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Stanford Online Masters In Computer Science – Have fun! You can get all this with one service… It’s called Grad School and it’s available for rent.
A year and a half ago, I entered Stanford’s CS graduate program for professionals, and graduated in December. Here’s the shiny new certificate. In total, I did 4 courses, and it took me about 5 to finish (I took a break in the summer.) In this article I will describe this program if you are interested.
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SCPD stands for Stanford Center for Professional Development. Here is their website. They offer courses on a variety of topics, from Computer Science Fundamentals, to Cybersecurity Strategy. I am enrolled in the Artificial Intelligence program which includes courses from the Computer Science department.
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In this program and most other SCPD programs, you take classes with other Stanford students: listen to lectures (online), submit assignments (written solutions to math problems or computer code), getting grades, taking tests and midterms, and discussing your problems with the Instructor.
It takes a quarter of each course to complete. I finished 4 courses over 5 quarters because I wanted to relax. I’m sure there is an absolute term, but I can’t find any reference to it now.
Generally, each program offers multiple courses, and you must complete multiple courses. For example, for the AI certificate, you must complete 4 of the 14 offered by the AI certificate: one compulsory (CS221 Artificial Intelligence: Principles and Techniques) and three elective courses. The range of courses offered will be updated to keep up with the times.
You do not have to complete the certificate program; in fact, you can just take the classes you’re interested in and simplify them with grades and assignments. You still have to go through the same registration process, but the expectations may be lighter.
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If you complete the program, you will receive a letter like the one above. And if you mention him on LinkedIn, you’ll have Stanford’s profile next to your profile 😉
Expect hard work if you’re serious about getting your degree (if you’re just taking courses, choose your own expectations). The conditions listed on the certification page are strict, so please check them.
There are many guides, there are Towards Data Science, there are books, and there are free videos on the Internet… But there are things that you can learn through supervised courses at the recognized institution.
It’s not up to you to pay for things or spend $5k without researching first, you can get a lot of this course for free or at least try the course before you buy it.
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It’s ridiculous how much stuff is available for free. Here is the full lecture on CS231n. Lecture notes are also available for other classes. Lecture notes for CS229 are basic information on “classical ML” for the book.
And of course, besides Stanford, there are other sources where you can learn about ML. Consider taking a Google Course. It’s more practice-based, and you don’t do all the math. If you take it, and you feel like you want to create more math and are ready to learn these concepts at a deeper level, move on to a more advanced program. Otherwise, keep hacking on cool ML-y stuff.
Now, I know, it’s hard to beat a credential from Stanford. Few schools have the awards, prestige, resources and faculty that Stanford provides. If you haven’t been to the Stanford Campus and live nearby, you need to check it out! There is even a Rodin Sculpture Garden.
However, if you live near, say, another good school that offers a similar program, consider applying to that school. Direct communication with TAs and other remote students has some advantages.
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Yes, SCPD policy discourages you from attending lectures and exams on campus. Even if you’re not “sure out of place” in the exam room, it’s never been a problem for me. I looked and found an empty space. TAs and teachers were happy to talk face-to-face instead of messing around with Zoom or other remote conferencing. However, I went to campus once only to find that my TA was at home, doing a video conference via Zoom.
In addition, some Poster Sessions where you present and present your project with posters are a good market. In particular the poster talk CS231n “Convolutional Neural Networks” is one: Waymo, Zoox, Cruise, and several other companies send their employees there.
The same can be said about other industry events: CVPR is said to have become not only a job fair but a full ML industry exhibition as well as a scientific conference.
No, you cannot get a Student ID so you will not get a discount. You will, however, have access to a digital library, and you can download the papers you need for your work from ACM, IEEE, etc. and other websites for free.
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And you will receive your @stanford.edu email throughout your course. Use it while you can.
Since Machine Learning requires a lot of GPU time, you can get credits on Microsoft Azure or Google Cloud for running GPU intensive calculations for assignments and projects. But if you have a gaming computer at home, you don’t have to. Last year, when I bought a new GPU, I could mostly ditch my old GeForce GTX 1070, which you can buy new for $300 (which is pretty old, as far as machine learning goes ). Remember, you spent $20,000 on tuition, so you’re guaranteed to save $300 for the GPU.
Even if you don’t have a gaming PC and only have a non-gaming laptop, consider doing an external GPU setup like the one I explained a year ago on the blog.
From the AI certification courses, here’s what I’ve covered (in the order you might be interested), with a more in-depth description to follow.
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CS231n Convolutional Neural Networks for Visual Recognition is the best Deep Learning and neural networks course I have taken. If you are interested in deep practical learning, take this course first. At the time of publishing this blog, registration for this course is open, so don’t miss your chance. Not only will you learn how to work in computer vision, but you’ll learn the basics of deep learning, starting with rendering and applying gradients and background scaling manually , and concludes by implementing proven architectures. (including the “nitty. -details” like building activaiton maps).
If this course was normal 5 years ago, it seems a bit outdated to me. I will not take it for the final update on the subject, but more for the basics.
Course that covers many AI topics including Graph Search Algorithms Evaluation (A-star), Reinforcement Learning (with a fun Pac-Man challenge where I got 4th place), Co-Processes Markov closure, Constraint satisfaction solving, and other “classical” Basic AI tools without much ML. If you think this course is easy because it is an “overview” course, don’t be fooled. You are expected to study deeply and demonstrate an understanding of it
Percy Liang taught the course; he is a good teacher and researcher; in fact our project for the CS224n course (see below) is an extension of his paper. 🙂
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CS224n Natural Language Processing with Deep Learning. I learned about Recurrent Neural Networks, LSTM, word vectors, and neural language models. In two of the assignments, you will implement a Neural Machine Translation component and train an encoder translation network to translate English into Spanish. You do this once with word input, and another time with CNNs. That’s crazy!! These were the most amazing achievements in the world 10 years ago and now you can do them
This is a great new course, and represents the state of the art in NLP when I took it a year ago. If you are interested in NLP, this course is a must. Out of all the courses, this was the best, freshest and most memorable for me.
AA228 Decision making under uncertainty. This is a CS/Aeronautics course that covers modeling and working with uncertainty in decision making and planning. In fact, it differs from those listed above and almost exclusively focuses on planning, Q-learning / SARSA, Monte-Carlo tree search methods, and part of Markov Co -close Processes.
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The most beneficial result for me was that I understood how to use Bayesian reasoning in practical situations. This course starts with the basics, and the instructor takes the approach of “if you don’t get the basics right, we might not even be talking about POMDP”. I can work about finally with conditional probabilities, and I can contribute to planning mission objectives at work. Stanford’s new master’s program
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