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AI Mastery

From Search Algorithms to Advanced Strategies

Embark on a thorough exploration of Artificial Intelligence (AI) in this meticulously designed course, suitable for both beginners and intermediate learners. Covering a diverse range of topics, it establishes a strong foundation in AI theory and algorithms while also delving into practical applications.

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Embark on a thorough exploration of Artificial Intelligence (AI) in this meticulously designed course, suitable for both beginners and intermediate learners. Covering a diverse range of topics, it establishes a strong foundation in AI theory and algorithms while also delving into practical applications.

Commencing with an overview of AI and its techniques, participants will delve into problem-solving approaches, encompassing both theoretical concepts and real-world implementations. Dive into engaging toy problems like Tic-tac-toe and the Travelling Salesman Problem to gain hands-on problem-solving experience.

Detailed lectures will introduce participants to general search algorithms, both uninformed and informed search methods, and adversarial strategies using game theory, including the Mini Max Algorithm. Additionally, the course explores Constraint Satisfactory Problems (CSP) and the pivotal role of intelligent agents in decision-making processes.

Understanding knowledge representation is vital in AI, and this course provides comprehensive coverage. From foundational propositional and predicate logic to advanced techniques like knowledge representation using rules, semantic nets, and frames, participants will gain insight into how AI systems store and process information.

As the course progresses, participants will delve into uncertainty in knowledge and reasoning, explore machine learning algorithms, and grasp the fundamentals of expert systems. By course completion, participants will possess a firm understanding of AI theory and practical skills applicable to real-world scenarios.

Whether you're a student, professional, or enthusiast, this course empowers you with the knowledge and tools to navigate the dynamic field of Artificial Intelligence confidently. Join us on this educational journey and discover AI's potential to revolutionize industries and shape the future.

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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores AI techniques that are standard across industry
Teaches problem-solving approaches, both theoretical and practical
Develops foundational and advanced knowledge representation techniques
Introduces machine learning algorithms and expert systems fundamentals
Builds a strong foundation for beginners and strengthens foundational knowledge for intermediate learners
Requires learners to come in with extensive background knowledge

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Career center

Learners who complete AI Mastery: From Search Algorithms to Advanced Strategies will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Developing machine learning models is central to the role of a Machine Learning Engineer. Knowledge of search algorithms, particularly heuristics, is useful for guiding the learning process. Models are often built to fulfill a goal, such as classifying or predicting something. This course provides a strong foundation in game theory, constraint Satisfactory Problems (CSP), and intelligent agents that can be used to understand and build models like these.
Software Engineer
Software Engineers use knowledge of algorithms, including uninformed and informed search, to implement efficient solutions. This course lays the foundation for understanding these algorithms. Additionally, the course provides a strong foundation in AI theory and applications that is highly relevant to many different roles in the software engineering field. These include roles focused on backend and frontend as well as mobile and desktop.
Data Scientist
Data Scientists who have the ambition of leading or building teams should have expertise in a range of data science areas, including data munging, machine learning, business intelligence, and data visualization. This course will be particularly useful for those who wish to have expertise in the machine learning area of data science. It will provide a firm understanding of search algorithms, AI theory and algorithms, constraint Satisfactory Problems (CSP), and intelligent agents that can be used to understand and implement data science tasks.
Game Theoretician
Game Theory is a branch of mathematics that is focused on analyzing strategies for decision-making in situations where multiple agents are involved. This course provides a foundation in adversarial strategies and game theory that will be helpful for those wishing to work as Game Theoreticians. The course explores these strategies through the Mini Max Algorithm, which is an extremely important algorithm for the field.
Artificial Intelligence Researcher
Artificial Intelligence Researchers develop new algorithms and techniques for a range of applications, including natural language processing, computer vision, and robotics. This course will help a person build a solid foundation in Artificial Intelligence (AI) theory and algorithms that will aid in the design and development of new AI techniques. The course also provides practical experience with toy problems that will be helpful for someone embarking on a career as an AI researcher.
Data Analyst
Data Analysts use their knowledge of AI and data science to find and analyze data that can be used to inform business decisions. This course will help Data Analysts build the necessary foundational knowledge of AI theory, algorithms, and applications that will be helpful for understanding data. The course will also provide knowledge of intelligent agents and CSPs which are used in a range of data analysis applications.
Robotics Engineer
Robotics Engineers design, build, and maintain robots. They use a range of AI techniques to do this, including search algorithms and intelligent agents. This course will provide robotics engineers with the necessary foundation in these areas, as well as provide practical experience with toy problems that will help them build a successful career in robotics
Quantitative Analyst
Quantitative Analysts use advanced mathematical and statistical techniques to analyze financial data. They often use AI techniques, such as machine learning and natural language processing, to do this. This course will help a person build a foundation in AI theory and algorithms that are used by quantitative analysts. The course will also provide useful insights into intelligent agents, CSPs, and adversarial strategies.
Computer Scientist
Computer Scientists work on a range of problems, from developing new algorithms to designing new programming languages. This course will help a person build a solid foundation in AI theory and algorithms that will be helpful for working on a range of computer science problems.
Operations Research Analyst
Operations Research Analysts use a range of techniques, including AI and optimization, to solve problems in a range of industries. This course will help a person build a foundation in AI theory and algorithms that will be helpful for a range of problems in operations research.
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. They use a range of techniques, including AI and data mining, to do this. This course will help a person build a foundation in AI theory and algorithms that will be helpful for working as a business intelligence analyst.
Product Manager
Product Managers work on the development and launch of new products. They use a range of techniques, including AI and market research, to do this. This course will help a person build a foundation in AI theory and algorithms that will be helpful for working as a product manager. It will also provide a useful foundation in adversarial strategies that can be used to better understand competitors.
Data Architect
Data Architects design and build data systems. They use a range of techniques, including AI and data management, to do this. This course will help a person build a foundation in AI theory and algorithms that will be helpful for a range of problems in data architecture. It will also provide insights into intelligent agents and CSPs which are used in a range of data architecture applications.
Machine Learning Product Manager
Machine Learning Product Managers work on the development and launch of machine learning products. They use a range of techniques, including machine learning and product management, to do this. This course will help a person build a foundation in AI theory and algorithms that will be helpful for working as a Machine Learning Product Manager. It will also provide the foundational knowledge of intelligent agents, search algorithms, and CSPs which are all relevant to the role.
Software Architect
Software Architects design and build software systems. They use a range of techniques, including AI and software engineering, to do this. This course will help a person build a foundation in AI theory and algorithms that will be helpful for a range of problems in software architecture. It will also provide foundational knowledge of intelligent agents, search algorithms, and CSPs which are all relevant to the role.

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in AI Mastery: From Search Algorithms to Advanced Strategies.
This textbook provides a comprehensive introduction to machine learning, covering supervised and unsupervised learning, reinforcement learning, and statistical modeling. It valuable resource for students and practitioners alike.
This textbook provides a comprehensive introduction to deep learning, covering neural networks, convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for students and practitioners alike.
This textbook provides a comprehensive introduction to reinforcement learning, covering Markov decision processes, dynamic programming, and deep reinforcement learning. It valuable resource for students and practitioners alike.
This textbook provides a comprehensive introduction to natural language processing, covering tokenization, part-of-speech tagging, parsing, and machine translation. It valuable resource for students and practitioners alike.
This textbook provides a comprehensive introduction to computer vision, covering image formation, feature detection, object recognition, and image segmentation. It valuable resource for students and practitioners alike.
This textbook provides a comprehensive introduction to speech and language processing, covering acoustics, phonetics, phonology, morphology, syntax, and semantics. It valuable resource for students and practitioners alike.
This textbook provides a comprehensive introduction to AI, covering fundamental concepts, algorithms, and applications. It valuable resource for students and practitioners alike.
This textbook provides a comprehensive introduction to AI, covering fundamental concepts, algorithms, and applications. It valuable resource for students and practitioners alike.
This textbook provides a comprehensive introduction to AI, covering fundamental concepts, algorithms, and applications. It valuable resource for students and practitioners alike.
Provides a comprehensive overview of AI, covering fundamental concepts, algorithms, and applications. It valuable resource for students and practitioners alike.
Explores the potential risks and benefits of AI, and argues for the need to develop AI systems that are aligned with human values.

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