Many UK universities are struggling financially, but there's one option that is rarely discussed: replacing lecturers with artificial intelligence (AI) machines. This might sound like sci-fi – after all, the lists of occupations vulnerable to AI rarely include teaching, which is still seen as too creative for computers. But a growing database of information harvested from online courses – clickstreams, eye-tracking and even emotion-detection – could make AI lecturers a common feature in the near future. Forget robo-lecturers whirring away in front of whiteboards: AI teaching will mostly happen online, in 24/7 virtual classrooms. AI machines will learn to teach by ferreting out complex patterns in student behaviour – what you click, how long you watch, what mistakes you make, even what time of day you work best.

As if manufacturers didn't already have enough on their hands trying to find suitable applicants for their shop floors and R&D departments, the world of artificial intelligence is about to explode onto the scene. And when it does, the scramble for talent will only grow maddeningly tougher. This may sound like trouble, but there's a tremendous upside. According to a newly released study by the MAPI Foundation and the Information Technology and Innovation Foundation (ITIF), not only will AI enable machines to do a lot more--but it will also empower humans to do a lot more as well. That means an upsurge of new kinds of jobs related to developing new AI solutions, leading new AI business strategies and supervising AI implementations.

For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it's used in Computer Science. This specialization aims to bridge that gap, getting you up to speed in the underlying mathematics, building an intuitive understanding, and relating it to Machine Learning and Data Science. In the first course on Linear Algebra we look at what linear algebra is and how it relates to data. Then we look through what vectors and matrices are and how to work with them. The second course, Multivariate Calculus, builds on this to look at how to optimize fitting functions to get good fits to data.

The training and development of your workforce is vital to the achievement of digital transformation success for businesses. And today, more and more businesses are leveraging e-learning to educate their employees. The advantages for businesses using online learning platforms as opposed to traditional training methods are bountiful. First, it lowers business costs since one training session can be delivered to multiple people. Second, topics can be broken down into bite-sized chunks, meaning that employees do not need to spend lengthy periods of time away from their desks.

Machine learning is impacting countless industries, from the recent discovery of a black hole to improving healthcare, we are just scratching the surface. The retail industry is a prime example. Retailers and manufacturers are racing to figure out how they can employ machine learning to target specific consumers, monitor trends, and discover new pricing models. While retailers and manufacturers are doubling down on new ways to target and sell to consumers, Jia Rui Ong, a two-time Nanodegree program graduate, and his team are employing machine learning to help you, the consumer, find the best price for the clothing you desire. We recently had a chance to sit down with Jia Rui Ong and his team at Yux to discuss their product, as well as, our newly updated Machine Learning Nanodegree program.

Although corporate leaders have talked about skills gaps for years, the spread of automation and artificial intelligence is prompting some of the biggest companies -- including Amazon, JPMorgan Chase, SAP, Walmart, and AT&T, to name just a few -- to take action, not with small pilots but with comprehensive plans to retrain large segments of their workforces. These programs signal that the "future of work" is no longer an event on the distant horizon. Our latest research finds that the occupational mix of the economy is already shifting in ways that will accelerate over the next decade. Although we estimate that only 5% of all occupations can be fully automated, the activities in nearly all jobs will evolve. As intelligent machines take over many physical, repetitive, or basic cognitive tasks, the work that remains will involve both more technical and digital skills and more personal interaction, creativity, and judgment.

On the day I met Sebastian Thrun in Palo Alto, the State of California legalized self-driving cars. Gov. Jerry Brown arrived at the Google campus in one of the company's computer-controlled Priuses to sign the bill into law. "California is a big deal," said Thrun, the founder of Google's autonomous-car program, "because it tends to be hard to legislate here." He said it with typical understatement. An idea that was in its technological infancy a decade ago, when Thrun and his colleagues were racing to develop a vehicle that could drive itself more than a few miles on a desert test course, was now being officially sanctioned by the country's most populous state.

The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance. The specialization aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) mapping the problem on a general landscape of available ML methods, (2) choosing particular ML approach(es) that would be most appropriate for resolving the problem, and (3) successfully implementing a solution, and assessing its performance. The specialization is designed for three categories of students: · Practitioners working at financial institutions such as banks, asset management firms or hedge funds · Individuals interested in applications of ML for personal day trading · Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance. The modules can also be taken individually to improve relevant skills in a particular area of applications of ML to finance.

Online 1 on 1 class is created for more personalized learning experience. It demands a large number of teaching resources, which are scarce in China. To alleviate this problem, we build a platform (marketplace), i.e., \emph{Dahai} to allow college students from top Chinese universities to register as part-time instructors for the online 1 on 1 classes. To warn the unqualified instructors and ensure the overall education quality, we build a monitoring and alerting system by utilizing multimodal information from the online environment. Our system mainly consists of two key components: banned word detector and class quality predictor. The system performance is demonstrated both offline and online. By conducting experimental evaluation of real-world online courses, we are able to achieve 74.3\% alerting accuracy in our production environment.

Artificial intelligence (AI) and machine learning are amazing technologies that are revolutionizing practically every field of human activity. Intelligent machines can assist or downright substitute humans in literally all tasks, from business and commerce to health care, environment, communications, and any endeavors we can imagine. Understanding AI, while this tech is still in its prime days, is a great way to boost a career in technology. Professionals who can build thinking machines able to get the most value from the immense vaults of unstructured data currently floating around are highly sought after by employers across the globe. Whether you already have experience in the technology field or you are a student with little or no background in AI and programming, there are many online courses available to outpace your competition and find the job of your life.