SINGAPORE - Students fresh out of secondary school will from April next year be able to take up a full-time diploma programme in applied artificial intelligence (AI) and analytics at Singapore Polytechnic (SP). The polytechnic, which will take up to 80 students in the first batch, will be the first of the five polys here to offer such a programme. Currently, such courses are offered as specialist diploma programmes, which are for existing diploma or degree holders - usually adult learners - to deepen their knowledge and skills. The new diploma course was launched on Friday (Oct 18) during the inaugural SP AI Symposium held at the Concorde Hotel, where there was a showcase of AI-related projects done by students and industry partners. Students enrolled in the programme will learn to apply AI and big data to solve current challenges across industries such as finance, information technology and commerce.

As you know a perceptron serves as a basic building block for creating a deep neural network therefore, it is quite obvious that we should begin our journey of mastering Deep Learning with perceptron and learn how to implement it using TensorFlow to solve different problems. In case you are completely new to deep learning, I would suggest you to go through the previous blog of this Deep Learning Tutorial series to avoid any confusion. Basically, a problem is said to be linearly separable if you can classify the data set into two categories or classes using a single line. On the contrary, in case of a non-linearly separable problems, the data set contains multiple classes and requires non-linear line for separating them into their respective classes. Let us visualize the difference between the two by plotting the graph of a linearly separable problem and non-linearly problem data set:Since, you all are familiar with AND Gates, I will be using it as an example to explain how a perceptron works as a linear classifier.

The United Arab Emirates (UAE) will host graduate-level courses in artificial intelligence (AI) at a new university in its capital, Abu Dhabi. The Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) aims to enable students, businesses and governments to increase the use of AI technology. Sultan Ahmed Al Jaber, UAE minister of state, said: "Mohamed bin Zayed University of Artificial Intelligence is an open invitation from Abu Dhabi to the world to unleash AI's full potential. "AI is already changing the world, but we can achieve so much more if we allow the limitless imagination of the human mind to fully explore it." The university, which will be located in Masdar City, Abu Dhabi, is tapping experience from across the world with a board of trustees from respected universities in the UK, the US and China. MBZUAI will offer postgraduate (MSc and PhD) courses in computer vision, machine learning and natural language processing. It is now open for admission to the academic year 2021-2022. Registration will begin in August 2020, with the first students starting the following month. All graduate students admitted will be offered a full scholarship and other benefits, including a monthly allowance, health insurance and accommodation. It will also help graduates find work and internships with local and global companies. MBZUAI has partnered with the Abu Dhabi-based Inception Institute of Artificial Intelligence for the supervision of PhD students and curriculum development, as well as collaborative research. Michael Brady, interim president at MBZUAI, said: "Following decades of research into machine learning and artificial intelligence, we are now at a turning point in the widespread application of advanced intelligence.

"The unpredictability of the outcomes of today's decision models often stems from an inability to properly capture and account for the uncertainty factors linked to these models' "behavior" in a business context. Decision intelligence provides a framework that brings together traditional and advanced techniques to design, model, align, execute, monitor and tune decision models." A growing number of companies are using DI to guide their decision-making including Google, IBM, Microsoft and many others across sectors. This intensive, one-day course will provide a hands-on, interactive, deep dive into DI for tehcnical and non-technical professionals. This is the only Decision Intelligence course currently available in New York City, being taught by one of the leading pioneers in the field, Dr. Lorien Pratt! "Curious to know what the psychology of avoiding lions on the savannah has in common with responsible AI leadership and the challenges of designing data warehouses?

Facebook's head of artificial intelligence, Yann LeCun, seems to fit that profile to a T. "I work mostly by intuition," he writes in When the Machine Learns, a new book that is part biography, part science lecture, part AI history, published Wednesday in French as Quand la machine apprend. "I project in my head the borderline cases, that which Einstein called the'thought experiments'," writes LeCun. LeCun is animated on stage, clearly energized by trying to convey things at the edges of AI that have come from his thought experiments. That ability to imagine something that doesn't exist, perhaps at the limit of what's generally thought feasible, is the mark of engineers and innovators. LeCun is something of a rarity among the AI crowd, a scientist who is at home in algorithm design but also has one foot firmly in computer engineering.

UC Berkeley Assistant Professor Zachary Pardos and his team have developed a machine learning approach that promises to help more community college students position themselves to transfer and succeed at four-year colleges and universities. Along the way, they've discovered that considering course enrollment patterns -- or the classes that students take before, along with, and after a particular course -- can help provide a more complete picture of what courses should "count" when students transfer. Roughly 80% of community college students aim to continue their education at four-year institutions, but the vast majority never make the transfer. Contributing to the problem are the complexities of "articulation," or determining which course at one institution will count for credit at another. This entails assessing the similarity of thousands, or potentially even millions, of pairs of courses, an endeavor that's impossible to comprehensively achieve and keep current across all institutions manually.

The UAE has set up an artificial intelligence university, claimed to be the first in the world, in Abu Dhabi. The Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) was inaugurated on October 17 and it offers courses for undergraduate students. It is also accepting applications for its first masters and PhD programmes this month, with classes scheduled to begin on September 20 next year. All admitted students will be given full scholarship plus benefits such as a monthly allowance, health insurance and accommodation. "AI is already changing the world, but we can achieve so much more if we allow the limitless imagination of the human mind to fully explore it. The university will bring the discipline of AI into the forefront, moulding and empowering creative pioneers who can lead us to a new AI-empowered era," said Sultan Ahmed Al Jaber, UAE Minister of State, who has been appointed Chair of the MBZUAI Board of Trustees and is spearheading the university's establishment.

HYDERABAD: Data acquisition, Python and neutral networks are few topics that students of classes 8 and 9 will be exposed to as part of the artificial intelligence (AI) curriculum, which many Central Board of Secondary Education (CBSE)-affiliated city schools are set to adopt from academic year 2020-21. Early this year, the CBSE had proposed to offer AI as a skill-set to keep up with the changing technology. Following this, the CBSE recently released the AI curriculum facilitator's handbook, which details various topics such as AI ethics, problem scoping, data acquisition, exploration and modelling. Curated by Intel, the curriculum will not only make students inquisitive but will also teach them basic tools that are required to develop AI-based solutions. For example, in Unit 1, students will be asked to prepare a dream smart home by including any gadgets or devices that they think will make their homes unique.

In this tutorial, you will learn how to use Cyclical Learning Rates (CLR) and Keras to train your own neural networks. Using Cyclical Learning Rates you can dramatically reduce the number of experiments required to tune and find an optimal learning rate for your model. Last week we discussed the concept of learning rate schedules and how we can decay and decrease our learning rate over time according to a set function (i.e., linear, polynomial, or step decrease). Cyclical Learning Rates take a different approach. In practice, using Cyclical Learning Rates leads to faster convergence and with fewer experiments/hyperparameter updates.