|April MOOCs in Computer Science|
|Written by Sue Gee|
|Monday, 07 April 2014|
The MOOC format seems particularly suited to computer science and every month seems to brings new ones. This month's round up includes a new provider, courses at several different levels, and a couple of apps to help you keep up.
Coursera has now released an Android version of its app that lets students browse courses and catch up on lectures anytime, anywhere such as on your commute or on the treadmill.
This is the counterpart of the iOS app launched late last year and provides lots of capabilities from enrolling in courses to streaming videos.
Streaming Udacity videos is also possible with Udacity for iPad which is the first of a planned series of mobile apps for its courses. It lets you watch lectures and view courseware, take quizzes and complete programming exercises.
The latest additions to the Udacity catalog include the first of three on Machine Learning from the Georgia Tech Masters in CS. It lasts approximately 1 month with a workload of 6 hours per week and the summary notes:
[it] is different in structure compared to most Udacity CS courses. There is a final project at the end of the course, and there are no programming quizzes throughout this course.
Udacity offers two options - you can follow the courseware for free while enrollment, which includes the project and personal guidance from a coach costs $150 per month.
The three Machine Learning courses are also distinctive in being "taught as a lively and rigorous dialogue" by its two instructors Professor Charles Isbell (Georgia Tech) and Professor Michael Littman (Brown University).
Topics covered in Machine Learning 1 - Supervised Learning include: Decision trees, neural networks, instance-based learning, ensemble learning, computational learning theory and Bayesian learning. In the final project, students will be expected to explore important techniques in Supervised Learning, and apply their knowledge to analyze how algorithms behave under a variety of circumstances.
Although listed by Udacity as "Intermediate", sampling the first couple of lectures it seems undemanding compared to Andrew Ng's Stanford University Machine Learning course which is currently underway on Coursera, which wasn't what I was expecting from a class at Master's level.
Also at Intermediate level, Udacity has introduced a new course Mobile Web Development. Although you can follow its courseware for free at any time the full course, which is also self-paced, is currently at capacity and if you want to enroll you'll have to wait for a place to become available.
If you are looking for something a little different edX has a new course that starts May 6th. Autonomous Navigation for Flying Robots sets out to introduce the basic concepts for autonomous navigation with quadrotors, including topics such as probabilistic state estimation, linear control, and path planning.
Meanwhile in April there's another chance to catch CS169.1x: Engineering Software as a Service which teaches the fundamentals of software engineering using Agile techniques to develop Software as a Service using Ruby on Rails.
Several Cousera courses that we've covered before are restarting during April, including Functional Programming Principles in Scala (April 25th) and Malicious Software and its Underground Economy (April 28th).
A course that's new to the Coursera platform this month, and suitable for those new to programming, is Programming for Everybody. Starting on April 10th it is a 10-week course requiring 2-4 hours per week it is being taught by Chuck Severance, whose Internet course was also aimed at a wide audience and had no pre-requisites. It is designed as a first programming course using Python programming language and simple data analysis programming exercises which can be done in the browser.
Programming knowledge is recommended for a course starting on Aril 22nd from Europe-based MOOC provider Iversity. Modelling and Simulation using MATLAB is an interdisciplinary course teaches you to simulate models for a wide range of applications using MATLAB – a high-level programming language and an environment for numerical computation and visualization.
The course, which is in English and taught by a team led by Georg Fries, Professor of Digital Signal Processing in the Department of Engineering at RheinMain University of Applied Sciences, Wiesbaden is divided into two sections. The first part teaches the basics and is mandatory for all participants. In the second part students can select which application area to work on
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|Last Updated ( Monday, 07 April 2014 )|