E-learning and ed-tech startups are becoming a rage as more and more people are developing interest in new forms of education involving innovation. This change is productive, crucial and able to break the geological boundaries for gaining quality education. The rising number of COVID-positive cases has made it very clear that without social distancing, it will be very difficult to control the spread of this deadly virus. So, in order to overcome the challenges faced by educational institutions, online teaching tools are now being implemented across different levels of education among many schools and universities in the world. Digitization of education is viewed as a need of the hour in India, where not many institutions are equipped with the right tools nor do they have the specialized aptitudes to make the learning environment technologically advanced.

Statistics is the science of turning data into insights and ultimately decisions. Behind recent advances in machine learning, data science and artificial intelligence are fundamental statistical principles. The purpose of this class is to develop and understand these core ideas on firm mathematical grounds starting from the construction of estimators and tests, as well as an analysis of their asymptotic performance. Taking this class will allow you to expand your statistical knowledge to not only include a list of methods, but also the mathematical principles that link them together, equipping you with the tools you need to develop new ones. This course is part of theMITx MicroMasters Program in Statistics and Data Science.

The Perceptron is a linear machine learning algorithm for binary classification tasks. It may be considered one of the first and one of the simplest types of artificial neural networks. It is definitely not "deep" learning but is an important building block. Like logistic regression, it can quickly learn a linear separation in feature space for two-class classification tasks, although unlike logistic regression, it learns using the stochastic gradient descent optimization algorithm and does not predict calibrated probabilities. In this tutorial, you will discover the Perceptron classification machine learning algorithm.

In light of the accelerating Digital Transformation across industries in the past years, it has never been more relevant than it is now during the global pandemic that you should improve your digital literacy and upskill yourself with data analytics skillsets. You'll be able to understand how each of the Chief Data Office function works and roles and responsibilities underpinned each pillar which covers the key digital concepts you need to know. There is a focus on the end-to-end data quality management lifecycle and best practices in this course which are critical to achieving the vision set out in the data strategy and laying the foundations for advanced analytics use cases such as Artificial Intelligence, Machine Learning, Blockchain, Robotic Automation etc. You will also be able to check your understanding about the key concepts in the exercises and there are rich reading materials for you to better assimilate these concepts. In light of the accelerating Digital Transformation across industries in the past years, it has never been more relevant than it is now during the global pandemic that you should improve your digital literacy and upskill yourself with data analytics skillsets.

Recently, I actively started looking for a job change to Data science, and I don't have any formal education like a Master's or Ph.D. background in AI/Machine Learning. I started learning it completely out of my own interest (not just because of the hype). It was one of the challenging tracks to opt-in, especially if you are working simultaneously on some other technology. I started my journey by enrolling myself in many MOOCs(Massive Open Online Courses) and started reading multiple blogs. It slowly started making sense.

If you think technology has only credited the Retail, F&B, eCommerce, Financial, and Agriculture verticles, then it's time for you to amaze yourself with the known yet unknown fact, the educational sector. The black & whiteboard to the projector screen and after COVID-19 it's the technology that makes education alive among the students. And it's important to acknowledge that the students enjoy the use of technology at every level of their learning process. Like how workplace digital transformation helped with high productivity and employee retention rate, similarly, creative ways to use technology in the classroom has created an excitement for learning among the students. The use of technology in teaching and learning has made life easier for both the teachers and students, the communication between the students and teachers are no more in a distress spot, right from the academic calendar schedules to lessons with media and visuals, technology integration has truly benefited education institutes.

By 2021, one in four forward-thinking enterprises will push AI to new frontiers, such as holographic meetings for remote work and on-demand personalised manufacturing, as per new predictions by Forrester Research. Even today, all of us are subconsciously using Machine Learning in our daily lives. Wish to stay home and yet be social? A nascent domain that's roughly 60 years old, has changed the way humans and machines perform, that's for sure. AI will create 2.3 million jobs in 2020.

Human-AI Interaction (HAII) was taught twice in a fully remote fashion over 12 weeks at Williams College to only undergraduates. The course was organized around 11.5 modules (i.e., topics), and each module included: 2x pre-recorded lecture videos, 2-3 readings (1 research paper 2 popular media), a 7 question quiz on that module's materials, a 60 minute synchronous [remote] class meeting with 8 students, followed by discussion forum posts and 2x responses to peers. The course was implemented in Canvas, referred to as "GLOW" at Williams, but I have made available some versions of the materials via Google documents on this website (apologies for any formatting issues!). Context for each course component is below, but details can be found on the Schedule and Syllabus pages. Lectures: Pre-recorded lectures for a module were posted twice per week (Thursdays & Mondays), which were recorded in 15 minute sections and linked together in a YouTube playlist for no more than 50 minutes total, although usually around 30-40 minutes.

Data science is one of the top skills in demand as jobs in the field sees an upward trend, especially after the pandemic. As a matter of fact, many online platforms are providing online data science courses. These programs also offer certifications on their completion, making aspiring data scientists more employable. Analytics India Magazine has collated some of the top subscription-based ed-tech platforms that provide learning data science in various formats. DataCamp is an ed-tech platform purely made only for data science.

Data scientists, machine learning engineers, and AI researchers all have their own skillsets. But what is that one special thing they have in common? They are all masters of deep learning. We often hear about AI, or self-driving cars, or the'algorithmic magic' at Google, Facebook, and Amazon. But it is not magic - it is deep learning. And more specifically, it is usually deep neural networks – the one algorithm to rule them all.