This paper considers a variant of the classical online learning problem with expert predictions. Our model's differences and challenges are due to lacking any direct feedback on the loss each expert incurs at each time step $t$. We propose an approach that uses peer assessment and identify conditions where it succeeds. Our techniques revolve around a carefully designed peer score function $s()$ that scores experts' predictions based on the peer consensus. We show a sufficient condition, that we call \emph{peer calibration}, under which standard online learning algorithms using loss feedback computed by the carefully crafted $s()$ have bounded regret with respect to the unrevealed ground truth values. We then demonstrate how suitable $s()$ functions can be derived for different assumptions and models.

After Google Earth, Google Forms is the Google product that I get the most excited about helping other teachers use. From gathering survey data to organizing event registration to creating online quizzes there are lots of things that can be done efficiently if you know how to use Google Forms. That said, Google Forms has lots of little features that are sometimes overlooked even by people who have made lots of forms in Google Forms. In the following video I demonstrate five features of Google Forms that every teacher should know how to use (if they use Google Forms).

Artificial Intelligence (AI) is a buzzword that has been coming up more and more in eLearning discussions. It's the next big thing as it has the potential to improve eLearning. Many people ask questions like, "Who uses AI?" "How can it be used?" and "What is its future in the eLearning industry?" This post was first published on eLearning Industry.

Jiawei Han, a professor of computer science at the University of Illinois at Urbana-Champaign, was recently named a Michael Aiken Chair, one of the University's highest awards. The endowed chair is the latest honor in Han's distinguished and pioneering career, with notable accomplishments including creating core data mining algorithms and co-authoring the textbook that is considered by many to have defined the field. Professor Han is also a busy and successful teacher with a love for "train[ing] the younger generation, whether at UIUC or all over the world on Coursera." Professor Han had three PhD students graduate in May, with one becoming a professor at Georgia Tech, one joining Google, and one joining Facebook. Students taking his classes as part of the Online Master of Computer Science in Data Science degree have an opportunity to learn from him through videos and can ask him questions directly during live office hours.

As higher education costs continue to rise, students bear the ultimate burden of choosing the right school, major, and delivery format to maximize post-graduation success. Unlike previous generations, millennials and adult learners are searching for alternatives to full-time, on-campus programs, and universities are eager to offer non-traditional routes to a degree. Distance learning programs have existed since the 1980s, but technological innovation, content scalability, and widespread mobile adoption have enabled the online degree program to be a competitive option for aspiring students. Long gone are the days of aggressive marketing tactics and empty promises made by degree mills and unaccredited for-profit universities. Today, a learner can enroll in competitive bachelor's and master's programs at U Penn, Columbia, Johns Hopkins, NYU, and more.

Are you interested in learning how to integrate machine learning in your apps? Machine Learning is the future of digital transformation. And now you can learn it from the comfort of your home.. in your own time.. without having to attend class. My name is Mohammad Azam and I am the creator of many popular online courses including Mastering MapKit in iOS Using Swift and Creating Stickers and iMessages Applications in iOS 10 Using Swift 3, Mastering Micro Services Using JPA, Mastering Server Side Swift Using Vapor, Mastering ARKit for iOS and more. I have created over 2 dozens apps and some of my apps were even featured by Apple on the App Store.

Google's TensorFlow framework is the current leading software for implementing and experimenting with the algorithms that power AI and machine learning. We will embark on this journey by quickly wrapping up some important fundamental concepts, followed by a focus on TensorFlow to complete tasks in computer vision and natural language processing. You will be introduced to some important tips and tricks necessary for enhancing the efficiency of our models. We will highlight how TensorFlow is used in an advanced environment and brush through some of the unique concepts at the cutting edge of practical AI. If you want to develop a solid foundation on using TensorFlow and continue your journey into advancing the state of the art in AI to create your own smart machine learning solutions, this course is for you.

Coursera Python for Everybody Specialization from University of Michigan is for those who are the complete beginners to programming language and also for who have no prior programming experience. This online coursera python for everybody course helps you to learn the basics of programming using Python Programming Language. This specialization will cover the fundamental topics of how you construct a program from a simple instruction in Python. After a general introduction to programming, coursera python for everybody teaches you how to use python to extract data from the web and work with databases. It's a good demonstration of how Python can be useful for managing large datasets.

Coursera Machine Learning by Andrew Ng is an online non-credit course authorized by Stanford University, to deeply understand the inner algorithms in Machine Learning. Machine learning is a core sub-area of artificial intelligence, it enables computers to get into a mode of self-learning without being explicitly programmed. When exposed to new data, these computer programs are enabled to learn, grow, change, and develop by themselves. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. The instructor of Coursera Machine Learning is Andrew Ng.