Tim Chartier – Big Data : How Data Analytics Is Transforming the World [Group Buy]

Tim Chartier – Big Data : How Data Analytics Is Transforming the World

Big Data: How Data Analytics Is Transforming the World introduces you to the key concepts, methods, and accomplishments of this versatile approach to problem solving. Taught by Professor Tim Chartier, an award-winning Associate Professor of Mathematics and Computer Science at Davidson College, these 24 half-hour lectures give you the big picture on big data, highlighting the crucial role of data analytics in today’s world and the even greater impact it will have in the future.

A Course for Data Users at All Levels

You need no expertise in mathematics to follow this exciting story. Professor Chartier explains the basic computational techniques used in data analytics, but his focus is on how these ideas are applied and the amazing results they achieve. His wealth of case histories and his many helpful graphics make Big Data both accessible and entertaining. Those who will benefit from his presentation include

• those in business, government, science, and other endeavors, who want a view into what data analytics can do for them;
• the intellectually curious, eager to investigate the role of computing and “data scraping” in the modern-day miracles of the information age;
• math enthusiasts who relish seeing a wide range of mathematical techniques address practical challenges;
• those considering, or already pursuing, work with data and aspiring to explore the full scope of their remarkable field; and
• anyone who relies on the Internet, smart phones, social media, or other tools that make them a participant in the data analytics revolution.

Big Data at Work

The volume, velocity, and variety of available data have increased at an astonishing rate during the last twenty years. That is to say, there are vast amounts of stockpiled data, and more is being generated constantly; the speed at which data is used, updated, and overturned in favor of newer data continues to accelerate; and data comes from many different sources and can be put to diverse uses. The miracle of data analytics is that ingenious algorithms are able to process this data deluge, which has been compared to trying to drink from a fire hose of information.

For instance, in just fifteen minutes the number of photos uploaded to Facebook exceeds the total number of photographs stored in the New York Public Library’s photo archives. Yet you can see a picture on your Facebook news feed within seconds after it’s posted. A high-speed computer algorithm allows the flood of imagery to be managed in a way that’s both timely and orderly. Professor Chartier explains how programmers achieve such feats by focusing only on the data that’s crucial to a specific task, while ignoring everything that’s irrelevant.

Big Data takes you behind the scenes to witness many examples of data analysis in action, including the following:

• Google Flu Trends: Google search queries on flu symptoms have sometimes proved more accurate and up-to-date at plotting the spread of flu than reports issued by doctors and hospitals. Explore the pitfalls and enormous potential of Internet traffic for charting many different trends.
• Online recommendations: Predictive analytics deals with forecasting the future, a task taken very seriously by companies like Netflix and Amazon that aim to predict what customers want. Learn how Netflix came up with an impressively accurate movie recommendation algorithm.
• March Madness: A classic exercise in data analytics is predicting the playoff winners of the NCAA basketball tournament, held every March. Follow the system for filling the game brackets, designed by Professor Chartier, and see how it applies to many other problems.

But big data and data analytics can also be a mixed blessing. While the field has revolutionized fraud detection, making many kinds of transactions much more secure, it has the potential to threaten personal privacy in ways that can be hard to spot. In this course, you learn that one of the best defenses for privacy is to know how data is compiled and processed, and which activities are the most compromising.

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