The Pros and Cons of Stanford Online Learning Courses For AI and Machine Learning: The Stanford Artificial Intelligence Professional Program

Stanford University, a renowned leader in higher education, has made a significant impact in the field of Artificial Intelligence (AI) through its instructors, such as Andrew Ng who popularized Machine Learning with his CS229 course on Coursera in 2012.

The Artificial Intelligence Professional Program at Stanford is highly regarded as one of the top post-secondary institutions for AI and provides students with a cost-effective way to gain a wealth of knowledge and resources in machine learning and AI. This program offers a fraction of the cost compared to the Online Graduate Program in Artificial Intelligence.

In this article, I am going to explore the pros and cons of the Professional Program to help you decide if the program is the right fit for you.

Pros:

1. Access to Graduate-Level AI Materials: One of the great things about the Stanford Online Learning courses is that they offer access to graduate-level materials in machine learning and AI. It used to be that you had to attend a university to get access to this type of education. However, the Stanford courses offer a breadth and depth of AI education that is beyond what most graduate programs can provide. Introductory level courses at least seem on-par with what one could expect from graduate-level instruction.
2. (Probably) One of the best learning sources for recent industry-relevant topics and techniques. Of course, working in the industry should give you the closest to the most recent information. But as far as online courses go, these are probably about 2 years behind industry, and ahead of most everyone else.
3. Flexible Learning: Unlike the live version of the course, which includes quizzes and exams, the online certificate program allows you to go at your own pace. This is especially helpful for students who may fall behind due to outside circumstances, such as COVID-19 (such as myself) or other life events.
4. Support from Course Facilitators: Although there won’t be any labs, you will get time each week with a knowledgeable Course Facilitator where you can ask questions, get code debugging assistance and get help with assignments. The Course Facilitators also monitor the Slack board to help with any questions as they come up.
5. Support from Program Managers: PM’s help with accommodations and filling in any gaps. For example, our PM for XCS221 made sure that we had course walk-though calls where our assignments would be explained to us, and she also arranged for us to have a Q&A with the Professor who teaches the live course at Stanford. She also helped navigate accomodations for me since I fell behind in the course due to COVID-19.
6. Opportunities for Networking: Taking the Stanford Online Learning courses also provides opportunities for networking and collaboration with other students who share your interests. You may even make friends and study together in future courses.
7. Recognition on LinkedIn: Upon completion of the program, you will receive a certification from Stanford University that will appear on your LinkedIn profile. This is a valuable asset that showcases your knowledge and interest in AI to potential employers.
8. Re-take options: Even if you don’t pass the class on your first try, there are options to re-take courses at a significant discount from the original cost.

Cons:

1. Outdated Content: The recorded classes in the XCS program may not be quote as up-to-date as the live classes, which are more expensive but could offer more recent discussions and developments in the field.
2. Missing Instructional Gaps (between the Course Lectures / Examples and Assignments): One of the biggest cons of the Stanford Online Learning courses is that there are no labs, which can make it challenging to take what you have learned from the video recordings of the class lectures and to translate that into the coursework and assignments. It can be a pretty heavy lift.
3. Difficulty: The coursework is not beginner-level, and it requires a strong background in programming, mathematics, and computer science. Unless you have a degree in one of these fields, it may be challenging to keep up with the course material.
4. Heavy Mathematical Approach: The course is heavily weighted towards a mathematical explanation of the material, which can make it difficult for some students to grasp the concepts. A more intuitive approach, such as the one used by CS188 at UC Berkeley could be easier to learn for some students, and I found the online videos a useful supplement for the intro course.
5. Self-Learning Required: The course recordings provide a good overview of the material, but they can be dense and not always exciting to learn from. It may take some extra effort and research to fill in the gaps and fully understand the course concepts.

In conclusion, the Stanford Online Learning courses offer a wealth of knowledge and resources for students interested in AI and machine learning and I personally think that it’s a pretty great deal for the access to material and instruction provided at this price point. However, the courses are not for everyone, and it is important to consider the pros and cons before enrolling. If you are willing to put in the effort, the rewards can be significant, including a valuable certification from Stanford University that will enhance your resume and LinkedIn profile.

Additional Resources:

• This article reviews some of the Graduate Level AI Courses at Stanford, which overlaps pretty heavily with the courses offered in the Professional Program

• A collection of “Cheat Sheets” with some of the core concepts covered in a few of the most popular Stanford AI Courses