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Wednesday, 26 August 2015

Big Data online university courses

If you are interested in the growing career field of data science or have a general IT interest in what Big Data is and how it can be applied to real world topics then be sure to review the following MOOCs that discuss Big Data.

Tackling the Challenges of Big Data (October 6 - November 17, 2015) MITProfessionalX

This Digital Programs course will survey state-of-the-art topics in Big Data, looking at data collection (smartphones, sensors, the Web), data storage and processing (scalable relational databases, Hadoop, Spark, etc.), extracting structured data from unstructured data, systems issues (exploiting multicore, security), analytics (machine learning, data compression, efficient algorithms), visualization, and a range of applications.
Each module will introduce broad concepts as well as provide the most recent developments in research.
The course is taught by a team of world experts in each of these areas from MIT and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).
CSAIL is the largest research laboratory at MIT and one of the world’s most important centers of information technology research. CSAIL and its members have played a key role in the computer revolution. The lab’s researchers have been key movers in developments like time-sharing, massively parallel computers, public key encryption, the mass commercialization of robots, and much of the technology underlying the ARPANet, Internet, and the World Wide Web.
CSAIL members (former and current) have launched more than 100 companies, including RSA Data Security, Akamai, iRobot, Meraki, ITA Software, and Vertica. The Lab is home to the World Wide Web Consortium (W3C).
With backgrounds in data, programming, finance, multicore technology, database systems, robotics, transportation, hardware, and operating systems, each MIT Tackling the Challenges of Big Data professor brings their own unique experience and expertise to the course.

Big Data: Measuring and Predicting Human Behaviour

Explore how the vast amounts of data generated today can help us understand and even predict how humans behave.

We increasingly rely on networked computer systems and smart cards to support our everyday activities, and everything we do generates data – whether buying bread at the supermarket, taking a ride on public transport, or calling a friend for a chat.
This data is opening up a new era for our understanding of human behaviour – and also for policy making and business processes which depend upon this understanding. Research has shown how data can give us insight into the risk of an upcoming stock market crash; decrease delays in measuring the spread of illness; or even allow us to predict where crimes might occur.
This course will help you understand and unlock the power of these new datasets. You will gain an overview of the state of the art in big data research across a range of domains, including economics, crime and health.
You will also acquire some basic practical skills for data science using, learning to write basic programs in R, create basic data visualisations and carry out simple analyses. By the end of the course, you will be able to find out and analyse what people have been looking for on Google and Wikipedia.

Mining Massive Datasets

This class from Stanford University teaches algorithms for extracting models and other information from very large amounts of data. The emphasis is on techniques that are efficient and that scale well.

We introduce the participant to modern distributed file systems and MapReduce, including what distinguishes good MapReduce algorithms from good algorithms in general.  The rest of the course is devoted to algorithms for extracting models and information from large datasets.  Participants will learn how Google's PageRank algorithm models importance of Web pages and some of the many extensions that have been used for a variety of purposes.  We'll cover locality-sensitive hashing, a bit of magic that allows you to find similar items in a set of items so large you cannot possibly compare each pair.  When data is stored as a very large, sparse matrix, dimensionality reduction is often a good way to model the data, but standard approaches do not scale well; we'll talk about efficient approaches.  Many other large-scale algorithms are covered as well, as outlined in the course syllabus.

There is a free book "Mining of Massive Datasets, by Leskovec, Rajaraman, and Ullman (who by coincidence are the instructors for this course :-).  You can download it at  Hardcopies can be purchased from Cambridge Univ. Press.

Big Data MOOC

This course is intended for Students, IT Professionals, and Business Leaders who want a high-level understanding of big data, big data technology, and big data related careers.

This MOOC will teach you how to “talk the talk” in the big data world. In other words, if you are:
  • Considering investing in a big data solution, this MOOC is for you
  • Considering a career in big data, this MOOC is for you
  • Often hearing terms like MapReduce, Hadoop, and petabytes and not sure what they are, this MOOC is for you
  • A Big Data enthusiast who wants to see what CloudU put together, this MOOC is for you
Whatever the reason, we’re glad you’re here. Help us make this Big Data MOOC even better by participating in polls and discussions in the Discussion Center. We want to be clear that this MOOC will not certify you or qualify you to be a Big Data Architect or Data Scientist. This MOOC simply introduces you to the big data landscape, big data concepts, and big data terms you need to know to “talk the talk” in the big data world.

If you successfully pass the “Big Data MOOC Final Exam” in the third week, you get a CloudU Big Data MOOC certificate, a nice looking web badge, and a chance to win a CloudU t-shirt.

We titled this MOOC “Bigger is Better” because we’re confident you will not find more industry insights in one place than the CloudU Big Data MOOC.

What are you waiting for? Class is in session!

Digital Analytics Fundamentals

This course from CloudU provides a foundation for marketers and analysts seeking to understand the core principles of digital analytics and to improve business performance through better digital measurement.

Course highlights include:

  • An overview of today’s digital measurement landscape
  • Guidance on how to build an effective measurement plan
  • Best practices for collecting actionable data
  • Descriptions of key digital measurement concepts, terminology and analysis techniques
  • Deep-dives into Google Analytics reports with specific examples for evaluating your digital marketing performance

Big Data Masters Programs

If you are looking for a more formal Big Data educational opportunity then review the Top 20 Masters Programs specializing in Big Data.

Big Data Analytics Master's Degrees: 20 Top Programs

These one-year and two-year graduate programs are just what's needed to close the big-data talent gap. Read on to find a school that fits your ambitions and background.
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