Machine Learning and Advanced Analytics


Today, with most people connected to the Internet, the power of the customer is almost limitless.The Internet has given them freedom to choose in a way that business could never have imagined.

They can browse your competitors’ Web sites with ease. They can compare prices, they can view sentiment about your business, and they can switch loyalty in a single click any time anywhere all from a mobile device. In addition, the emergence of social media sites means that customers also have a voice.

They can express opinion and sentiment about products and brands on Twitter Facebook, and review web sites and create social networks by attracting followers, and following others.

For many CEOs, customer retention, loyalty, service and growth are top of their agenda. In addition improving operational effectiveness is also high on their priority list.

This new 2-day seminar looks at the need to capture new data sources to add to what we already know and use Machine Learning to automatically discover, profile and catalog what is in these data sources. It then looks at how Machine Learning and Advanced Analytical techniques, such as text analyses, sentiment analysis, graph and streaming Analytics, can be used at scale on Big Data to provide new insight that helps foster growth, reduce costs and improve effectiveness for competitive advantage.

What you will learn

  • How data and analytical characteristics can dictate the approach taken and tools needed to conduct exploratory analytics
  • How to develop analytical models using supervised and unsupervised Machine Learning
  • How to develop Machine Learning models at scale on Apache Spark and Hadoop
  • Tools for building Machine Learning models
  • Tools for deploying, monitoring and re-training Machine Learning models
  • Tools and techniques for discovery, analysis and visualisation of multi-structured data
  • Text and Sentiment Analysis
  • Scaling text analysis to run on Hadoop and Spark
  • Clickstream analysis
  • Graph analysis – 4 graph analytical techniques to identify shortest path, analyse connectivity, identify communi- ties, determine influencers and important people in social networks etc.
  • Scale graph analysis on Apache Spark GraphX
  • Analyse fast data in real-time using Streaming Analytics
  • Deep Learning with multi-layer neural networks
  • Leverage Machine Learning and Advanced Analytics quickly and easily from self-service BI reports and dash- boards for access over the Web and on mobile devices

Main Topics

  • An Introduction to Data Exploration, Discovery and Visualisation
  • Getting Started with Predictive Analytics and Machine Learning
  • Advanced Analytics for Multi-Structured Data
  • Search, BI & Big Data
  • Deploying and Using Self-Service Data Discovery and Visualisation Tools




23 - 24 Jun 2022


Online event
Share on: