Data Security
Category: Law, Regulation, and Compliance
Category: Continuous Monitoring
Category: Mitigation
Category: Artificial Intelligence
Category: Data Integrity
Category: Critical Thinking

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: Complex Problem Solving
Category: Human Centered Design
Category: Analytical Skills
Category: Problem Solving
Category: Problem Management
Category: Design Thinking
Category: Project Management Life Cycle
Category: User Centered Design
Category: Business Analysis
Category: Data Science
Category: Critical Thinking

Earn a career certificate

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Instructors

Sray Agarwal
Fractal Analytics
1 Course1,287 learners
Rasesh Shah
Fractal Analytics
1 Course2,137 learners
Fractal Analytics Academy
Fractal Analytics
21 Courses93,747 learners

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