Big Data Fundamentals

Learn how big data is driving organisational change and essential analytical tools and techniques, including data mining and PageRank algorithms.

Length: 10 weeks
Effort: 8 to 10 hours per week 
Level:

Intermediate

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Organizations now have access to massive amounts of data and it’s influencing the way they operate. They are realizing in order to be successful they must leverage their data to make effective business decisions.

In this course, part of the Big Data MicroMasters program, you will learn how big data is driving organisational change and the key challenges organizations face when trying to analyse massive data sets.

You will learn fundamental techniques, such as data mining and stream processing. You will also learn how to design and implement PageRank algorithms using MapReduce, a programming paradigm that allows for massive scalability across hundreds or thousands of servers in a Hadoop cluster. You will learn how big data has improved web search and how online advertising systems work.By the end of this course, you will have a better understanding of the various applications of big data methods in industry and research.

What you'll learn

  • Knowledge and application of MapReduce
  • Understanding the rate of occurrences of events in big data
  • How to design algorithms for stream processing and counting of frequent elements in Big Data
  • Understand and design PageRank algorithms
  • Understand underlying random walk algorithms

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University pathways

Related degrees from the University of Adelaide

Master of Data Science

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Bachelor of Computer Science

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