Artificial Intelligence Graduate Certificate

Stanford School of Engineering

Graduate Certificates
Graduate Certificate
Delivery Methods
Online, instructor-led
Program Planning Document
Program Planning Document
Tuition
$18,200 - $22,400
View Courses
View Courses
Academic Calendar
Academic Calendar

Get Started

Overview

"Artificial intelligence is the new electricity."
Andrew Ng, Stanford Adjunct Professor 

AI is changing the way we work and live, and has become a de facto part of business and culture. This graduate certificate, which has quickly become our most popular, provides you with a deep dive into the principles and methodologies of AI. Selecting from a variety of electives, you can choose a path tailored to your interests, including natural language processing, vision, data mining, and robotics.

Courses are taught by prominent Stanford faculty whose research is at the forefront of emerging AI developments, including Andrew Ng, Christopher Manning, Chelsea Finn, Percy Liang, Jeanette Bohg.

Courses

Required (complete at least 1)

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Course Title/Code:
Artificial Intelligence: Principles and Techniques
CS221
Delivery
  • Online, instructor-led
Status text
Enrollment Open
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Course Title/Code:
Machine Learning
CS229
Delivery
  • Online, instructor-led
Status text
Enrollment Open

Elective (complete at most 3)

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Course Title/Code:
Decision Making Under Uncertainty
AA228
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Principles of Robot Autonomy I
AA274A
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Computational Logic
CS157
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Introduction to Robotics
CS223A
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Natural Language Processing with Deep Learning
CS224N
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Deep Reinforcement Learning
CS224R
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Natural Language Understanding
CS224U
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Machine Learning with Graphs
CS224W
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Probabilistic Graphical Models: Principles and Techniques
CS228
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Deep Learning
CS230
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Computer Vision: From 3D Reconstruction to Recognition
CS231A
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Deep Learning for Computer Vision
CS231N
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Reinforcement Learning
CS234
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Deep Generative Models
CS236
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Principles of Robot Autonomy II
CS237B
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Deep Multi-task and Meta Learning
CS330
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Mining Massive Data Sets
CS246
Delivery
  • Online, instructor-led
Status text
Enrollment Closed
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Course Title/Code:
Machine Learning Theory
STATS214
Delivery
  • Online, instructor-led
Status text
Enrollment Closed

How Much It Will Cost

See more about tuition and fees.

How Long It Will Take

  • Complete four courses including 1-2 required course(s) and 2-3 electives within 3 academic years.
  • Your time commitment will vary for each course. You should expect an average of 15-20 hours per week for the lecture and homework assignments.
  • Most students complete the program in 1-2 years.
  • CS229 is an especially difficult class. If you have never taken a graduate class through SCPD, we recommend choosing a different course to begin your studies.

What You Need to Get Started

Before enrolling in your first graduate course, you must complete an online application.

Don’t wait! While you can only enroll in courses during open enrollment periods, you can complete your online application at any time.

Once you have enrolled in a course, your application will be sent to the department for approval. You will receive an email notifying you of the department's decision after the enrollment period closes. You can also check your application status in your mystanfordconnection account at any time.

Learn more about the graduate application process.

What You Need to Succeed

  • College level calculus and linear algebra including a good understanding of multivariate derivatives and matrix/vector notation and operations (MATH104, MATH113, CS205L or equivalent).
  • You should be familiar with Probability Theory and basic probability distributions (Continuous, Gaussian, Bernoulli, etc.) You should be able to define the following concepts for both continuous and discrete random variables; Expectation, independence, probability distribution functions, and cumulative distribution functions (CS109, STATS116 or equivalent).
  • Programming experience including familiarity with Linux command line workflows, Java/JavaScript, C/C++ (CS108 or equivalent) Python, or similar languages.
  • A conferred Bachelor’s degree with an undergraduate GPA of 3.0 or better.

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Upcoming Events

AI Informational Session

Tuesday, May 30, 2023 1:00 pm - 1:45 pm
ONLINE EVENT
Artificial Intelligence has transformed countless industries, and changed the way we all live and work. You can be part of what’s next by building your expertise in key techniques, tools, and knowledge fundamental to driving AI advancements… Details