Skip to content

Expand Your Knowledge of Artificial Intelligence

Nanodegree Program

Learn essential Artificial Intelligence concepts from AI experts like Peter Norvig and Sebastian Thrun, including search, optimization, planning, pattern recognition, and more.

Enroll Now
  • Estimated time
    3 Months

    At 12-15 hrs/week

  • Enroll by
    June 14, 2023

    Get access to classroom immediately on enrollment

  • Skills acquired
    Optimization Algorithms, Minimax Search, Bayesian Networks

What you will learn

  1. Learn Foundational AI Algorithms

    3 months to complete

    Learn to write programs using the foundational AI algorithms powering everything from NASA’s Mars Rover to DeepMind’s AlphaGo Zero. This program will teach you classical AI algorithms applied to common problem types. You’ll master Bayes Networks and Hidden Markov Models, and more.

    Prerequisite knowledge

    This program requires experience with linear algebra, statistics, and Python (including object-oriented programming).

    1. Introduction to Artificial Intelligence

      In this course, you'll learn about the foundations of AI. You'll configure your programming environment to work on AI problems with Python. At the end of the course you'll build a Sudoku solver and solve constraint satisfaction problems.

    2. Classical Search

      In this course you’ll learn classical graph search algorithms--including uninformed search techniques like breadth-first and depth-first search and informed search with heuristics including A*. These algorithms are at the heart of many classical AI techniques, and have been used for planning, optimization, problem solving, and more. Complete the lesson by teaching PacMan to search with these techniques to solve increasingly complex domains.

      • Automated Planning

        In this course you’ll learn to represent general problem domains with symbolic logic and use search to find optimal plans for achieving your agent’s goals. Planning & scheduling systems power modern automation & logistics operations, and aerospace applications like the Hubble telescope & NASA Mars rovers.

      • Optimization Problems

        In this course you’ll learn about iterative improvement optimization problems and classical algorithms emphasizing gradient-free methods for solving them. These techniques can often be used on intractable problems to find solutions that are "good enough" for practical purposes, and have been used extensively in fields like Operations Research & logistics. You’ll finish the lesson by completing a classroom exercise comparing the different algorithms' performance on a variety of problems.

        • Adversarial Search

          In this course you’ll learn how to search in multi-agent environments (including decision making in competitive environments) using the minimax theorem from game theory. Then build an agent that can play games better than any humans.

        • Fundamentals of Probabilistic Graphical Models

          In this course you’ll learn to use Bayes Nets to represent complex probability distributions, and algorithms for sampling from those distributions. Then learn the algorithms used to train, predict, and evaluate Hidden Markov Models for pattern recognition. HMMs have been used for gesture recognition in computer vision, gene sequence identification in bioinformatics, speech generation & part of speech tagging in natural language processing, and more.

      All our programs include

      • Real-world projects from industry experts

        With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.

      • Real-time support

        On demand help. Receive instant help with your learning directly in the classroom. Stay on track and get unstuck.

      • Career services

        You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.

      • Flexible learning program

        Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

      Program offerings

      • Class content

        • Real-world projects
        • Project reviews
        • Project feedback from experienced reviewers
      • Student services

        • Student community
        • Real-time support
      • Career services

        • Github review
        • Linkedin profile optimization

      Succeed with personalized services.

      We provide services customized for your needs at every step of your learning journey to ensure your success.

      Get timely feedback on your projects.

      • Personalized feedback
      • Unlimited submissions and feedback loops
      • Practical tips and industry best practices
      • Additional suggested resources to improve
      • 1,400+

        project reviewers

      • 2.7M

        projects reviewed

      • 88/100

        reviewer rating

      • 1.1 hours

        avg project review turnaround time

      Learn with the best.

      Learn with the best.

      • Peter Norvig

        Research Director, Google

        Peter Norvig is a Director of Research at Google and is co-author of Artificial Intelligence: A Modern Approach, the leading textbook in the field.

      • Sebastian Thrun


        As the founder and president of Udacity, Sebastian’s mission is to democratize education. He is also the founder of Google X, where he led projects including the Self-Driving Car, Google Glass, and more.

      • Thad Starner

        Professor of Computer Science, Georgia Tech

        Thad Starner is the director of the Contextual Computing Group (CCG) at Georgia Tech and is also the longest-serving Technical Lead/Manager on Google's Glass project.

      Top student reviews

      0.0 stars
      NaN stars


      NaN stars


      NaN stars


      NaN stars


      NaN stars


      NaN stars


      Artificial Intelligence

      Get started today

        • Learn

          Learn everything you need to start building your own AI applications

        • Average Time

          On average, successful students take 3 months to complete this program.

        • Benefits include

          • Real-world projects from industry experts
          • Real-time classroom support
          • Career services

        Program Details

        Program overview: Why should I take this program?
        • Why should I enroll in this program?

          The Artificial Intelligence Nanodegree program features expert instructors, and world-class curriculum built in collaboration with top companies in the field. The program offers a broad introduction to the field of artificial intelligence, and can help you maximize your potential as an artificial intelligence or machine learning engineer. If you’re ready for an efficient and effective immersion in the world of AI, with the goal of pursuing new opportunities in the field, this is an excellent program for you.

        • What jobs will this program prepare me for?

          This Nanodegree program is designed to build on your existing skills as an engineer or developer. As such, it doesn't prepare you for a specific job, but instead expands your skills with artificial intelligence algorithms. These skills can be applied to various applications such as video game AI, pathfinding for robots, and recognizing patterns over time like handwriting and sign language.

        • How do I know if this program is right for me?

          In this Nanodegree program, you will learn from the world’s foremost AI experts, and develop a deep understanding of algorithms being applied to real-world problems in Natural Language Processing, Computer Vision, Bioinformatics and more. If your goal is to become an AI expert, then this program is ideal, because it teaches you some of the most important algorithms in AI. You’ll benefit from a structured approach for applying these techniques to new challenges, and emerge from the program fully prepared to advance in the field.

        Enrollment and admission
        • What are the prerequisites for enrollment?

          If you are new to Python programming, we suggest our AI Programming with Python Nanodegree program. You must have completed a course in computer science algorithms equivalent to the Data Structures & Algorithms Nanodegree program prior to entering the program. Additionally, you should have the following knowledge:

          Intermediate Python programming knowledge, including:

          • Strings, numbers, and variables
          • Statements, operators, and expressions
          • Lists, tuples, and dictionaries
          • Conditions, loops
          • Generators & comprehensions
          • Procedures, objects, modules, and libraries
          • Troubleshooting and debugging
          • Research & documentation
          • Problem solving
          • Algorithms and data structures

          Basic shell scripting:

          • Run programs from a command line
          • Debug error messages and feedback
          • Set environment variables
          • Establish remote connections

          Basic statistical knowledge, including:

          • Populations, samples
          • Mean, median, mode
          • Standard error
          • Variation, standard deviations
          • Normal distribution

          Intermediate differential calculus and linear algebra, including:

          • Derivatives & Integrals
          • Series expansions
          • Matrix operations through eigenvectors and eigenvalues

          Additionally, you should be able to follow and interpret pseudocode for algorithms like the example below and implement them in Python. You should also be able to informally evaluate the time or space complexity of an algorithm. For example, you should be able to explain that a for loop that does constant O(1) work on each iteration over an array of length n has a complexity of O(n).

        • If I don’t meet the requirements to enroll, what should I do?

          We have a number of courses and programs we can recommend that will help prepare you for the program, depending on the areas you need to address. For example:

        • Do I need to apply? What are the admission criteria?

          No. This Nanodegree program accepts all applicants regardless of experience and specific background.

        Tuition and term of program
        • How is this Nanodegree program structured?

          The Artificial Intelligence Nanodegree program is comprised of content and curriculum to support four (4) projects. We estimate that students can complete the program in three (3) months working 12-15 hours per week.

          Each project will be reviewed by the Udacity reviewer network. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.

        • How long is this Nanodegree program?

          Access to this Nanodegree program runs for the length of time specified above. If you do not graduate within that time period, you will continue learning with month-to-month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our Nanodegree programs.

        • Can I switch my start date? Can I get a refund?

          Please see the Udacity Program FAQs for policies on enrollment in our programs.

        Software and hardware: What do I need for this program?
        • What software and versions will I need in this program?

          You will need a computer running a 64-bit operating system (most modern Windows, OS X, and Linux versions will work) with at least 8GB of RAM, along with administrator account permissions sufficient to install programs including Anaconda with Python 3.5 and supporting packages. Your network should allow secure connections to remote hosts (like SSH). We will provide you with instructions to install the required software packages. Udacity does not provide any hardware.

        Artificial Intelligence

        Enroll Now