Lectures translation is a case of spoken language translation and there is a lack of publicly available parallel corpora for this purpose. To address this, we examine a language independent framework for parallel corpus mining which is a quick and effective way to mine a parallel corpus from publicly available lectures at Coursera. Our approach determines sentence alignments, relying on machine translation and cosine similarity over continuous-space sentence representations. We also show how to use the resulting corpora in a multistage fine-tuning based domain adaptation for high-quality lectures translation. For Japanese--English lectures translation, we extracted parallel data of approximately 40,000 lines and created development and test sets through manual filtering for benchmarking translation performance. We demonstrate that the mined corpus greatly enhances the quality of translation when used in conjunction with out-of-domain parallel corpora via multistage training. This paper also suggests some guidelines to gather and clean corpora, mine parallel sentences, address noise in the mined data, and create high-quality evaluation splits. For the sake of reproducibility, we will release our code for parallel data creation.

Jennifer Turner's algebra classes were once sleepy affairs and a lot of her students struggled to stay awake. She uses Bakpax, which can read students' handwriting and auto-grade schoolwork, and she assigns lectures for students to watch online while they are at home. Using the program has provided Turner, 41, who teaches at the Gloucester County Christian School in Sewell, N.J., more flexibility in how she teaches, reserving class time for interactive exercises. "The grades for homework have been much better this year because of Bakpax," Turner said. "Students are excited to be in my room, they're telling me they love math, and those are things that I don't normally hear."

You all know of Coursera's machine learning course and Andrew Ng's deep learning specialization. You even talk about fast.ai, These are all excellent resources to learn data science, but I want to make you aware of a lesser-known, yet superb, set of courses with which you can augment your knowledge in only a few hours. You've probably heard of Kaggle. You most likely have even participated in a challenge and maybe uploaded some kernels, but did you know Kaggle also provides data science education?

EU presidency extends access to free AI course across EU Jan Petter Myklebust 13 December 2019 European Union employment ministers have endorsed a proposal from Finland's Presidency of the Council of the EU to provide European citizens with free access to a successful online course on basic artificial intelligence (AI), developed and run by the University of Helsinki in partnership with private firm Reaktor. To achieve this, the course on "Elements of AI" will be made available in all official EU languages. The Finnish government will fund the project with €1.7 million (US$1.9 million) from Finland's Ministry of Economic Affairs and Employment as part of the EU Council presidency's effort to democratise awareness of AI and develop people's skills for jobs of the future. At the launch of the initiative in Brussels on 10 December, Finland's Minister of Employment Timo Harakka said: "Our investment has three goals: we want to equip EU citizens with digital skills for the future; we wish to increase practical understanding of what artificial intelligence is; and by doing so, we want to give a boost to the digital leadership of Europe." "As our presidency ends, we want to offer something concrete. It's about one of the most pressing challenges facing Europe and Finland today: how to develop our digital literacy," Harakka said.

Last year, Finland launched a free online crash course in artificial intelligence with the aim of educating its citizens about the new technology. Now, as a Christmas present to the world, the European nation is making the six week program available for anyone to take. Finland is relinquishing the EU's rotating presidency at the end of the year, and decided to translate its course into every EU language as a gift to citizens. But there aren't any geographical restrictions as to who can take the course, so really it's to the world's benefit. The course certainly proved itself in Finland, with more than 1 percent of the Nordic nation's 5.5 million citizens signing up. The course, named Elements of AI, is currently available in English, Swedish, Estonian, Finnish, and German.

News that Pearson, the world's largest textbook publisher, is phasing out print publications for higher education to adopt a resolutely digital-first policy may signal an eventual full stop for traditional book learning. In the view of Mike Buchanan, executive director of HMC, which represents independent school head teachers, digital education will unlock a less rigid approach to classroom-based learning, as well as enable closer collaboration with pupils' families. "In a growing number of schools, the use of modern management information and recording systems to harvest details of classroom activities and pupil progress is already allowing parents to access and aggregate their child's attainment records," he says. "In the future, this will no doubt see the traditional termly report being replaced by daily digital updates." Mr Buchanan predicts individual academic achievement will be charted by artificial intelligence (AI), rather than by a plethora of exams, and argues that for teachers disenchanted by the current need to "teach to the test", the freedom to pursue a more rounded curriculum will foster a new optimism.

Andrew Ng is most of the world's most prominent AI scientist's and educators. On this episode of CxOTalk, he shares practical advice for adopting AI in the enterprise. Dr. Andrew Ng is a globally recognized leader in AI (Artificial Intelligence). He has helped two of the world's leading technology companies in their "AI transformation": He was Chief Scientist at Baidu, where he led the company's 1300 person AI Group and was responsible for driving the company's global AI strategy and infrastructure. He was also the founding lead of the Google Brain team.

Organisations across the world are witnessing talent shortage in AI and are struggling to hire competent employees in this ever-changing landscape. Since every company is striving for a data-driven approach, there is a rise in the integration of technologies such as artificial intelligence, data science, among others, to achieve business objectives. However, the absence of superior talent in the market is impeding the growth of firms. In fact, research tells us that 85% of AI projects fail due to risk, confusion and lack of upskilling in the employees. "It is very challenging to get excellent developers in the space even though AI and Data Science has been the most sought-after skill," says Gaurav Mehrotra, vice president and head of business data solutions at Innoviti Payment Solutions. A recent report published by noted online learning platform Coursera states that out of the 45 million learners on the platform, two million enrolled in AI-based content in 2019.

Once a user logs into an online shopping website, knowing whether the person will make a purchase or not holds a massive economical value. A lot of current research is focused on real-time revenue predictors for these shopping websites. In this article, we will start building a revenue predictor for one such website. In this Data Science Machine Learning project, we will create a Real-time prediction of online shoppers' purchasing intention Project using Apache Spark Machine Learning Models using Logistic Regression, one of the predictive models. Databricks lets you start writing Spark ML code instantly so you can focus on your data problems.

For India's online learners, 2019 was the "Year of AI." Artificial Intelligence (AI) emerged as the most popular subject among e-learners, accounting for nearly two million enrollments in the last year alone, according to online learning platform Coursera's latest learner trends released yesterday (Dec. The analysis included 45 million learners, including five million Indians, on the platform. AI became accessible to the masses with AI For Everyone, which was launched in February this year by deeplearning.ai, Taught by Ng himself, AI For Everyone is described as a "primer course, geared toward non-technical learners--from marketers and designers to financiers and CEOs." It was the fifth most popular Coursera course of the year globally, and the fourth most popular in India.