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Find a path to becoming a AI Project Manager. Learn more at:
OpenCourser.com/career/uh0lwu/ai
Reading list
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Written by a leading expert in AI, this book offers strategic insights and technical guidance for AI project implementation. Provides a roadmap for navigating the challenges and complexities of real-world AI projects.
A timely and important book that makes the case for using AI for social good. The book includes a series of concrete recommendations for how AI can be used to address the world's most pressing problems.
An introduction to the numerous social challenges that AI can help solve, including climate change, poverty, and healthcare access. The book is written by a professor at the University of Illinois who leading researcher in the field.
A forward-looking exploration of the potential of AI for social good. The book includes essays from leading AI researchers on the most promising areas for future research and development.
A comprehensive overview of the ways that AI is being used to solve social problems, such as poverty, hunger, and homelessness. The book includes case studies of real-world applications, such as using AI to predict natural disasters and target aid to those who need it most.
A comprehensive guide to machine learning using Python. Covers various aspects of AI project implementation, including data preprocessing, feature engineering, and model evaluation.
Provides a practical approach to AI project implementation using popular Python libraries. Includes hands-on exercises and real-world examples to reinforce learning.
Focuses on the implementation aspects of machine learning projects. It covers a variety of topics, including data collection, feature engineering, and model selection.
Focuses on practical AI project implementation, particularly for coders and software developers. Provides a hands-on approach to building and deploying AI models.
Provides a comprehensive guide to AI project implementation using Python. Covers various aspects of AI, including data preparation, model training, and deployment.
Written by the creator of Keras, this book provides a practical guide to deep learning using Python. Covers various aspects of AI project implementation, including model architecture, training techniques, and deployment.
A comprehensive overview of the ways that AI is being used to improve healthcare. The book includes case studies of real-world applications, such as using AI to diagnose disease and develop new treatments.
A passionate call to action for using AI to solve the world's biggest problems. The book includes stories of real-world AI applications that are making a positive impact.
A comprehensive resource guide on the use of AI for social good in developing countries. The book includes case studies of real-world applications, such as using AI to improve agricultural yields and reduce poverty.
Provides a conceptual understanding of AI algorithms and their implementation. Suitable for beginners or those seeking a strong foundation in AI concepts.
A concise introduction to the key concepts of AI and its potential applications for social good. The book is written by a professor at the University of Oxford who leading researcher in the field.
Provides a step-by-step guide to implementing AI projects. It covers a variety of topics, including data collection, model training, and evaluation.
For more information about how these books relate to this course, visit:
OpenCourser.com/career/uh0lwu/ai
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Bars indicate relevance. All salaries presented are estimates. Completion of this course does not guarantee or imply job placement or career outcomes.
