Top 10 Artificial Intelligence Books For Beginners in 2024

Top 10 Artificial Intelligence Books For Beginners in 2024



In today’s rapidly evolving world, the significance of Artificial Intelligence (AI) is hard to ignore. From powering voice assistants to driving innovations in various industries, AI has become an integral part of our daily lives. Amidst these changes, the business world is amplifying its commitment to AI and machine learning, with a substantial 63% of companies planning to either increase or maintain their spending on these technologies in 2023. As the interest in AI continues to grow, there’s a parallel surge in the demand for reliable resources that cater to beginners eager to understand this transformative technology.

This article aims to serve as a roadmap for individuals venturing into the realm of AI, providing a curated list of the top 10 Artificial Intelligence books for beginners in 2024. Whether you’re a tech enthusiast or a novice, these recommended reads will pave the way for a comprehensive understanding of AI concepts and applications.

The Importance of Foundational Knowledge

Understanding artificial intelligence (AI) begins with establishing a solid foundation. Books play a crucial role in providing beginners with the essential knowledge required to comprehend AI concepts. These resources delve into the basics, offering insights into fundamental AI principles and their real-world applications.

However, theoretical knowledge alone isn’t sufficient for mastery in AI. Practical, hands-on experience is crucial for bridging the gap between theory and real-world application. For example, understanding how to implement machine learning algorithms in real-world situations is a key aspect of mastering AI. Practical courses enable learners to take theoretical knowledge and apply it in practical, problem-solving contexts.

Top 10 AI Books for Beginners

“Artificial Intelligence: A Guide for Thinking Humans” by Melanie Mitchell

Key Takeaways: Mitchell offers a relatable exploration of AI’s history and core concepts using analogies that resonate with readers of all backgrounds. This book serves as a robust foundation for understanding AI’s societal influences.

Limitations: While comprehensive, it may not delve into the technical depths required for advanced learning in AI.

“Automate This: How Algorithms Came to Rule Our World” by Christopher Steiner

Key Takeaways: Steiner’s narrative on the rise of algorithms paints a vivid picture of AI’s transformative role in finance and healthcare, among other sectors, making it captivating for beginners.

Limitations: The book’s focus on storytelling may limit detailed technical insights into algorithm development.

“AI Superpowers: China, Silicon Valley, and the New World Order” by Kai-Fu Lee

Key Takeaways: Lee provides a unique geopolitical lens on the AI race, ideal for understanding the global landscape and job market implications of AI.

Limitations: It may not cover the hands-on skills needed to implement AI solutions.

“The Hundred-Page Machine Learning Book” by Andriy Burkov

Key Takeaways: Burkov’s succinct work is a practical intro to machine learning, complete with algorithm discussions and code examples—a quick yet thorough guide for the uninitiated.

Limitations: Its brevity might skip over the complexity of some concepts that a more extensive guide could cover.

“Machine Learning for Dummies” by John Paul Mueller and Luca Massaron

Key Takeaways: This entry in the “For Dummies” series demystifies AI jargon and algorithms, proving an accessible starting point for newcomers.

Limitations: The simplification necessary for accessibility may not satisfy those looking for in-depth technical discussions.

“Python: Beginner’s Guide to Artificial Intelligence” by Amir Ziai, Denis Rothman, Rahul Kumar, Abhishek Nagaraja, Ankit Dixit, Matthew Lamons

Key Takeaways: This book is a resourceful guide for gaining practical knowledge in machine learning, deep learning, and data analysis, using Python and TensorFlow. It’s structured to apply AI skills to real-world projects.

Limitations: The content may require some basic understanding of Python, which might not be ideal for absolute beginners.

“Python: Advanced Guide to Artificial Intelligence” by Armando Fandango, Giuseppe Bonaccorso, and Rajalingappaa Shanmugamani

Key Takeaways: This advanced guide covers machine learning algorithms and techniques like object classification and detection using Python, offering a deep dive into TensorFlow’s features.

Limitations: Its advanced level may be challenging for readers without a foundational understanding of AI.

“Artificial Intelligence By Example” by Denis Rothman

Key Takeaways: The book presents AI through real-life scenarios, exploring advanced machine learning models and their application to Blockchain and IoT.

Limitations: It assumes prior experience with Python and statistics, which might not suit all beginners.

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“Artificial Intelligence Basics: A Non-Technical Introduction” by Tom Taulli

Key Takeaways: This book offers a non-technical introduction to AI concepts like machine learning and robotics, addressing the future impact of AI on society.

Limitations: May not cover the technical details desired by those who wish to delve into the programming aspects of AI.

“A First Course in Artificial Intelligence” by Osondu Oguike

Key Takeaways: An introductory book that explores problem-solving strategies in AI, with a focus on knowledge-based agent design and algorithmic foundations.

Limitations: Its focus on introductory content might not fully satisfy readers looking for comprehensive, advanced topics.

Limitations of Learning from Books Alone

Theory Vs Practical Experience

Books on AI, such as “AI books for beginners”, primarily focus on theoretical concepts, but AI’s evolving nature demands practical skills. For example, generative AI, a key trend in 2024, involves intricate skills like automated code generation and debugging, which are better learned through application rather than theory​​.

Real-World Application Gap

AI books often lack the nuances of real-world scenarios. The transition from generative AI tools with specific capabilities to multi-modal systems integrating text, visuals, and audio exemplifies a complexity that can be challenging to grasp without hands-on experience​​.

Evolving Legal and Ethical Landscape

The rapidly changing legal and ethical landscape of AI, like the development of international frameworks for safe AI deployment, is a dynamic subject that books might not fully capture in real-time​​.

Financial Burden

The financial aspect further compounds the challenges associated with relying solely on AI books for learning. Books, often expensive, necessitate a substantial investment, particularly considering that comprehensive AI knowledge may require purchasing multiple volumes. This financial burden can be a deterrent for individuals seeking cost-effective and efficient learning resources. Contrary to this, our artificial intelligence guide can serve as the one-stop solution for you to know the how and why of AI for free.

Technological Advancements

Quantum AI, a significant advancement in 2024, represents a leap in AI capabilities. Learning about such technologies through books might not provide the practical understanding necessary for applying these concepts in fields like drug discovery or climate change modeling.

Limited Scope of Books

While books offer foundational knowledge, they often can’t keep pace with AI’s rapid advancements. For instance, the complex legal challenges surrounding AI-generated content, such as copyright issues, are areas where books may provide outdated information due to the fast-evolving nature of these issues​​.

Lack of Interactivity and Personalization

Books lack interactive elements that facilitate experiential learning. Unlike structured courses or hands-on workshops, books can’t adapt to individual learning styles or provide real-time feedback, which is crucial for understanding complex AI concepts and their applications.

Limited Exposure to Diverse Perspectives

Books on AI, even the best ones for beginners, typically present a singular viewpoint. AI, being a multifaceted field, benefits from exposure to diverse perspectives and case studies, which books may not adequately cover. Engaging with a variety of resources, including courses and practical workshops, can provide a more well-rounded understanding.

Lack of Professional Development

Contrary to the common belief that acquiring a multitude of books equates to expertise, it’s crucial to recognize that possessing an extensive collection of AI literature does not inherently translate to practical proficiency. Simply reading books won’t suffice in proving one’s expertise or securing a job in the competitive landscape of AI. Ultimately you need expert help to land a high-paying AI job.

The reality is that the job market values practical skills and tangible accomplishments over a mere accumulation of theoretical knowledge. In the dynamic field of artificial intelligence, where advancements occur swiftly, employers seek individuals who can apply their understanding to real-world scenarios.

Moreover, books alone, regardless of their quality, lack the ability to grant the recognized certifications often demanded by employers. Renowned certifications hold significant weight in the job market, validating an individual’s expertise and practical capabilities in AI. These certifications serve as a credible testament to one’s proficiency, bridging the gap between theoretical knowledge and practical application.

While books on artificial intelligence provide a solid theoretical foundation, they have limitations in terms of keeping up with rapid technological advancements, offering practical experience, and adapting to the learner’s needs. This underscores the importance of complimenting book learning with practical, interactive, and up-to-date courses like those offered by the Blockchain Council.

The Importance of Practical Skills

  • Bridging Theory and Practice: While AI books for beginners cover theoretical aspects, real-world case studies demonstrate the practical application of these theories. For instance, AI’s role in predictive analytics in project management highlights how theoretical knowledge is applied in real-world scenarios, a perspective often not fully captured in books​​.
  • Learning from Real-World Challenges: Case studies provide insight into the challenges and solutions encountered in actual AI implementations. For example, the integration of multi-modal AI systems in various domains showcases the practical challenges and innovative solutions that books may not fully explore​​.
  • Understanding the Ethical Implications: Real-world examples help understand AI’s ethical and legal implications. The evolving frameworks around safe AI, like the Bletchley Declaration, illustrate the practical considerations in ethical AI deployment, which are better understood through case studies rather than theoretical explanations​​.
  • Staying Updated with Latest Trends: Case studies reflect the latest trends in AI, such as the applications of Quantum AI in different industries. They provide up-to-date knowledge on how these advanced technologies are being used in the real world, which is crucial for staying current in this rapidly evolving field​​.

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The Role of Certification Courses in AI Learning

As you dive into the extensive knowledge provided by these top 10 artificial intelligence books, it’s essential to pair theoretical understanding with practical skills. Artificial Intelligence certifications by the Blockchain Council can serve as a powerful complement to your book knowledge, offering a structured pathway to validate and apply what you’ve learned. Here are the best AI certifications for beginners that require no technical knowledge:

Certified Chatbot Expert™

Explore the world of chatbot development with the Certified Chatbot Expert™ program. This certification not only covers the design and components of chatbots but also provides hands-on experience in natural language processing in Python. Consider this certification as a practical extension of your knowledge gained from AI books. With a focus on natural language processing in Python, this certification can be completed in approximately 6 hours, providing a quick yet thorough exploration of chatbot development.

Certified BARD AI Expert

The Certified BARD AI Expert program offers comprehensive knowledge of BARD AI and its applications. Through hands-on experiences, you can master the art of creating content with this generative AI technology. Think of this certification as a practical bridge between theoretical understanding and creative content generation explored in AI books. With a duration of around 5 hours, this certification combines theoretical knowledge with hands-on experiences, allowing you to master the art of creating imaginative content using generative AI technology.

Certified Generative AI Expert™

Stay at the forefront of technological innovation with the Certified Generative AI Expert™ program. This certification delves into generative models, neural networks, and advanced machine learning techniques. The hands-on experience provided will empower you to create AI systems that generate imaginative outputs, aligning seamlessly with the creative aspects discussed in AI books. With a duration of approximately 7 hours, this certification provides a comprehensive exploration of AI-driven creativity, allowing you to create imaginative and innovative outputs.

Certified ChatGPT Expert

Unleash the potential of AI with the Certified ChatGPT Expert Certification program. This certification focuses on the innovative natural language processing capabilities of ChatGPT. Consider it a practical avenue to apply the knowledge gained from AI books in the context of language processing tools and their applications. with a duration of around 7 hours, this certification equips you with the knowledge and skills to harness the potential of this groundbreaking AI tool in various sectors, including customer service, marketing, advertising, and healthcare.

Certified Artificial Intelligence (AI) Expert™

The Certified Artificial Intelligence (AI) Expert™ certification offers a comprehensive learning program covering various AI fields. From statistics to deep learning and regenerative AI like ChatGPT, this certification acts as a broad practical extension of the core ideas discussed in AI books. With a duration of approximately 6 hours, this certification provides beginner-friendly training to introduce learners to core AI concepts.

The best part of these certification programs is, they are self-paced, online and come with a globally recognized lifetime-valid AI certificate that will help you land a high-paying AI job. Further, you can enroll for the interactive live training on AI that allows you to have a one-to-one discussion with an expert in the field and get your doubts resolved. Incorporating these certifications into your AI learning journey can solidify your understanding and provide tangible skills, ensuring a well-rounded and practical approach to artificial intelligence.

Why Should You Consider an AI Certification by the Blockchain Council?

It is necessary to navigate through the pages of the top artificial intelligence books for beginners. While such books are essential to introduce the fundamental theories and concepts of AI, they represent only one side of the AI mastery coin. The other, equally critical side, is the application of this knowledge through hands-on practice—a facet where Blockchain Council’s AI certification programs shine as a perfect complement.

Books on AI, replete with theoretical knowledge, case studies, and historical contexts, allow beginners to familiarize themselves with the terminology and basic frameworks of artificial intelligence. They often explain complex algorithms and ethical considerations in AI, serving as an indispensable resource for anyone new to the field. However, understanding AI’s intricacies from books might not translate into the ability to navigate the practical challenges that arise when AI is applied to real-life problems. This is where Blockchain Council’s certifications step in to fill the gap. 

As a leader in AI education, Blockchain Council is dedicated to empowering individuals with knowledge that goes beyond the surface. With a commitment to fostering a deep understanding of AI, Blockchain Council stands out as a reliable source for quality education in this field. The practical experience provided by these AI courses is not just an add-on but a crucial component of the AI learning ecosystem. By offering artificial intelligence certifications, the Blockchain Council propels learners from theoretical understanding to practical proficiency.

The AI certification courses are designed to build upon the knowledge gained from books, allowing learners to engage with AI tools and platforms actively. For instance, after reading about the possibilities of generative AI, a course on becoming a Certified Generative AI Expert™ can give students the hands-on experience of working with these models, understanding their capabilities, and exploring their creative potential. Similarly, the Certified ChatGPT Expert™ course can turn readers fascinated by conversational AI models into creators of sophisticated chatbots.

By emphasizing the importance of this dual approach, the Blockchain Council ensures that learners are not just consuming information but are also equipped to apply it, thus providing them with a competitive edge in the AI industry. Combining the foundational knowledge from AI books with the Blockchain Council’s immersive AI certification programs can be a game-changing strategy for beginners. It provides a robust, rounded educational experience that prepares them not just to participate in the AI revolution but to lead it.


Embarking on the journey of learning Artificial Intelligence (AI) requires a balanced and comprehensive approach. The rapidly evolving landscape of AI, as highlighted by the generative AI growth, shifting investment trends, and corporate spending patterns, emphasizes the need for a well-rounded understanding of this transformative technology.

As we explored the top 10 Artificial Intelligence books for beginners in 2024, it becomes evident that these resources serve as invaluable guides for individuals stepping into the realm of AI. From foundational concepts to practical applications, these books lay the groundwork for a solid understanding of AI’s nuances and potential impact on various industries. The economic impact of AI is undeniably vast, with the global market size reaching around $207 billion in 2023. And the demand for AI-related skills is on the rise. In the United States, excluding sectors like agriculture, forestry, fishery, and hunting, AI-related job postings increased from 1.7% in 2021 to 1.9% in 2022. 

Take the next step in your AI learning journey by exploring the recommended books and considering the enriched experience offered by Blockchain Council’s AI certifications. Stay ahead of the curve, equip yourself with a robust understanding of AI, and position yourself for success in this ever-evolving technological landscape. The combination of insightful literature and practical education awaits you for a truly holistic AI learning experience.

Frequently Asked Questions

  • The best AI book depends on your level of expertise and specific interests.
  • “Artificial Intelligence: A Guide for Thinking Humans” by Melanie Mitchell is recommended for a broad exploration of AI history and core concepts.
  • “Automate This: How Algorithms Came to Rule Our World” by Christopher Steiner is captivating for beginners, offering insights into AI’s transformative role in various sectors.
  • “The Hundred-Page Machine Learning Book” by Andriy Burkov is a practical intro to machine learning, suitable for those looking for a quick yet thorough guide.
  • “Python: Beginner’s Guide to Artificial Intelligence” by Amir Ziai and team is resourceful for gaining practical knowledge in machine learning, deep learning, and data analysis using Python and TensorFlow.
  • Start with foundational books like “Artificial Intelligence: A Guide for Thinking Humans” and “Automate This” for a broad understanding of AI concepts.
  • Progress to more technical books like “The Hundred-Page Machine Learning Book” for practical insights into machine learning algorithms.
  • Explore specialized books based on your interests, such as “Python: Beginner’s Guide to Artificial Intelligence” for hands-on experience with AI in Python.
  • Begin by understanding foundational AI concepts through introductory books and online resources.
  • Dive into more technical aspects with books like “The Hundred-Page Machine Learning Book” and online courses offering hands-on experience.
  • Stay updated with the latest trends by reading industry reports, research papers, and following reputable AI blogs.
  • Consider enrolling in AI certification programs, like those offered by Blockchain Council, to gain practical skills and validate your knowledge.
  • The best AI certification depends on your specific goals and areas of interest within AI.
  • Consider certifications like Certified Chatbot Expert™ for chatbot development or Certified Generative AI Expert™ for in-depth knowledge of generative models.
  • The Certified Artificial Intelligence (AI) Expert™ certification offers a broad learning program covering various AI fields, including statistics, deep learning, and regenerative AI.
  • Choose certifications based on your current knowledge level and desired specialization to enhance your practical skills in AI.

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