Big Data

 

 


 

Master Big Data with UCSD and Coursera



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E.g., 2017-08-17
E.g., 2017-08-17
E.g., 2017-08-17
Sep 4th 2017

Le MOOC « Fondamentaux pour le big data » permet d'acquérir efficacement le niveau prérequis en informatique et en statistiques pour suivre des formations dans le domaine du big data. Le big data offre de nouvelles opportunités d’emplois au sein des entreprises et des administrations. De nombreuses formations préparant à ces opportunités de métiers existent. Le suivi de ces formations nécessite des connaissances de base en statistiques et en informatique que ce MOOC vous propose d’acquérir dans les domaines de l’analyse, algèbre, probabilités, statistiques, programmation Python et bases de données.

Average: 6.3 (9 votes)
Aug 21st 2017

This course is for those new to data science.

Average: 6.8 (6 votes)
Aug 21st 2017

This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.

Average: 8 (1 vote)

Aug 21st 2017

Welcome to Data-driven Decision Making. In this course you'll get an introduction to Data Analytics and its role in business decisions. You'll learn why data is important and how it has evolved. You'll be introduced to “Big Data” and how it is used.

Average: 6.7 (6 votes)
Aug 21st 2017

You've learned the basic algorithms now and are ready to step into the area of more complex problems and algorithms to solve them. Advanced algorithms build upon basic ones and use new ideas. We will start with networks flows which are used in more obvious applications such as optimal matchings, finding disjoint paths and flight scheduling as well as more surprising ones like image segmentation in computer vision or finding dense clusters in the advertiser-search query graphs at search engines. We then proceed to linear programming with applications in optimizing budget allocation, portfolio optimization, finding the cheapest diet satisfying all requirements, call routing in telecommunications and many others. Next we discuss inherently hard problems for which no exact good solutions are known (and not likely to be found) and how to solve them approximately in a reasonable time. We finish with some applications to Big Data and Machine Learning which are heavy on algorithms right now.

Average: 6.7 (18 votes)
Aug 21st 2017

Accounting Analytics explores how financial statement data and non-financial metrics can be linked to financial performance. In this course, taught by Wharton’s acclaimed accounting professors, you’ll learn how data is used to assess what drives financial performance and to forecast future financial scenarios. While many accounting and financial organizations deliver data, accounting analytics deploys that data to deliver insight, and this course will explore the many areas in which accounting data provides insight into other business areas including consumer behavior predictions, corporate strategy, risk management, optimization, and more.

Average: 6.6 (14 votes)

Aug 21st 2017

You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering. However, it contains a number of recitals and R Studio tutorials which will consolidate your competences, enable you to play more freely with data and explore new features and statistical functions in R.

Average: 5 (2 votes)
Aug 21st 2017

By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff. We've designed this course to be as convenient as possible without sacrificing any of the essentials.

Average: 7.1 (16 votes)
Aug 21st 2017

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems.

Average: 5.5 (16 votes)
Aug 21st 2017

This course is for novice programmers or business people who'd like to understand the core tools used to wrangle and analyze big data. With no prior experience, you'll have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment. In the assignments you will be guided in how data scientists apply the important concepts and techniques, such as Map-Reduce that are used to solve fundamental problems in big data. You'll feel empowered to have conversations about big data and the data analysis processes.

Average: 6.6 (10 votes)
Aug 21st 2017

Data visualisation is vital in bridging the gap between data and decisions. Discover the methods, tools and processes involved. Data visualisation is an important visual method for effective communication and analysing large datasets. Through data visualisations we are able to draw conclusions from data that sometimes are not immediately obvious, and interact with the data in an entirely different way.

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Aug 14th 2017

In this second MOOC in the Social Marketing Specialization - "The Importance of Listening" - you will go deep into the Big Data of social and gain a more complete picture of what can be learned from interactions on social sites. You will be amazed at just how much information can be extracted from a single post, picture, or video. In this MOOC, guest speakers from Social Gist, BroadReader, Lexalytics, Semantria, Radian6, and IBM's Bluemix and Social Media Analytics Tools (SMA) will join Professor Hlavac to take you through the full range of analytics tools and options available to you and how to get the most from them. The best part, most of them will be available to you through the MOOC for free! Those purchasing the MOOC will receive special tools, templates, and videos to enhance your learning experience.

Average: 7.7 (7 votes)