Monday 29 February 2016, 8:30am – 5:00pm, Australian Technology Park, Eveleigh, Sydney
ACS Members are offered 44% discount off the full price (incl. of GST and after 44.4%):
Early Bird - $400 (until 22 February 2016)
Standard - $500
Register at https://goo.gl/N842c5
Note: The discount of 44.4% for ACS professional members will apply automatically when using the above link
This is a course with a strong focus on hands-on learning through a number of step-by-step exercises.
The course starts with Big Data fundamentals, introduces various types of datasources and then provides students with the opportunity to use Big Data and Machine Learning on a practical problem. And, at the end of the course, one of the most important considerations for Big Data in the enterprise - privacy, will be covered.
After completing the course, in addition to the course material, participants will take with them a Virtual Machine (VM) with ready-to-use Big Data and Machine Learning solutions that can be deployed as prototypes for Big Data initiatives.
The course covers the following topics:
- Big Data Overview - looks at the definition of Big Data and what its characteristics mean.
- Machine Learning (ML) - is an introduction to Machine Learning, a growing area very closely linked to Big Data.
- Big Data Sources - there are many places where we can find datasets to be used in a Big Data initiative. We will look at some of these datasets, their locations and the mechanisms to access them.
- Big Data Tools - we will cover two of the most popular tools on the market today - Hadoop and MongoDB.
- Big Data Privacy - this module will examine the challenges posed by Big Data in the enterprise in the area of privacy.