Big Data

 

 


 

Master Big Data with UCSD and Coursera



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E.g., 2017-04-26
E.g., 2017-04-26
E.g., 2017-04-26
May 8th 2017

Get a practical insight into big data analytics, and popular tools and frameworks for collecting, storing and managing data. Data is everywhere and can be obtained from many different sources. Digital data can be obtained from social media, images, audio recordings and sensors, and electronic data is quite often available as real-time data streams.

Average: 10 (1 vote)
May 1st 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)
May 1st 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)
May 1st 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: 7.2 (13 votes)
May 1st 2017

This course is for those new to data science.

Average: 7 (5 votes)
May 1st 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: 7.2 (5 votes)
May 1st 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.

No votes yet
May 1st 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: 6.6 (17 votes)
May 1st 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)
May 1st 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 (13 votes)
May 1st 2017

Work with airline data to learn the fundamentals of the R platform. We live in a data-driven world. This course is relevant to learners who are interested in analyzing data that is pervasive across disciplines.

No votes yet
Apr 24th 2017

Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data. After completing this course, you will be able to model a problem into a graph database and perform analytical tasks over the graph in a scalable manner. Better yet, you will be able to apply these techniques to understand the significance of your data sets for your own projects.

Average: 6 (1 vote)
Apr 24th 2017

Want to learn the basics of large-scale data processing? Need to make predictive models but don’t know the right tools? This course will introduce you to open source tools you can use for parallel, distributed and scalable machine learning.

Average: 7.8 (10 votes)
Apr 24th 2017

Learn how you can predict customer demand and preferences by using the data that is all around you. In a digital world, data has gone ‘big’ – ushering in the age of the zettabyte. This subject shows you how big data equals business opportunity. Find out what ‘big data’ means and where it comes from – including ordinary transactions and social interactions. See how smart businesses use data to target their offerings and get ahead of market trends. Consider how marketing data can be based on false assumptions such as the ‘last click myth’.

Average: 7.7 (7 votes)
Apr 24th 2017

This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection efforts.

Average: 5.5 (19 votes)
Apr 24th 2017

This course distills for you expert knowledge and skills mastered by professionals in Health Big Data Science and Bioinformatics. You will learn exciting facts about the human body biology and chemistry, genetics, and medicine that will be intertwined with the science of Big Data and skills to harness the avalanche of data openly available at your fingertips and which we are just starting to make sense of.

Average: 5.7 (6 votes)
Apr 24th 2017

Welcome to the Cloud Computing Applications course, the second part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data!

Average: 7.4 (5 votes)
Apr 24th 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)
Apr 24th 2017

Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools.

Average: 5.2 (5 votes)
Apr 24th 2017

Este curso pretende ser una introducción al Business Intelligence (BI). Se presenta que es un sistema de BI, cuál es la arquitectura de estos sistemas, cuáles son las metodologías principales de Business Analytics (el Clustering y la Clasificación), y cuáles son las tendencias actuales en el área del Business Intelligence.

Average: 5.5 (2 votes)

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