Learning Management

Andrew Ng: How to be an innovator

MIT Technology Review

Having spent many years working on AI research and building AI products, I'm fortunate to have participated in a few innovations that made an impact, like using reinforcement learning to fly helicopter drones at Stanford, starting and leading Google Brain to drive large-scale deep learning, and creating online courses that led to the founding of Coursera. I'd like to share some thoughts about how to do it well, sidestep some of the pitfalls, and avoid building things that lead to serious harm along the way. As I have said before, I believe AI is the new electricity. Electricity revolutionized all industries and changed our way of life, and AI is doing the same. It's reaching into every industry and discipline, and it's yielding advances that help multitudes of people.

Learning and Evidence Analytics Framework Bridges Research and Practice for Educational Data Science

Communications of the ACM

Learning analytics (LA) as a research discipline focuses on multiple perspectives of understanding and supporting educational activities utilizing collected log data. To do so at a national and even international level, educational technology platforms that enable gathering users' interaction traces and digitally generated artifacts must store data in a standardized format. In Japan, the government initiated the GIGA School project in 2020, which installed more than nine million tablet PCs and high-speed Internet access at compulsory education institutions (elemental and middle schools). Such infrastructure enables the collection of educational data and analysis with the aim to improve educational practices in each school. With standardized data logging, it is possible to aggregate data from all schools and to generate educational Big Data that can support evidence-based policy-making and research at a national level.

10 of the best free artificial intelligence courses on edX


TL;DR: A wide range of online courses on AI(opens in a new tab) are available for free at edX. Master the basics, dive into machine learning, and grapple with ethical issues, without spending anything. Udemy leads the way when it comes to the size of offering, but edX is the top choice if you're looking to learn from the very best institutions in the world. Especially when you consider that these courses are offered for free. These free courses include unlimited access to all the video content, so you can enroll and start learning at your own pace.

10 of the best artificial intelligence courses you can take online for free


These free courses include unlimited access to all the video content, so you can enroll and start learning at your own pace. The only catch is that you miss out on things like a certificate of completion or direct messaging with the instructor, but does that really matter to you? If so, you have the option to upgrade and get your hands on that certificate for your CV. Learn how to make the most of artificial intelligence with Udemy.

The best ChatGPT courses you can take online for free


TL;DR: A wide range of free ChatGPT courses are available on Udemy. Learn how to boost your productivity, earn passive income, and create engaging content with help from artificial intelligence. There are many reasons to fear ChatGPT and the seamingly unstoppable rise of AI, but there are also plenty of reasons to be optimistic. Yes, artificial intelligence could lead to human extinction, but it could also save you time with your daily tasks, so maybe it's worth the risk. If you're looking to get the most out of ChatGPT, you can take a wide range of online courses on this popular chatbot with Udemy.

20 of the best MIT courses you can take online for free


You can learn at your own pace and even receive a verified certificate of completion for a small fee. There's no pressure to pay for a certificate, but it might be nice to stick something on your CV. It is from MIT, after all. Find all the best free online MIT courses on edX.

Investment Management with Python and Machine Learning


Founded in 1906, EDHEC is now one of Europe's top 15 business schools . Based in Lille, Nice, Paris, London and Singapore, and counting over 90 nationalities on its campuses, EDHEC is a fully international school directly connected to the business world. With over 40,000 graduates in 120 countries, it trains committed managers capable of dealing with the challenges of a fast-evolving world. Harnessing its core values of excellence, innovation and entrepreneurial spirit, EDHEC has developed a strategic model founded on research of true practical use to society, businesses and students, and which is particularly evident in the work of EDHEC-Risk Institute and Scientific Beta. The School functions as a genuine laboratory of ideas and plays a pioneering role in the field of digital education via EDHEC Online, the first fully online degree-level training platform.

AI Applications in People Management


In this course, you will learn about Artificial Intelligence and Machine Learning as it applies to HR Management. You will explore concepts related to the role of data in machine learning, AI application, limitations of using data in HR decisions, and how bias can be mitigated using blockchain technology. Machine learning powers are becoming faster and more streamlined, and you will gain firsthand knowledge of how to use current and emerging technology to manage the entire employee lifecycle. Through study and analysis, you will learn how to sift through tremendous volumes of data to identify patterns and make predictions that will be in the best interest of your business. By the end of this course, you'll be able to identify how you can incorporate AI to streamline all HR functions and how to work with data to take advantage of the power of machine learning.

Fundamentals of Machine Learning for Supply Chain


This course will teach you how to leverage the power of Python to understand complicated supply chain datasets. Even if you are not familiar with supply chain fundamentals, the rich data sets that we will use as a canvas will help orient you with several Pythonic tools and best practices for exploratory data analysis (EDA). As such, though all datasets are geared towards supply chain minded professionals, the lessons are easily generalizable to other use cases.