Learn Web Application Engineering by the co-founder of Reddit

If you haven’t joined an online course already now is your chance! Udacity has listed several new courses coming up mid-April including Web Application Engineering taught by Steve Huffman, the co-founder of Reddit. Udacity currently has two active courses CS101 and CS373 that you can jump into today for free.  It’s not just Udacity but Coursera with many courses running now or will be running shortly, and let’s not forget MITx.

The first of these free online courses were started in October of 2011: AI Class, Machine Learning and Introduction To Databases. They were run by Stanford professors Sebastian Thrun, Andrew Ng, and Jennifer Widom respectively.

Sebastian Thrun, along with several other co-founders, then created their own company called Udacity. Thrun’s methodology is based on the idea of iterative progression: you may get a C in college and be done with it, but with Thrun and Udacity you may get a C, have to try again, and try again until you understand the material and can get an A. Courses are taught by Stanford professors and other passionate guests; mostly using youtube videos and a built-in python interpreter, which leads to an intuitive and fun experience.

At the same time Professor Andrew Ng, along with Professor Daphne Koller  created their own company Coursera.  They are currently offering tons of free online courses taught by professors from Stanford, UofM, and UC Berkeley. Many of the Coursera and Udacity courses overlap.

MITx has launched it’s first course Circuits and Electronics with world re-known professors Anant Argwal , Gerald Sussman (author of SICP, and Scheme programming language), and Piotr Mitros.

There is another MIT endeavor not related to MITx. It is that of Professor Pritchards’ Introductory Physics course running on the MIT RELATE platform which like all others you still have time to register for.

If you’re anything like me you run a tight schedule, so it’s a good thing that most courses will be repeated every ‘term’. The professors improve on every iteration of their classes so you can only expect them to get better, and already the quality is outstanding. Overall it’s a great system and I love the fact there are multiple players from big schools engaging in this method of education. It could lead to something revolutionary if it hasn’t already. If it’s all a bit much I’ve included short descriptions, links, and video where available, for all relevant courses below.

I think everyone should at least dip their toes into one class from Udacity and one from Coursera, you never know where it could lead you or how it could change your context.

 

UDACITY

CS 101 – BUILDING A SEARCH ENGINE
For non-programmers learning to program and develop a minimal search engine in python. Taught by Professor David Evans, a great teacher.

CS 253 – WEB APPLICATION ENGINEERING
How the web works, managing state, security, integration, scalability, more… – Taught by Steve Huffman (co-founder of Reddit, Hipmunk)

CS 262 – PROGRAMMING LANGUAGES
Implement a limited javascript interpeter using python while learning lexical analysis, parsing, and more … – Taught by Professor Westley Weimer

CS 373 – PROGRAMMING A ROBOTIC CAR
Working in python and dealing with probabilities, sensors, path finding, more … – Taught by Professor Sebastian Thrun

CS 387 – APPLIED CRYPTOGRAPHY
Symmetric/Asymmetric encryption, Public-key protocols, Secure computation, more… -Taught by Professor David Evans

Under development:
Theory of Computation, Operating Systems, Computer Networks, Distributed Systems, Computer Security, Algorithms and Data Structures, Software Engineering Practices

 

MITx

6.002x CIRCUITS & ELECTRONICS
Serves as a first course in electrical engineering or electrical engineering and computer science – Taught by Professor Anant Agarwal, Professor Gerald Sussman, Piotr Mitros

 

MECHANICS ONLINE (SPRING 2012 MIT RELATE)
Introductory Newtonian Mechanics with some calculus. “We’ll train you to concentrate on planning and understanding the solution rather than focusing on obtaining the answer. ” – Taught by Professor Pritchard

 
COURSERA

MODEL THINKING

From the game of life to societal models of rioting behavior, modeling will help you become a better thinker – Professor Scott E. Page (University of Michigan)

Model Thinking

NATURAL LANGUAGE PROCESSING

From spelling and grammar correction in word processors to machine translation on the web, from email spam detection to automatic question answering, NLP is everywhere – Taught by Professor Dan Jurafsky (Stanford) and Professor Christopher Manning (Stanford)

Natural Language Processing

GAME THEORY

Learn modeling of conflict among nations, political campaigns, competition among firms, and trading behavior in markets such as the NYSE. – Taught by Professor Matthew O. Jackson (Stanford) and Professor Yoav Shoham (Stanford)

Game Theory

PROBABILISTIC GRAPHICAL MODELS

Learn algorithms for using a PGM to reach conclusions about the world from limited and noisy evidence, and for making good decisions under uncertainty and more. – Taught by Professor Daphne Koller (Stanford)

Probabilistic Graphical Models

CRYPTOGRAPHY

Learn how two parties who have a shared secret key can communicate securely when a powerful adversary eavesdrops and tampers with traffic and more. – Taught by Professor Dan Boneh (Stanford)

Cryptography

DESIGN AND ANALYSIS OF ALGORITHMS I

Learn several fundamental principles of algorithm design. You’ll learn the divide-and-conquer design paradigm, with applications to fast sorting, searching, and multiplication. Learn the answers to questions such as: How do data structures like heaps, hash tables, bloom filters, and balanced search trees actually work, anyway? – Taught by Professor Tim Roughgarden (Stanford)

Design and Analysis of Algorithms I

SOFTWARE AS A SERVICE

Learn engineering fundamentals for long-lived software using the highly-productive Agile development method for Software as a Service (SaaS) using Ruby on Rails – Taught by Professor Armando Fox (UC Berkeley) and Professor David Patternson (UC Berkeley)

Software as a Service

COMPUTER VISION

Learn about remarkable successes of computer vision – capabilities such as face detection, handwritten digit recognition, segmenting out organs or tissues in biological images and more – Taught by Professor Jitendra Malik (UC Berkeley)

Computer Vision

Under development:
CS 101, Machine Learning, Human-Computer Interaction, Making Green Buildings, Information Theory, Anatomy, Computer Security

 

  • http://twitter.com/hamiltonkb Kevin Browne

    Great resource you’ve made here Alex!