Student Guide to AI and Robotics

This book provides a practical and accessible introduction to AI and robotics, presenting the foundational technologies driving the development of intelligent systems. It covers key topics such as machine learning, perception, control, and autonomous decision-making, balancing theoretical concepts with practical applications.

Through selected examples and case studies, the book explores robotics platforms and applied AI technologies used across industries, offering insights into their transformative potential in real-world scenarios. With a focus on hands-on learning, it introduces programming languages and tools commonly used in AI and robotics, empowering readers to apply concepts and techniques effectively. It also addresses the importance of building secure, responsible systems and examines the future of human-AI collaboration.

An essential resource for introductory AI and robotics courses, this book provides the foundational knowledge needed to advance in these dynamic fields.

Mahwish Zahara is an artificial intelligence (AI) lecturer, published author, and guest speaker, specialising in marketing strategy, data science, and applied AI. She designed and launched one of the UK’s first ever Master's courses in AI in Marketing, which enabled students to learn machine learning workflows, advanced data applications, and how to apply them to real world business problems.

An expert in marketing strategy with a PhD in Business and Marketing, her research explores the intersection of digital technologies and marketing, with a focus on generative AI, marketing automation, consumer insights, and algorithmic decision-making. Through her research and teaching, she embeds new technologies into the learning journey to develop technical and critical thinking skills for the AI-enabled future global economy.

She has contributed curriculum design and innovation at academic and commercial levels, developing frameworks for ethical and strategic use of large language models for teaching and research outputs. Delivering hands-on experience and an industry-facing approach to learning, her students gain experience with AI model programming workflows, large model architectures, and cloud-based computing platforms while developing critical thought around their limitations, metrics for performance, and real-world applicability.

She investigates frontier technologies like quantum computing, AI-driven robotics, and the next generation of intelligent systems. With recent publications and editing AI in marketing texts on AI-powered customer experience, conversational AI, and ethics of AI in marketing, Dr Zahara continues to contribute to innovation at the forefront of AI and marketing.

Tamour Raza conducts research around artificial intelligence and robotics engineering, specialising in machine learning, algorithmic decision-making, and designing intelligent socio-technical systems. His work has covered both theoretical and computational principles for supervised and unsupervised learning; prediction; optimisation-based decision-making; and modelling systems that learn through feedback commonly used in robotics and autonomous systems.

He is particularly interested in how intelligent systems behave at scale, deployed in intricate settings defined by uncertainty, variability, real-time operations, and large, heterogeneous end-users. Tamour explores system performance, robustness, and adaptation, while considering broader implications such systems have when deployed at scale.

Tamour’s previous academic research has surrounded artificial intelligence systems within industry sectors, publishing papers around algorithmic systems in marketing and how technologies such as recommender systems, customer intelligence models, and real-time decision engines affect organisational decision-making processes and end-user experiences. He is the co-author of AI textbook A Student Guide to AI and Robotics, which closely ties his research to real-world applications.

Tamour takes a socio-technical approach to his research and considers, alongside raw technical performance metrics of machine learning systems, how they may be used at an organisational level, and what their broader ethical and societal consequences are. He aims to design systems that are rigorous, interpretable, and accountable.

Obianuju Blossom Ochuba specialises in robotics and artificial intelligence with a focus on intelligent systems, automation, and data-driven solutions. She graduated with a Master of Science degree in Robotics and Artificial Intelligence as well as a degree in Electrical and Electronic Engineering.

She has experience in robotic perception, adaptive control, automation, and intelligent data systems. She also possesses knowledge in programming and algorithm development, which she has utilised while working in technical and analytics roles in the industry. She has worked on projects involving automation pipelines, data systems/architecture, and AI-driven decision-making systems.

Her expertise includes building and testing smart systems in real-world scenarios. She’s always curious about how well these systems perform and how they can be scaled. Obianuju often implements her work from an engineering standpoint and an applied standpoint, as she loves to understand the theory behind practical implementations. She’s passionate about creating and helping to build robust and scalable AI systems as well as helping technology function in complex real-world scenarios.