Big Data

 

 


 

Master Big Data with UCSD and Coursera



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Jan 23rd 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 (13 votes)
Jan 23rd 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: 6.8 (11 votes)
Jan 23rd 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: 7 (1 vote)
Jan 23rd 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: 6.5 (8 votes)
Jan 23rd 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: 7.5 (11 votes)
Jan 23rd 2017

This course is for those new to data science.

Average: 7.3 (4 votes)
Jan 23rd 2017

Smartphones are one of the most influential devices that we use in our everyday lives. Smartphones consist of the most advanced hardware and software technologies that exist in the world, all combined together into a miraculous single easy-to-use portable system.

Average: 3.3 (4 votes)
Jan 23rd 2017

Learn various methods of analysis including: unsupervised clustering, gene-set enrichment analyses, Bayesian integration, network visualization, and supervised machine learning applications to LINCS data and other relevant Big Data from high content molecular and phenotype profiling of human cells.

Average: 2.7 (3 votes)
Jan 23rd 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: 9 (2 votes)
Jan 23rd 2017

You have most likely heard about Clouds and Big Data before, and already know how significantly important they are and will be in the future.

Average: 3.8 (9 votes)
Jan 23rd 2017

Every information service is connected through the Internet. If your work is any bit related to information, there is no excuse, you have to know what the Internet is and how it works! The relation of information and the Internet is equivalent to the blood and blood vessels of our body, which we have been using and will be using every day of our lives.

Average: 5.8 (6 votes)
Jan 23rd 2017

What is the Internet of Things? What is augmented reality? This course deals with the new emerging technologies of IoT (Internet of Things) and AR (Augmented Reality).

Average: 4 (3 votes)
Jan 23rd 2017

This course covers the services and specifications of the most popular wireless communication technologies used around the world.

Average: 4.3 (6 votes)
Jan 23rd 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: 6.4 (14 votes)
Jan 22nd 2017

Learn how to use Azure Data Lake technologies to store and process big data in the cloud. Want to store and process data at scale? This data analysis course teaches you how to apply the power of the Azure cloud to big data using Azure Data Lake technologies.

No votes yet
Jan 16th 2017

This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University.

Average: 2.9 (7 votes)
Jan 16th 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: 4 (4 votes)
Jan 16th 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.

No votes yet
Jan 16th 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: 7.7 (6 votes)
Jan 16th 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: 5.4 (17 votes)

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