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Sebastian Thrun, Thad Starner, and Peter Norvig

Unlock the potential of AI with our comprehensive artificial intelligence training course. Grow your career by enrolling in our online Introduction to AI course.

Prerequisite details

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Unlock the potential of AI with our comprehensive artificial intelligence training course. Grow your career by enrolling in our online Introduction to AI course.

Prerequisite details

To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:

  • Object-oriented programming basics
  • Command line interface basics
  • Basic algorithms
  • Intermediate Python
  • Basic calculus
  • Linear algebra
  • Basic probability

You will also need to be able to communicate fluently and professionally in written and spoken English.

What's inside

Syllabus

Welcome to Introduction to Artificial Intelligence!
An introduction to basic AI concepts and the challenge of answering "what is AI?"
In this lesson, you'll dive right in and apply Artificial Intelligence to solve every Sudoku puzzle.
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If you do not want to use Workspaces, then follow these instructions to set up your own system using Anaconda, a popular tool to manage your environments and packages in python.
Use constraint propagation and search to build an agent that reasons like a human would to efficiently solve any Sudoku puzzle.
Expand from the constraint propagation technique used in the Sudoku project to the Constraint Satisfaction Problem framework that can be used to solve a wide range of general problems.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Appropriate as an introduction for learners who are new to AI and want to explore this field further
Recommended for individuals seeking foundational knowledge in AI as it covers fundamental concepts and practical applications
Suitable for those interested in pursuing careers in fields related to AI, such as machine learning, computer vision, and natural language processing
Prerequisites include proficiency in object-oriented programming, command line interface, and basic algorithms, making it accessible to those with some programming background
Taught by instructors recognized for their expertise and experience in AI and related fields
Emphasizes practical application through the use of constraint propagation and search techniques in Sudoku puzzles, strengthening problem-solving abilities

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Artificial Intelligence with these activities:
Compile and review notes, assignments, quizzes, and exams
Reinforce your understanding of course material through comprehensive review.
Show steps
  • Carefully review all class notes, assignments, and quizzes, focusing on key concepts and ideas.
  • Practice solving problems and answering questions related to the course material.
  • Identify areas where you might need additional clarification or support.
Review: Artificial Intelligence by Stuart Russell and Peter Norvig
Gain deeper knowledge of AI concepts prior to engaging with the course curriculum.
View Melania on Amazon
Show steps
  • Read through the entire book.
  • Take notes on key topics.
  • Identify areas where you need further clarification.
Organize a study group to discuss complex AI concepts
Foster collaboration and deeper understanding through peer-to-peer discussions.
Browse courses on Artificial Intelligence
Show steps
  • Identify other learners who are interested in forming a study group.
  • Set up regular meeting times and a communication platform.
  • Choose specific topics or questions to discuss in each session.
  • Facilitate discussions and encourage active participation from all members.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve Sudoku puzzles to practice constraint propagation
Strengthen your understanding of constraint propagation through practical problem-solving.
Show steps
  • Find online Sudoku puzzles or download a Sudoku app.
  • Solve each puzzle using the constraint propagation technique.
  • Identify patterns and strategies that you can apply to future puzzles.
Watch video tutorials on advanced algorithms for AI
Expand your knowledge of AI algorithms beyond the scope of the course curriculum.
Browse courses on Advanced Algorithms
Show steps
  • Identify reputable sources or platforms that offer video tutorials on AI algorithms.
  • Select specific tutorials that align with your interests or areas where you need further clarity.
  • Watch the tutorials carefully, taking notes if necessary.
Build a Python script that leverages constraint propagation to solve Sudoku puzzles
Apply your knowledge of Python and constraint propagation to create a practical tool.
Browse courses on Python
Show steps
  • Design the algorithm for solving Sudoku puzzles using constraint propagation.
  • Implement the algorithm in Python.
  • Test your script on various Sudoku puzzles to validate its accuracy.
Develop a Python project that applies AI techniques to a real-world problem
Apply your learning and build a portfolio piece that showcases your proficiency in AI.
Show steps
  • Identify a specific problem or challenge that you want to address using AI.
  • Research and select appropriate AI techniques for your project.
  • Design and implement a Python project that leverages these techniques.
  • Test your project thoroughly and document your findings.

Career center

Learners who complete Introduction to Artificial Intelligence will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data scientists analyze and interpret data to extract meaningful insights. They use their insights to make informed decisions and solve complex problems. Introduction to Artificial Intelligence would help build a foundation for understanding the principles and techniques used for analyzing and interpreting data to drive decision-making.
Machine Learning Engineer
Machine learning engineers construct and implement algorithms and systems to enable computer systems to learn. They often focus on developing solutions to problems in specific domains, such as healthcare or financial analysis. Introduction to Artificial Intelligence would help build a foundation for understanding the underlying principles of machine learning algorithms and how to apply them to solve problems.
Artificial Intelligence Engineer
Artificial Intelligence Engineers design, develop, and test AI systems. Their job is at the intersection of computer science and mathematics. Introduction to Artificial Intelligence would help lay a foundational understanding of key concepts for designing and developing AI systems. Moreover, the course's focus on the constraint satisfaction problem framework can provide insights for developing solutions to problems across a wide range of domains.
Robotics Engineer
Robotics Engineers design, develop, and test robots. Introduction to Artificial Intelligence would help build a foundation for understanding the principles of AI and how they can be used to develop intelligent robots. The course's focus on constraint solving can provide valuable insights for developing robots capable of navigating complex environments.
Software Engineer
Software Engineers design, develop, and test software systems. Introduction to Artificial Intelligence would help build a foundation for understanding the principles of AI and how they can be used to develop intelligent software systems. The course's focus on programming and problem-solving can provide valuable insights for developing software systems that solve complex problems.
Business Analyst
Business Analysts help organizations understand their business needs and develop strategies to meet those needs. Introduction to Artificial Intelligence would help build a foundation for understanding how AI can be used to improve business processes and decision-making. The course's focus on problem-solving and data analysis can provide valuable insights for developing business strategies.
Product Manager
Product Managers are responsible for the development and marketing of products. Introduction to Artificial Intelligence would help build a foundation for understanding how AI can be used to develop and market products. The course's focus on problem-solving and data analysis can provide valuable insights for developing and marketing products that meet the needs of customers.
Consultant
Consultants help organizations solve problems and improve their performance. Introduction to Artificial Intelligence would help build a foundation for understanding how AI can be used to solve problems and improve performance. The course's focus on problem-solving and data analysis can provide valuable insights for developing solutions to complex problems.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment recommendations. Introduction to Artificial Intelligence would help build a foundation for understanding how AI can be used to analyze financial data. The course's focus on probability and statistics can provide valuable insights for developing quantitative analysis tools and techniques.
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations. Introduction to Artificial Intelligence would help build a foundation for understanding how AI can be used to analyze financial data. The course's focus on probability and statistics can provide valuable insights for developing financial analysis tools and techniques.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve problems in business and industry. Introduction to Artificial Intelligence would help build a foundation for understanding how AI can be used to solve problems in business and industry.
Risk Analyst
Risk Analysts assess and manage risks for organizations. Introduction to Artificial Intelligence would help build a foundation for understanding how AI can be used to assess and manage risks. The course's focus on probability and statistics can provide valuable insights for developing risk analysis tools and techniques.
Statistician
Statisticians collect, analyze, and interpret data. Introduction to Artificial Intelligence would help build a foundation for understanding how AI can be used to collect, analyze, and interpret data. The course's focus on probability and statistics can provide valuable insights for developing statistical analysis tools and techniques.
Data Analyst
Data Analysts collect, analyze, and interpret data. Introduction to Artificial Intelligence would help build a foundation for understanding how AI can be used to collect, analyze, and interpret data. The course's focus on programming and data analysis can provide valuable insights for developing data analysis tools and techniques.
Teacher
Teachers develop and implement curriculum and lesson plans for students. Introduction to Artificial Intelligence may be useful for developing curriculum and lesson plans that incorporate AI concepts and applications.

Reading list

We've selected seven 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 Introduction to Artificial Intelligence.
Provides a comprehensive overview of deep learning techniques and algorithms. It valuable resource for additional reading and for gaining a deeper understanding of deep learning.
Introduces the fundamental concepts and algorithms of reinforcement learning. It valuable resource for additional reading and for gaining a deeper understanding of reinforcement learning.
Provides a comprehensive introduction to probabilistic graphical models. It valuable resource for additional reading and for gaining a deeper understanding of probabilistic graphical models.
Introduces the fundamental concepts and algorithms of computer vision. It valuable resource for additional reading and for gaining a deeper understanding of computer vision.
Introduces the fundamental concepts and algorithms of natural language processing. It valuable resource for additional reading and for gaining a deeper understanding of natural language processing.
Provides a comprehensive introduction to speech and language processing. It valuable resource for additional reading and for gaining a deeper understanding of speech and language processing.
Provides a gentle introduction to probabilistic graphical models concepts and algorithms. It valuable resource for additional reading and for those with little or no background in probabilistic graphical models.

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