3 Day Masterclass Predictive Analytics 2 with R | Terrapinn Training

London, 19-21 Mar 2018

3 day Masterclass

Predictive Analytics 2.0

Transition to R Data mining in SQL Enterprise predictive analytics

Predictive Analytics 2.0: With R & SQL

This course will bring Predictive Analytics together, using R, to create a truly enterprise solution for all predictive analytics needs. R has had become the standard for statistical analysis and predictive analytics. The cost efficiency of the software – it is free – coupled with the incredible variety of supplementary packages available to augment its powerful script-based language, makes it a one-stop shop for all predictive analytics needs.

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get practical

Implement analytical techniques in a corporate environment. Each case study is based on real world the experience of the trainer and Jube.IO

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gain strategic advantage

Several R disciplines into a single three day course. Introduction with Numeric Prediction, Big Database Fundamentals and Machine Learning.

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learn from the best

Go from no real analytical capability to competence in just three days

This course will build upon the techniques taught in the first Predictive Analytics course...

Big Data and Predictive Analytics are seeing explosive growth. There is a shortfall of individuals who understand these concepts. Not having these skills in any industry which aggregates data leads to an enormous competitive disadvantage.

This course will develop your skills in data analysis, summary statistics, forecasting and predictive analytics as well as predictive analytics using regression, probability, decision trees and neural networks.   

This course includes an annual subscription to Quandl Machine Learning Datasets for US Equities - used in the course - worth £900.


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In just 3 days you will:

  • Apply the predictive analytics methodology and use R in the real world, introducing all the concepts that were available in the GUI tools, while introducing more advanced concepts built upon such techniques (such as GARCH or ARIMA)
  • Use R with some of the most powerful Predictive Analytics packages in common use.
  • Create powerful SQL Statements to Offload work from R and create advanced, high performance, Abstractions, while comparing their offer to that of prolific NoSQL databases.
  • Implement your analysis in R Server, implementing pragmatically in a corporate environment using R Server.
  • Gain an annual subscription to Quandl Machine Learning Datasets for US Equities - used in the course - worth £900.

Meet your instructor

Richard Churchman teaching Predictive Analytics 2.0 for Terrapinn Training

Richard Churchman is Managing Partner at Jube.io where he is responsible for developing a proprietary predictive analytics platform that is used in a variety of industries. The platform is predominantly positioned in Funds (Banks, Hedge Funds, Sovereign Wealth Funds and Mutual Funds etc.) to help manage investment portfolios using a blend of Quantitative Methods (Regression and Neural Networks typically) and Qualitative Methods (Expert Judgement and increasingly Augmented Bayesian Networks).

Richard has over 16 years’ experience working with predictive analytics across a variety of industries and so can provide meaningful insight into the application of all techniques taught on the course in other problem industrial domains (e.g. Marketing Churn Models).

Organisations that will benefit:

  • All Forward Thinking Companies
  • Retailers
  • Ecommerce Platforms
  • Software Developers
  • Banks & Financial Services
  • Service providers
  • Business Intelligence Firms
  • Data Companies

Who will attend:

  • C-Suite Executives: CEOs, CFOs, CTOs, COOs, CIOs
  • Heads of Technology
  • Heads of Analytics
  • Heads of Enterprise
  • Marketing Managers
  • Risk Executives
  • Big Data
  • Data Warehousing
  • Business Analysts
  • Data Officers/Scientists/Engineers
  • Database Developers
  • Product Managers
  • Product Designers

Course Agenda

  • Module 1: Predictive Analytics Introduction
  • Case Study: Elicitation of Variables
  • Module 2: Getting Started with R.
  • Module 3: Data Structures
  • Module 4: Loading and Merging Data
  • Case Study: Stock Price Fetch and Aggregation
  • Module 4: Summary Statistics and Plots in R
  • Case Study: Stock Price Fetch and Aggregation
  • Module 5: Summary Statistics and Plots in R
  • Case Study: Abstracted Market Data Analysis.
  • Module 6: Linear Regression
  • Case Study: Linear Regression
  • Module 7: Logistic Regression//
  • Case Study: Regression Based Classification in R//
  • Module 8: Exhaustive Search with Exhaustive Jube.io (Free Licence for Course Participants worth $800) //
  • Module 9: Decision Trees//
  • Case Study: Decision Trees for Credit Risk Analysis //
  • Module 10: Clustering Unsupervised//
  • Module 11: Norsys Netica and Bayesian//
  • Recap: Day 2
  • Module 12: Norsys Netica and Bayesian Analysis Machine Learning
  • Case Study: Bayesian Network
  • Module 13: Bayesian Methods in R
  • Module 14: Neural Networks
  • Case Study: Improving Logistic Regression with a variety of Neural Networks in R
  • Module 15: Automated Processing with NeuroSolutions Infinity
  • Module 16: Real-Time R Invocation with R.net
  • Case Study: Finalising a Script for Production Use

For further information please call: +44 (0)207 092 1045

The earlier you book, the more you save…

Additionally, VAT may be applicable depending on course location.
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  • “I think is a fantastic course for anybody who is enthusiastic about big data”

    - Pricing Analyst,First National Bank

  • “The course content format the delivery methods examples were very engaging that I developed a special interest in Data secure again”

    - Director, MDSap Tech

  • “An awesome, hands on training that will teach you how to apply these concepts in real life”

    - Research analyst, Kauffman Foundation


We can come to you too! If you have a team of six or more, why not hold a private course? Our experts come to you and the course is tailored to your requirements.

Call +44 (0)20 7092 1045 (United Kingdom)
or +65 6322 2333 (Asia Pacific)
for more details