Stanford Artificial Intelligence Professional Program – Rejoice! You can get this and more from a certain office… It’s called a Grade School and it’s available for a fee.
A year and a half ago, I enrolled in a CS-related professional graduate program at Stanford, and finally graduated in December. Here is my new glossy book. It took me 5 quarters to complete, taking four shifts in total (I took the summer off.) In this article I will describe these programs if you are interested.
Stanford Artificial Intelligence Professional Program
SCPD stands for People’s Constituent Assembly. Here is their website. They offer courses in a variety of areas, from computer science fundamentals to cyber security strategy. Artificial Intelligence program enrolled in courses offered by the Computer Science Department.
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In this and most SCPD programs, you take classes with other Stanford students: listen to lectures (addresses), assign assignments (solve math problems or computer code), take grades, take tests and midterms, and discuss your questions with teaching assistants. .
Each course completes a quarter. I completed four courses in five terms because I wanted to take a summer vacation. I’m sure there’s a full term, but I can’t find any right now.
Usually, each program offers several courses, and you must complete a specific course. For example, for the AI certificate, you must complete 4 of the 14 offered in the AI certificate: one mandatory (CS221 Artificial Intelligence: Principles and Techniques) and three elective courses. The list of course providers has been updated to keep up with the times.
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You do not need to complete a certificate program; In fact, you can take only the classes you need and easily take them according to your class and placement. You’ll still need to go through the same registration steps, but the expectations may be simpler.
If you complete the program, you will receive the above card. And if you’re on LinkedIn, you’ll have a Stanford icon next to your profile 😉
Of course, if you get a certificate, expect more jobs (if you take some courses, choose the ones you expect). The requirements are strictly outlined on the certification page, so please review them.
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There are so many guides, there is Versus Data Science, there are books, and online videos for free… but you can get things only through training provided by a reputable organization.
If you pay for things or spend $5k without doing your own prior research, you can get that much education for free or at least try the education before you buy.
It’s crazy how much of this stuff is available for free. The full reading notes for CS231n are the same. There are familiar diatribes in other sections as well. The CS229 Lecture Notes is a valuable book of basic information for “Classical ML”.
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And of course there are other resources besides Stanford where you can learn about ML. Consider Google’s course. It’s more practice-oriented, and you don’t have to do all the math. If you find and feel that you are doing a lot of math and want to learn these concepts at a higher level, you can go for some advanced programs. If not, proceed to hack ML-y stuff.
Now, I know, a bill from Stanford is hard to beat. Few schools have the credentials, reputation, resources, and professors that Stanford offers. If you’ve never been to the Stanford campus and live nearby, you should check it out! It also has a Rodin sculpture in the garden.
However, if you live near another good school that offers a similar program, consider enrolling at that school instead. There are some advantages to meeting face-to-face with TAS and other distance learners.
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SCPD policy prohibits reading and testing on campus. This has never been a problem for me unless you get “spotted” on test forums. I’ve always found it spot on now. TAS and professors were always more than happy to talk in person rather than zoom or crash another remote conference. However, I only went to campus once to meet my TA and do a video conference.
Additionally, some poster sessions are essentially giant career fairs, where you show and present your project with posters. Notably, the CS231n Convolutional Neural Networks session was the last: Waymo, Zoox, Cruise and other companies were there to explain their complements.
The same can be said about other industry events: CVPR reports not only its work, but the entire industry’s ML curve at the scientific conference Expo.
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No, you cannot get a student ID and therefore are not eligible for credit. But you get access to a digital library, and you can submit all the papers you need for your work to ACM, IEEE, etc. and others for free.
And @stanford.edu you will receive an email for your study period. Use it when you can.
Because machine learning requires a lot of GPU time, you’ll have credits in Microsoft Azure or Google Cloud to run GPU-intensive calculations for class assignments and projects. But if you have a computer game at home, you don’t need to do that. Last year, when I got a new GPU, I could get away with an old GeForce GTX 1070, which you could buy new for $300 (well, old, as far as learning machines go). Remember, you have $20,000 for education, so you can definitely save $200 for a GPU.
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If you don’t have a gaming PC and only have a non-gaming laptop, consider getting an external GPU like I mentioned on the blog last year.
From the AI certificate courses, which I took (in the order you want), with a more in-depth description.
CS231n Convolutional Neural Networks Visual Review I took the best course in deep learning and neural networks. If you are interested in deep practical learning, get this first. At the time of publishing this blog, the number of this course is open, so don’t miss your chance. Not only will you work in computer vision, but you’ll learn the fundamentals of deep learning, starting with self-development and implementation steps and backpropagation, ending with the implementation of tried-and-true architectures with basic computer functions (including the “nitty-gritty” details). activaiton as construction of maps).
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Since this method was state of the art 5 years ago, it seemed to me that there was little information. It is not a sharp cut for the matter, but more for the basics.
Inferential graph query algorithms (A-star), reinforcement learning (I got 4th in a fun PAC-Man challenge), Markov decision processes, satisfiability constraints, and other basic “classical” AI tools without much ML at the core. If you think this course is easy because it’s an “overview”, don’t be fooled. You are expected to dig deep and show understanding
The course is led by Percy Liang; He is a great teacher and researcher; In fact, our goal for the course CS224n (see below) was an extension of his paper. 🙂
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Submit 5 days before submission of Leaderboard for Pac-Man Tournament… 🙁 If you get a high score, don’t reveal it!
CS224n Natural Language Processing with Deep Learning. I learned about recurrent neural networks, LSTM, word vectors and neural language models. In two classifications, they apply neural translation machine components to an encoder-decoder network to translate English into Spanish. I buy it in one word and another time in Josie’s time. This is crazy! These were the biggest brain teasers in the world 10 years ago and now you can do them
This is a new course, and represents the state of the art in NLP when I took it a year ago. If you are interested in NLP, you must have this course. Of all the courses, this was the most learned, the most modern and the most memorable for me.
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AA228 Decision-Magic Under Uncertainty. This is a CS/Aeronautical course covering modeling and working with uncertainties in decision making and planning. Indeed, Niche is different from the above and almost entirely different in design, Q-Learning/SARA, Monte-Carlo tree search methods and semi-observable Markov decision processes.
It was a very useful result for me because I finally understood how to use Bayesian inference in real situations. This course starts with the basics, and the instructor takes the approach of “Unless you understand the basics, we can’t even talk about POMDPs.” Finally, I am actually working on situational opportunities, and can now contribute to the mission statement. Continuous advances in technology.
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