3 Day Predictive Analytics Training Course in partnership with
Pragmatic Predictive Analytics
A training course to implement analytical techniques in a real business environment cutting through the academic theory to get straight to outcomes. Each case study is based on the real world experience of the trainer and Jube.
Immediate Return on Training
Several Predictive Analytics disciplines in a single five day training course delivering an all encompassing, enterprise, predictive analytics capability for your business just as the course concludes.
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.
The Tools Used
R has 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. It is little wonder that it is unseating SAS as the corporate choice for new Predictive Analytics projects.
When taken together with the wide array of packages available to R, nearly anything required of an analyst practicing predictive analytics, is available in R and therefore, without any license costs. There are however three, entirely elective, GUI licensed products which provide such immeasurable value, beyond what is available in R, such that they are also covered in the course, this is Norsys Netica, Exhaustive and Neurosolutions Infinity.
The course aims to bring Predictive Analytics together using R primarily, as well as some superb GUI licenced tools, to create a truly enterprise solution for all predictive analytics needs.
The Training Course
The training course is delivered in the meeting facilities of a high quality hotel brand in various locations around the world. Training course participants should be reasonably proficient in Excel. Training course participants are required to bring their own laptop and install Amazon Workspaces Client in advance of the course. The training course offers:
- Three days of hands-on, in-person training.
- A printed training material, including a Proprietary Procedure Manual to take away.
- A remote Windows 7 Desktop, powered by Amazon Workspaces, with all required predictive analytics training course software and training course datasets installed in advance.
- Morning Snacks, Lunch, Afternoon Snacks and Unlimited Refreshments.
- Free Exhaustive Licence, a software product created by Jube and featured in this training course, for creating machine augmented Linear and Logistic Regression models worth $800.
- Guaranteed small class size. The course is confirmed with a minimum of two participants and sealed at a maximum of four participants. With such small class sizes there will be plenty of time to ask questions and receive personal attention from the trainer.
- A highly consultative engagement. There will be plenty of time to discuss your specific projects and learning objective to provide immediate return to your organisation upon course completion.
Training Day 1
The first day of the workshop will focus on numeric prediction and will use simple techniques to produce Predictive Analytics based upon market datasets. Day one will be orientated around so called ‘Linear’ techniques built upon foundation statistics for the purposes of numeric value prediction:
- Training Module: Predictive Analytics Introduction
- Training Case Study: Elicitation of Factors
- Training Module: Getting Started with R
- Training Module: Data Structures
- Training Module: Loading and Merging Data
- Training Module: Summary Statistics and Plots in R
- Case Study: Abstracted Market Data Analysis
- Training Module: Linear Regression
- Training Case Study: Stock Price Prediction with Linear Regression
Training Day 2
The second day of the workshop will focus more on predictive analytics using more advanced techniques and machine learning. Day two is orientated around classification and in addition to quasi linear techniques, in the form of Logistic Regression. brings to bear ‘nonlinear’ classification techniques such as Decision Trees and Bayesian Networks:
- Training Module: Logistic Regression
- Training Case Study: Debit Card Fraud Risk with Logistic Regression
- Training Module: Exhaustive Search with Exhaustive Jube.io
- Training Module: Decision Trees
- Training Case Study: Decision Trees for Credit Risk Analysis
- Training Module: Clustering Unsupervised
- Training Case Study: Identify Customer Types
- Training Module: Support Vector Machines
- Training Cae Study: Handwriting Recognition
Training Day 3
The third day of the training course will focus on using computational power to automate model search and selection. R will be introduced as a means of consolidating predictive analytics into a single, centralized enterprise level tool:
- Training Module: Norsys Netica and Bayesian Analysis Belief (No Data, No Problem)
- Training Module: Neural Networks with Neurosolutions
- Training Case Study: Stock Market Prediction with Neural Networks
- Training Module: Automated Processing with NeuroSolutions Infinity
- Training Module: Monte Carlo Simulation for Prescriptive Analytics.