This year, the world witnessed significant technology advancements that will have long term implications for our economy and the way we work. Artificial intelligence dominated the list of top courses this year, taking three of the spots in our top 10 list, including the Machine Learning and Deep Learning courses taught by our co-founder Andrew Ng and a Machine Learning course from the University of Toronto. Blockchain has also burst onto the scene, putting Princeton's Bitcoin and Cryptocurrency course at number five on the list.

About this course: In this project-based course, you will design and execute a complete GIS-based analysis – from identifying a concept, question or issue you wish to develop, all the way to final data products and maps that you can add to your portfolio. Your completed project will demonstrate your mastery of the content in the GIS Specialization and is broken up into four phases: Milestone 1: Project Proposal - Conceptualize and design your project in the abstract, and write a short proposal that includes the project description, expected data needs, timeline, and how you expect to complete it. Milestone 2: Workflow Design - Develop the analysis workflow for your project, which will typically involve creating at least one core algorithm for processing your data. The model need not be complex or complicated, but it should allow you to analyze spatial data for a new output or to create a new analytical map of some type. Milestone 3: Data Analysis – Obtain and preprocess data, run it through your models or other workflows in order to get your rough data products, and begin creating your final map products and/or analysis.

According to some dire and sensational headlines, many people will likely soon find themselves in the unemployment line, while a relative of a Roomba moves in to their office, taking over their old job. Few topics have created so much fear, uncertainty and doubt in the workplace as recent developments in robotics and artificial intelligence. As people welcome Siri, Alexa and Google Assistant into their homes and personal lives, they are beginning to wonder if the same technology that answers their questions and assists them in their day-to-day lives could soon replace them in the office and on the factory floor, doing the same work they did – but better, faster, cheaper, 24/7/365. Earlier this year, the Center for Leadership Insight at Russell Reynolds Associates set out to examine how management, finance and administrative workers spend their time at work. Looking at data on 103 different jobs, we classified a total of 1,880 tasks (the specific activities these workers undertake) based on the likelihood that each task would be replaced or disrupted by AI.

About this course: The Large Hadron Collider (LHC) is the largest data generation machine for the time being. It doesn't produce the big data, the data is gigantic. Just one of the four experiments generates thousands gigabytes per second. The intensity of data flow is only going to be increased over the time. So the data processing techniques have to be quite sophisticated and unique.

I am sure we have all heard about Sophia the robot, as most of us have been fixated on her journey for quite some time now. Like Sophia, who has been constructed using Artificial Intelligence (AI) technology, which has become one of the industry's most followed technology of the season, is being studied by many scientists and researchers to connect the distinctions between machines and humans. How do these machines run on AI technology allowing them to operate independently, learning from their environment to interact how humans do. Isn't it marvelous and something to be in awe of? As Artificial Intelligence (AI) is still developing and advancing to claim the human-level intelligence, let us acknowledge the principles and methods it is deploying to improve the abilities of these machines to think like a human.

About this course: The goal of this course is to give learners basic understanding of modern neural networks and their applications in computer vision and natural language understanding. The course starts with a recap of linear models and discussion of stochastic optimization methods that are crucial for training deep neural networks. Learners will study all popular building blocks of neural networks including fully connected layers, convolutional and recurrent layers. Learners will use these building blocks to define complex modern architectures in TensorFlow and Keras frameworks. In the course project learner will implement deep neural network for the task of image captioning which solves the problem of giving a text description for an input image.

One of the most common problems learners have when jumping into Machine Learning and Data Science is the steep learning curve, and when you add to this the complexity of learning programming languages like Python or R you can get demotivated and lose interest fast. In this course you will learn the basic concepts of machine learning using a visual tool. Where you can just drag drop machine learning algorithms and all other functionality hiding the ugliness of code, making it much more easier to grasp the fundamental concepts. I will "hand-hold" you as we build from scratch 2 different types of supervised machine learning algorithms used in the real world, across several industries and I will explain where and how they are used. The course will teach you those fundamental concepts of machine learning by implementing practical exercises which are based on live examples.

Coding is a fundamental skill for children to learn in school, but it is more than just feeding programming into a computer. Learning to code teaches valuable cognitive skills like critical thinking and problem solving. As coding moves from school to home, many toy manufacturers are responding with gadgets that turn homework into a game. Most coding toys work by using a companion app to teach children how to combine commands to make the toys generate sounds, lights and movement. If you're looking for the perfect gift for children eager to learn the basics of coding, or want to give a little one a heads up when they get to logic and problem solving in school, here are 10 of the best coding toys on the market today.

The teaching of this course is done making the use of the "inverted classroom" model. This in simple terms means that instead of being introduced to the related material in a large lecture hall that limits itself to one-way communication, one can first watch the lecture that has been recorded by Geoffrey Hinton as a set of about 3 short videos at home before the commencement of the class, and then in class, takes place a much more dynamic discussion about it. If one is already registered for the class, you will be able to view all these videos on the Coursera website. Further details of how to do this will be given in the first lecture period.

In Data visualization with R course you will learn about Data visualization in a very systematic and easy way. R is a very powerful option in many software development domains. At its core, R is a statistical programming language that provides impressive tools for data mining and analysis, creating high-level graphics, and machine learning. R gives aspiring analysts and data scientists the ability to represent complex sets of data in an impressive way. By the end of the course, you will have enough knowledge and skill full of different visualization techniques, with the capacity to apply these abilities to real-world data sets.