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AI Fundamentals for Business Leaders


AI Fundamentals for Business Leaders Book

Introducing "Artificial Intelligence Fundamentals for Business Leaders" - the perfect guide to help non-technical business leaders understand the power of AI. Completely up to date with the latest advancements in generative AI.

Part of the Byte-sized Learning series, these books break down complex concepts into easily digestible pieces, providing you with a solid foundation in the fundamentals of AI.

More Than a Book

By purchasing this book, you will also be granted access to the AI Academy platform. There you can test your knowledge through end-of-chapter quizzes and engage in discussion with other readers.

You will also receive 50% discount toward the enrollment in the self-paced course of the same name and enjoy video summary lessons, instructor-graded assignments, and live sessions. A course certificate will be awarded upon successful completion.

The perfect gift for someone you love!

AI Fundamentals for Business Leaders Audiobook


Introduction to Artificial Intelligence
Learning Objectives: 
Demonstrated comprehension of AI's evolution, definition, applications, and comparison with human intelligence.

  1. Innovate and Adapt, Faster!
  2. AI and the Transformation of the Global Business Landscape
  3. What is Artificial Intelligence?
  4. Human Intelligence Versus Machine Intelligence
  5. Current and Emerging Applications
  6. Computational Power
All About Data
Learning Objectives: 
Clear understanding of the significance of data, and strategies for data management.

  1. Big Data
  2. Data Science Versus Machine Learning
  3. Harnessing Data for Machine Learning: Strategies and Challenges
  4. Proprietary Data as a Competitive Advantage
  5. Open Data and Data Sharing
  6. The New Era of Generative AI: Understanding the Data Management Implications
Machine Learning for Business Leaders
Learning Objectives: 
Familiarity with machine learning algorithms, and different learning types.

  1. Why Business Leaders Must Understand Machine Learning
  2. Expert Systems
  3. Machine Learning
  4. Supervised Learning
  5. Unsupervised Learning
  6. Self-Supervised Learning - Bridging the Gap
  7. Reinforcement Learning
  8. Reinforcement Learning from Human Feedback (RLHF): Enhancing AI Models with Human Input
Stepping-Stone Models and Concepts - Non-Technical Overview
Learning Objectives: 
Demonstrated comprehension of parametric and non-parametric algorithms.

  1. Parametric And Non-Parametric Algorithms
  2. Linear Regression
  3. Logistic Regression
  4. Decision Trees
  5.  Ensemble Methods
  6. K-Means Clustering
  7. Key Steps of a Machine Learning Project
Deep Learning for Business Leaders
Learning Objectives: 
Understanding of deep learning, its basics, and the structure and types of neural networks, and the key steps involved in a machine learning project.

  1. Introduction to Deep Learning
  2. Neurons
  3. The Perceptron
  4. Training a Neuron
  5.  Neural Networks
  6. Basic Types of Neural Networks
Model Selection and Evaluation - Business Decision-Making
Learning Objectives: 
Ability to select and evaluate machine learning models and utilize them for decision-making.

  1. Model Selection
  2. The Unreasonable Effectiveness of Quality Data
  3. Model Evaluation
  4. Outputs Versus Outcomes
  5. Enhancing Decision-Making with Machine Learning
Generative AI For Business Leaders
Learning Objectives: 
Detailed understanding of generative AI, its value chain, transformer models, diffusion models, and governance challenges.

  1. Introduction to Generative AI
  2. Transformer Models
  3. Transformers: The Near Future
  4. Generative Adversarial Networks
  5. Diffusion Models
  6. Foundation Models
  7. The Generative AI Value Chain
  8. Training GPT Assistants and the Art of Prompting
  9. Prompt Strategies
  10. Regulating and Governing Generative AI: A Case Study of the European Union
AI Opportunities and Challenges for Your Business or Industry
Learning Objectives:       
To analyze the opportunities and challenges posed by the integration of Generative AI technologies in your business operations, and to design an initial strategic response to these insights. You can work on a real or imagined business.
End-of-chapter quizzes to check your knowledge as you read the book
About the Author: Inês Almeida
Inês Almeida

Inês Almeida

Inês is the Chief Transformation Officer at Now Next Later AI, an AI advisory, training, and publishing business supporting organizations with their AI strategy, transformation, and governance. She is a strong proponent of human-centered, rights-respecting, responsible AI development and adoption. Ignoring both hype and fear, she provides a balanced perspective grounded in scientific research, validated business outcomes and ethics.

With a wealth of experience spanning over 26 years, Inês held senior positions at companies such as Thoughtworks, Salesforce, and Publicis Sapient, where she advised hundreds of executive customers on digital- and technology-enabled Business Strategy and Transformation. Inês serves as an AI advisory member in the Adelaide Institute of Higher Education Course Advisory Committee.

Inês is the author of several books, including three AI guides with a clear aim to provide an independent, balanced and responsible perspective on Generative AI business adoption. She is a regular speaker at industry events such as Gartner Symposium, SXSW, and ADAPT. Her latest books show her extensive knowledge and insights, displaying her unique perspective and invaluable contributions to the field.

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