Big Data Fundamentals

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.


Course Objectives:

  • 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.


Recommended Background

  • Recommended for individuals heading towards a career in data science / currently in a business data analyst/ data scientist role.
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Course ID

ED138

Skill Focus

Smart Technology

Instructor(s)

The University of Adelaide

Employee Type

New applicants, Leadership

Method of Delivery

Digital

Estimated Effort

100 hrs

Cost

Audit Free


Certification is paid for $ 199.00 ; Full financial aid available for certification