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Stepz Kottayam
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Shaping the Future
Shaping the Future

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Microsoft launches entry-level software development and AI courses

Microsoft today launched two new courses in its online education program for developers: an entry-level software development class and an AI course for more advanced developers who want to expand their knowledge of machine learning. It’s no secret that there aren’t enough data scientists and machine learning developers available to fulfill the current demand. It’s no surprise then that a number of large companies have started to teach the fundamentals of these disciplines to their existing employees and starting today, anybody can take the AI courses that Microsoft first developed for its own employees. The Microsoft Professional Program for Artificial Intelligence is available for free on edX.org, though you can also opt to pay for a certificate. Each course runs for three months and starts at the beginning of the quarter. Unsurprisingly, there’s a bit of a focus on Azure and Microsoft’s Cognitive Services here (and you need an Azure account), but otherwise the course is agnostic to the operating system you run. The overall program consists of ten courses that range from introductions to AI and Python for data science, to a class on ethics for AI developers and lots of hands-on work with training models. Most of the ten required courses should take about eight to sixteen hours to complete.
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Together with Vodafone Business, Continental Tire has launched the ContiConnect #IoT platform. Companies can use it to monitor the condition of their commercial vehicles’ tires. Get your free ticket here: http://fal.cn/4bAU #vfv18 #hm18
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Learning to write programs that generate images

Through a human’s eyes, the world is much more than just the images reflected in our corneas. For example, when we look at a building and admire the intricacies of its design, we can appreciate the craftsmanship it requires. This ability to interpret objects through the tools that created them gives us a richer understanding of the world and is an important aspect of our intelligence. We would like our systems to create similarly rich representations of the world. For example, when observing an image of a painting we would like them to understand the brush strokes used to create it and not just the pixels that represent it on a screen. In this work, we equipped artificial agents with the same tools that we use to generate images and demonstrate that they can reason about how digits, characters and portraits are constructed. Crucially, they learn to do this by themselves and without the need for human-labelled datasets. This contrasts with recent research which has so far relied on learning from human demonstrations, which can be a time-intensive process.
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