Was one of your New Year’s resolutions to build up your knowledge, skills and talents for the new digital world? If so, there are plenty of online options to help you achieve your goals, and at no cost to you, from the crop of MOOCs (massive open online courses) that’s sprung up.
The Semantic Web Blog scoured some of them to present you with some possible courses of study to consider in pursuit of your goals:
- Data scientists-in-training, Johns Hopkins Bloomberg School of Public Health assistant professor of biostatistics Jeff Leek wants to help you get a leg up on Big Data – and the job doors that understanding how to work with it opens up – with this applied statistics course focusing on data analysis. The course notes that there’s a shortage of individuals with the skills to find the right data to answer a question, understand the processes underlying the data, discover the important patterns in the data, and communicate results to have the biggest possible impact, so why not work to become one of them and land what Google chief economist Hal Varian reportedly calls the sexy job for the next ten years – statistician (really). The course starts Jan. 22.
- We’ve seen a lot about robots in the news over the last month, from the crowd-funded humanoid service robot Roboy, the brainchild of the Artificial Intelligence Laboratory of the University of Zurich, to Vomiting Larry, a projectile vomiter developed to help scientists to better understand the spread of noroviruses. If you’d like to learn about what’s behind robots that can act intelligently (sorry, Larry, but you might not qualify here), you want to learn more about AI. And you can, with a course starting Jan. 28 taught by Dr. Gerhard Wickler and Prof. Ausin Tate, both of the University of Edinburgh.
- Siri, where can I go to find out more about natural language processing? One option: Spend ten weeks starting February 11 learning about NLP with Michael Collins, the Vikram S. Pandit Professor of Computer Science at Columbia University. Students will have a chance to study mathematical and computational models of language, and the application of these models to key problems in natural language processing, with a focus on machine learning methods.
- edX doesn’t offer as many courses as Coursera does, but it also is providing an AI option for those interested in how they can play a part in developing household robots, self-driving cars and intelligent computer systems in general. Taught by Dan Klein, associate professor of computer science at the University of California, it starts Feb. 18.
- SaaS (software-as-a-service) is leaving a footprint on software apps of every variety, including the semantic space. CS169.2x is the second half of the University of California, Berkeley’s semester long course on Software as a Service, beginning Feb. 15, bringing students up to speed on creating more sophisticated SaaS apps, monitoring real-world user performance, providing security for customer data and more.
- No surprise that AI is alive and well at tech-focused Udacity – you can take an introductory course taught by Sebastian Thrun, research professor at Stanford University and Google research director Peter Norvig, or one that will teach you how to program a robotic car. That’s taught by Thrun, as well, who’s also a Google Fellow. Google, of course, has been out in-front of the self-driving car wave – and just this past fall these cars became explicitly legal to drive in California. Thrun previously developed a robot, Stanley, that drove itself in a race through the Mojave Desert (see a video here). Today, you can stop by and say hi to Stanley at the Smithsonian.
- If there’s one thing that’s common in the semantic space, it’s that there a lot of start-ups out there trying to capitalize on the technology in creating cool new services for consumers and businesses. If that’s your dream, perhaps you should trundle over to the course on how to build a startup, taught by Silicon Valley entrepreneur Steve Blank. He didn’t start up any semtech companies – CRM vendor E.piphany and semi-conductor companies Zilog and MIPS Computers were his babies, among a few others – but the value is in the how, not the what.
Good luck meeting your goals!
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