Stanford Offers Free Online Courses in CS, Robotics
Well, I just found out what I’m doing this weekend. Stanford University has launched 10 online courses in the areas of computer science and electrical engineering. Free to download, each course includes lectures (video and transcripts), handouts, assignments and exams. You don’t have to register. You won’t be able to interact with the professor of the course but you can with the other virtual students doing the coursework.
The 10 current courses are divided into three categories: Introduction to Computer Science, Artificial Intelligence and Linear Systems and Optimization.
Introduction to Computer Science
This course is the largest of the introductory programming courses and is one of the largest courses at Stanford. Topics focus on the introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing.
Programming Methodology teaches the widely-used Java programming language along with good software engineering principles. Emphasis is on good programming style and the built-in facilities of the Java language. The course is explicitly designed to appeal to humanists and social scientists as well as hard-core techies. In fact, most Programming Methodology graduates end up majoring outside of the School of Engineering.
Topics: Abstraction and its relation to programming. Software engineering principles of data abstraction and modularity. Object-oriented programming, fundamental data structures (such as stacks, queues, sets) and data-directed design. Recursion and recursive data structures (linked lists, trees, graphs). Introduction to time and space complexity analysis. Uses the programming language C++ covering its basic facilities.
Advanced memory management features of C and C++; the differences between imperative and object-oriented paradigms. The functional paradigm (using LISP) and concurrent programming (using C and C++). Brief survey of other modern languages such as Python, Objective C, and C#.
Artificial Intelligence
Topics: robotics foundations in kinematics, dynamics, control, motion planning, trajectory generation, programming and design.
Natural Language Processing (no video for this one) (Correction: video can’t be downloaded but it is there on the site. Thanks, Christopher!)
This course is designed to introduce students to the fundamental concepts and ideas in natural language processing (NLP), and to get them up to speed with current research in the area. It develops an in-depth understanding of both the algorithms available for the processing of linguistic information and the underlying computational properties of natural languages. Wordlevel, syntactic, and semantic processing from both a linguistic and an algorithmic perspective are considered. The focus is on modern quantitative techniques in NLP: using large corpora, statistical models for acquisition, disambiguation, and parsing. Also, it examines and constructs representative systems.
Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control.
The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.
Linear Systems and Optimization
The Fourier Transform and its Applications
Topics include: The Fourier transform as a tool for solving physical problems. Fourier series, the Fourier transform of continuous and discrete signals and its properties. The Dirac delta, distributions, and generalized transforms. Convolutions and correlations and applications; probability distributions, sampling theory, filters, and analysis of linear systems. The discrete Fourier transform and the FFT algorithm. Multidimensional Fourier transform and use in imaging. Further applications to optics, crystallography. Emphasis is on relating the theoretical principles to solving practical engineering and science problems.
Introduction to Linear Dynamical Systems
Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution and transfer matrix descriptions. Control, reachability, state transfer, and least-norm inputs. Observability and least-squares state estimation.
Concentrates on recognizing and solving convex optimization problems that arise in engineering. Convex sets, functions, and optimization problems. Basics of convex analysis. Least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems. Optimality conditions, duality theory, theorems of alternative, and applications. Interiorpoint methods. Applications to signal processing, control, digital and analog circuit design, computational geometry, statistics, and mechanical engineering.
Continuation of Convex Optimization I. Subgradient, cutting-plane, and ellipsoid methods. Decentralized convex optimization via primal and dual decomposition. Alternating projections. Exploiting problem structure in implementation. Convex relaxations of hard problems, and global optimization via branch & bound. Robust optimization. Selected applications in areas such as control, circuit design, signal processing, and communications. Course requirements include a substantial project.
I luvz free learning stuff
[...] Visto en Moue Magazine. [...]
wow, nice stuff!
I love robots, but i am not able learn because of no resources…..teach me please
May I recommend my Free Video Lecture blog as well? I have been collecting video lectures there for more than 2 years now. Take a look
Wow, I would highly recommend this series. Good stuff.
JT
http://www.FireMe.To/udi
MIT has already been doing this, and a lot more, for years. Almost all their courses are available to view for free.
ocw.mit.edu
MIT has already been doing this, and a lot more, for years. Almost all their courses are available to view for free.
Thanks for that link, RT. I read last night about MIT’s offerings while I was reading about Stanford’s. I’m going to check their stuff out as well.
good news ! if the video can be downloaded
[...] mentioned in the comments section of the Stanford University post that MIT has been offering free online coursework for years. I wasn’t aware of that before [...]
Thanks so much for posting the links to these classes, these are very valuable resources and I plan on looking into several of them. I just wanted to point out one thing that you may want to change however, and that’s that the NLP class does have video lectures available for viewing at the URL you linked to in the post. So, you may want to update the NLP portion of the post and just remove the parenthetical comment beside the title.
Thanks again for the post, very useful stuff!
Thanks, Christopher! I had read their footnote to mean that no video was available at all when they only meant it wasn’t available for download. I made the correction.
[...] design, signal processing, and communications. Course requirements include a substantial project. -Moue Magazine Stanford Offers Free Online Courses in CS, Robotics __________________ The Ultimate Gameboot Thread – Gameboots and More! – [...]
You can get many more free online courses from top-notch universities right here.
http://www.oculture.com/2007/07/freeonlinecourses.html
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Thank you for supplying this.
I have just one question: this is not a certified thing, right? As in, I learn, then get evaluation and get a certification that I know what I learned?
Thank you, again!
José, it isn’t a certification thing, unfortunately. It is basically the high tech, free equivalent of auditing a class. You don’t receive anything for doing it except the knowledge.
Thank you for your reply miss Brandy.
You’re welcome!
[...] Moue Magazine – Free online Standford courses in CS and Robotics [...]
Stanford University has launched 10 online courses in the areas of computer science and electrical engineering. Free to download, each course includes lectures (video and transcripts), handouts, assignments and exams.
Hello I’m interested in these free online courses from Stanford.
[...] Moue Magazine »Stanford Offers Free Online Courses in CS, Robotics The 10 current courses are divided into three categories: Introduction to Computer Science, Artificial Intelligence and Linear Systems and Optimization. (tags: video stanford programming online lectures free education) [...]
I love robot very much, but I have no correlative professional knowledge, and I hope these courses could help the people who are same as me. Thanks for Stanford University.
oh dear, now I’ll have to put off my projects for another few months while I go through these!
great list thanks
I am 3 or 4 lessons away from finishing cs106a…great way to learn java. i love the instructor Mehran Sahami.
Leslie, I’m at the beginning of that same course. I agree about the professor. He’s awesome.
Free online classes at Stanford University…
from Moue Magazine
Stanford University has launched 10 online courses in the areas of computer science and electrical engineering. Free to download, each course includes lectures (video and transcripts), handouts, assignments and exams. You don’t …
good
[...] http://www.mouemagazine.com/blog/2008/09/stanford-offers-free-online-courses-in-cs-robotics/ [...]
I don’t think that the title of your post is appropriate. IMO the phrase “free courses” is wrong, it is “free course ware” or “free course material” or similar. They are not offering free courses!
Hello,I am a Chinese. love robot MIT as great as Stanford
Thanks for Stanford University
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