Information Session: Artificial Intelligence Online Programs I March 2025

Key Concepts

• AI Graduate Certificate (Stanford Online)
• AI Professional Program/Certificate
• Credit-bearing vs. Non-credit bearing courses
• Stanford Online (CGOE - Center for Global and Online Education)
• Prerequisites (Calculus, Linear Algebra, Probability, Programming)
• Flexibility (Pace, Enrollment)
• Course Facilitators
• Graduate Credit Transfer
• Stanford Transcript
• Enrollment Periods

AI Graduate Certificate (Pax Hehmeyer)

Overview

• Accredited certificate consisting of four graduate-level courses.
• Courses are actual on-campus courses taken online, with the same assignments, deadlines, and workload.
• 12-20 units of work, up to three years to complete.
• Cost is per unit, with tuition subject to annual changes.

Course Structure

• One required course: either CS229 (Machine Learning) or CS221 (Artificial Intelligence Principles and Techniques).
• Remaining units can be fulfilled with electives.
• Additional AI-related courses not listed may be petitioned for credit.
• Examples of electives: Large Language Modeling from Scratch, Natural Language Understanding for Speech.

Course Experience

• Lectures are recorded and available for live streaming or later viewing.
• Mix of written programming assignments, projects, exams, and problem sets.
• Following the academic calendar is crucial for meeting deadlines.
• Upon completion, students earn a Stanford transcript and units.
• Up to 18 units may be applied towards a Stanford master's degree (subject to admission and departmental approval).
• A grade of B or better is required to continue taking courses and earn the certificate.

Target Students

• Flexible program suitable for various students.
• Professionals with advanced degrees seeking to refresh skills or fill gaps in their knowledge.
• Individuals considering graduate school who want to test the waters.
• Other graduate certificates are available for introductory programming or foundations of computer science.

Prerequisites

• Bachelor's degree required with a GPA of 3.0 or better.
• College calculus, linear algebra (usually multivariable calculus), and probability theory.
• Strong programming experience.
• Prerequisites are reviewed by the department on a course-by-course basis.
• Transcripts are reviewed to verify prerequisites.
• Reviewing course material is recommended if it has been a long time since taking prerequisite courses.
• Public-facing websites for courses often provide detailed prerequisite information and sample problem sets.
• Lecture recordings on the Stanford Online YouTube channel can help gauge course difficulty.

Application Process

• Apply on a course-by-course basis, not admitted into a program.
• Create an account on the Stanford Online website and submit a non-degree option application.
• Required materials: short statement of purpose, personal information, professional background, and educational background (official transcripts).
• The application is reviewed only when enrolling in a course.
• The department reviews the application to determine if the applicant meets the requirements for the specific course.
• Subsequent course enrollments require re-evaluation by the department, including review of Stanford transcripts.

Enrollment Periods

• Enrollment is not continuously open.
• Enrollment periods open approximately two months before the quarter begins.
• Summer enrollment opens on April 7th, for courses starting in June.
• Autumn enrollment opens in late July/early August, for courses starting in late September.
• The academic calendar on the Stanford Online website shows enrollment periods for all quarters.

International Students

• The program is global, with students from around the world.
• Challenges may arise due to time zone differences.
• Teaching teams accommodate different time zones and work schedules.
• A generous drop policy allows students to drop courses within the first three weeks for a full tuition refund (minus a processing fee).

Master's Degree Implications

• Up to 18 units from non-degree courses can be applied towards a relevant master's degree (subject to admission and departmental approval).
• Being a non-degree student is not a fast track into a master's degree program.
• Master's degrees in the School of Engineering are available on a part-time and/or online basis.
• Computer science degrees can be completed fully online, but course selection may be limited.

AI Professional Program (Petra Parikova)

Overview

• Professional version of the AI program, based on graduate-level content.
• Offers additional flexibility for professionals who may not need credit or have employer constraints.
• Classes are still challenging and cover the same depth and breadth as the graduate program.

Course Offerings

• Eight classes currently available, equivalent to graduate courses (e.g., XCS229 Machine Learning, XCS224N Natural Language Processing with Deep Learning).
• Classes run off the academic schedule with modifications.
• Upcoming classes: Machine Learning with Graphs (starting next Monday), Machine Learning (starting May 5), Deep Generative Models (starting May 19).
• Most enrollments are currently open, except for two classes that are currently paused.
• Recommended starting point: Artificial Intelligence Principles and Techniques (covers a wide range of AI concepts).
• A short video is available with recommendations on which courses to take based on prior knowledge and experience.

Course Structure and Flexibility

• Uses recorded lectures from Stanford faculty.
• Lectures are segmented by topic, with optional content removed to focus on core aspects.
• No final exams or project work.
• Focus on core assignments.
• Sessions run throughout the year, usually twice or three times a year, in 10-week sprints or cohorts with approximately 160 learners in each cohort.
• Uses the same set of written and programming assignments as the graduate version.
• Auto-graders provide debugging assistance and feedback.

Support and Community

• Course facilitators who have taken the graduate class support cohorts with content-related questions.
• Support is available through individual calls and a Slack community.
• The community is vibrant, offering opportunities to meet fellow learners and form teams.

Certification

• Classes can be taken individually or as part of the AI Professional Certificate program.
• Taking one class results in a course certificate.
• Taking three classes results in the AI Professional Certificate in addition to the course certificates.

Assignments

• Written assignments involve math, proofs, and logical reasoning.
• Programming assignments are written in pure Python, often without common packages.

Prerequisites

• Similar to the graduate program.
• No long application or transcript uploads.
• Applicants are asked about their proficiency in Python, college calculus, linear algebra, and probability.
• The application is fairly short (10-20 minutes).
• The video with course recommendations includes more information about specific prerequisites.

Pass/Fail

• The professional program is pass/fail.
• A certificate is awarded for passing the class.
• Passing rate is 70%.

Comparison of AI Graduate Certificate and AI Professional Program

| Feature | AI Graduate Certificate

Synthesis/Conclusion

The presentation provides a detailed overview of the AI Graduate Certificate and the AI Professional Program offered by Stanford Online. It highlights the key differences between the two programs, focusing on the level of commitment, flexibility, cost, and the type of recognition received upon completion. The speakers address common questions about prerequisites, application processes, enrollment periods, and the applicability of these programs for international students. The information is presented to help prospective students make informed decisions about which program best suits their individual needs and career goals. The presentation also emphasizes the availability of resources, such as YouTube videos and course websites, to help students prepare for the rigorous coursework involved.