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Chris Callison-Burch

Take a look at artificial intelligence through philosophical and science fiction lenses, and review Python basics. Then explore AI algorithms through studying rational agents and common search algorithms like A* search. Complete short coding assignments in Python.

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What's inside

Syllabus

Week 1: Artificial Intelligence Overview
In the first week of the course, we will introduce AI by delving into the philosophical underpinnings of artificial intelligence, integrating the work of important thinkers from Descartes to Alan Turing. We’ll also look at how Science Fiction often foretells the future of artificial intelligence, including examples of AI from hit 1970s and 1980s films that, decades later, have become a reality. We will also start refreshing our Python knowledge to prepare for our coding assignments later in the course.
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Week 2: Task Environment and Python Review
This week, we will set us up for some key considerations we’ll make when designing our own AI systems and how they should behave. Should they act like humans do, or think like humans do, or act and think rationally? We'll define what rational agents are and explore task environments before completing our Python review. At the end of the week, you will work on your first of three programming assignments.
Week 3: Uninformed Search
In artificial intelligence, a surprising number of tasks that we want to solve can be cast as search problems. This week, we will introduce the formal definition of search problems, and examine some classic algorithms for solving search problems called shortest path algorithms. These are sometimes referred to as “uninformed” search algorithms or “blind” search algorithms, because they are run without any additional knowledge of where our goal lies. We’ll also look at some variants of these algorithms that have computational complexity guarantees.
Week 4: Informed Search
We can often find a solution to a search problem more quickly if we have some knowledge about how close we are to a goal state. This week we’ll look at the process of incorporating such knowledge into search algorithms, which, when used optimally, can help focus our search efforts so that we avoid exploring actions that move us further away from the goal. We’ll examine the most famous informed search algorithm, A* search, which is guaranteed to find an optimal solution first.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Emphasizes the philosophical and scientific aspects of artificial intelligence, providing a well-rounded understanding
Taught by Chris Callison-Burch, a renowned expert in natural language processing and machine translation
Provides a practical approach through Python coding assignments, enabling learners to apply their knowledge
Covers fundamental concepts such as rational agents and common search algorithms, laying a solid foundation in AI
Suitable for learners seeking an introduction to AI, particularly those interested in its philosophical underpinnings and Python programming

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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 Artificial Intelligence Essentials with these activities:
Read 'Gödel, Escher, Bach: An Eternal Golden Braid'
Get a philosophical background of artificial intelligence early on.
Show steps
  • Get a copy of the book.
  • Read the book.
Read 'Superintelligence: Paths, Dangers, Strategies'
Get a broad perspective on the potential benefits and risks of AI.
Show steps
  • Get a copy of the book.
  • Read the book.
Solve Python coding problems on LeetCode
Practice your Python skills and learn to solve algorithmic problems.
Browse courses on Python
Show steps
  • Sign up for a LeetCode account.
  • Choose a problem to solve.
  • Solve the problem.
Five other activities
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Show all eight activities
Write a blog post about the different types of AI algorithms
Improve your understanding of the concepts by explaining them to others.
Browse courses on Machine Learning
Show steps
  • Choose an AI algorithm to write about.
  • Research the algorithm.
  • Write a blog post explaining the algorithm.
Watch tutorials on Coursera about AI
Supplement your learning with additional resources.
Show steps
  • Find a tutorial on Coursera.
  • Watch the tutorial.
Attend a workshop on AI
Learn from experts and network with other AI professionals.
Browse courses on Artificial Intelligence
Show steps
  • Find a workshop on AI.
  • Register for the workshop.
  • Attend the workshop.
Volunteer at an AI organization
Gain practical experience and contribute to the AI community.
Show steps
  • Find an AI organization to volunteer for.
  • Contact the organization and express your interest in volunteering.
  • Attend a volunteer orientation.
  • Start volunteering.
Mentor other students in AI
Strengthen your understanding of AI by teaching it to others.
Browse courses on Artificial Intelligence
Show steps
  • Find other students who are interested in learning about AI.
  • Offer to mentor them.
  • Meet with your mentees regularly to help them learn about AI.

Career center

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