NEW DELHI: India has an opportunity to create a locally designed Artificial Intelligence plan that would work for its needs and help nurture world-dominating companies specialising in this emerging field, say experts. So far, the country is seen as lagging behind the US and China in building capabilities in AI due to the lack of large internet companies that harness data of users. However, growing investments across sectors in building data-based businesses and the recognition by the government to create enabling policies for AI is throwing up opportunity for entrepreneurs. "India could have a very large role to play, all the pieces are in place, it has a great opportunity, and is upto India to either succeed or fail," Andrew NG, one of the most prominent experts of AI told ET. NG, who was the cofounder of Google Brain and is the founder of online learning platform Coursera added that he gets pitch notes from Indian startups.

Recognising the potential and the fact that India doesn't want to miss the bus on AI, the government has beginning to take steps.India has an opportunity to create a locally designed Artificial Intelligence plan that would work for its needs and help nurture world-dominating companies specialising in this emerging field, say experts. So far, the country is seen as lagging behind the US and China in building capabilities in AI due to the lack of large internet companies that harness data of users. However, growing investments across sectors in building data-based businesses and the recognition by the government to create enabling policies for AI is throwing up an opportunity for entrepreneurs. "India could have a very large role to play, all the pieces are in place, it has a great opportunity, and is up to India to either succeed or fail," Andrew Ng, one of the most prominent experts of AI told ET. Ng, who was the co-founder of Google Brain and is the founder of online learning platform Coursera added that he gets pitch notes from Indian startups.

THE training and development of your workforce is vital to the achievement of digital transformation success for businesses. And today, more and more businesses are leveraging e-learning to educate their employees. The advantages for businesses using online learning platforms as opposed to traditional training methods are bountiful. First, it lowers business costs since one training session can be delivered to multiple people. Second, topics can be broken down into bite-sized chunks, meaning that employees do not need to spend lengthy periods of time away from their desks.

For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in maths - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it's used in Computer Science. This specialisation aims to bridge that gap, getting you up to speed in the underlying maths, building an intuitive understanding, and relating it to Machine Learning and Data Science. In the first course on Linear Algebra we look at what linear algebra is and how it relates to data. Then we look through what vectors and matrices are and how to work with them. The second course, Multivariate Calculus, builds on this to look at how to optimise fitting functions to get good fits to data.

In what way will AI be incorporated into e-learning in the near future? E-learning has the potential to revolutionize education. For one thing, the internet and burgeoning AI technology have made e-learning more accessible than ever before. But e-learning also offers solutions to some of education's most pressing challenges, and in the future, it could serve to more adequately provide all students access to quality teaching. Everyone processes content in different ways and at different speeds.

Responding to questions over email and posted on forums, Jill had a casual, colloquial tone, and was able to offer nuanced and accurate responses within minutes. A robot has been teaching graduate students for 5 months and none of them realized. Here are just a few of artificial intelligence tools and technologies that will shape and define the educational experience of the future. Duolingo: voice recognition for language learning Duolingo is the world's most popular platform to learn a language. App predicts your word strength, figures out which sentences will help you best practice your weakest words/skills, recommends immersion practice documents (translations) based on your progress and estimates the quality of a translation-in-progress. Plexuss: college comparison and recruitment platform Plexuss facilitates contact between universities and future students, and aims to help students make an informed decision when it comes to choosing the right university.

Machine learning and AI are some of the biggest topics in the tech world right now, and Google is looking to make those fields more accessible to more people with its new Learn with Google AI website. Google has been pursuing AI education for a while, both with advanced projects like TensorFlow and more playful projects like cat doodles and a machine vision experiment meant to showcase AI projects in more practical ways. Google envisions the Learn with Google AI site serving as a repository for machine learning and AI, and it's meant to be a hub for anyone looking to "learn about core ML concepts, develop and hone your ML skills, and apply ML to real-world problems." The site will apparently cater to all levels of AI enthusiasts, from researchers looking for advanced tutorials to beginners. The site also features a free course called Machine Learning Crash Course (MLCC).

One year back, I was a newbie to the world of Machine Learning. I used to get overwhelmed by small decisions, like choosing the language to code with, choosing the right online courses, or choosing the correct algorithms. So, I have planned to make it easier for folks to get into Machine Learning. I'll assume that many of us are starting from scratch on our Machine Learning journey. Let's find out how current professionals in the field reached their destination, and how we can emulate them on our journey. I will illustrate how you can learn Data Science by drawing a parallel between how Rafael Nadal learned to play tennis, and how you can learn Machine Learning.

Machine learning and AI are some of the biggest topics in the tech world right now, and Google is looking to make those fields more accessible to more people with its new Learn with Google AI website. Google has been pursuing AI education for a while, both with advanced projects like TensorFlow and more playful projects like cat doodles and a machine vision experiment meant to showcase AI projects in more practical ways. Google envisions the Learn with Google AI site serving as a repository for machine learning and AI, and it's meant to be a hub for anyone looking to "learn about core ML concepts, develop and hone your ML skills, and apply ML to real-world problems." The site will apparently cater to all levels of AI enthusiasts, from researchers looking for advanced tutorials to beginners. The site also features a free course called Machine Learning Crash Course (MLCC).

Robots Can cost as low as $25,000* 250,000 purchased globally in 2016** *Source: Robots: The new low-cost worker, Dhara Ranasinghe, CNBC, April 10, 2015. The "average" US worker now spends 25% of their day reading or answering emails Fewer than 16% of companies have a program to "simplify work" or help employees deal with stress. The average mobile phone user checks their device 150 times a day. The "average" US worker works 47 hours and 49% work 50 hours or more per week, with 20% at 60 hours per week 40% of the US population believes it is impossible to succeed at work and have a balanced family life. FOMO We are all suffering from…….