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Data analytics stage 2

This intermediate one day course brings together in- depth, state-of-the-art research and practical techniques in data science.

About this course

This learning experience will allow attendees to refresh or develop their skills by consolidating in-depth, state-of-the-art research and practical techniques in data science. At the course’s conclusion you’ll have the expertise to appreciate data science projects and professionally communicate with analytics experts.

Course structure

  • Introduction to machine learning, fundamentals of data pre-processing
  • Linear Regression and Introduction to Bayesian Approach: Naive Bayes
  • Decision Tree classifier and introduction to ensemble classifier: Random Forest
  • Competition (application of today’s learning)


Learning outcomes

  • Apply an industry standard analytics life cycle methodology for data mining and pattern discovery
  • Understand key terms and concepts in data mining
  • Interpret, synthesis and communication insight extracted from analytics in a context-appropriate manner


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Who is this course for?

This course is targeted at individuals and organisations looking to improve their use of big data for decision making.


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