Predictive Analytics Methods Training. An Intensive Practical Training Course.
You can learn Predictive Analytics for business - even if you are an absolute beginner - in just a week. Start off Predictive Analytics training with intuitive GUI tools, then transition to R and SQL in this intensive training course.
Austin, TX, USA | Krakow, Poland | Miami,FL, USA | Atlanta, GA, USA | Las Vegas, NV, USA | Toronto, Canada | Taipei, Taiwan (for Hong Kong) | Port Louis, Mauritius | Chicago, IL | Washington, DC | Sydney, Australia.
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.
Using intuitive GUI tools this training course will guide you through a methodology that focuses on practical application where the techniques taught will be transferable across a wide variety of industries. The GUI tools used in this training course are a superb means to introduce Predictive Analytics, although much of the functionality can, and will, be replicated in R.
After mastering the fundamentals, using GUI tools, this training course will transition to R and SQL. R training will assure an enterprise predictive analytics capability as a primary outcome of the training course. R has become the standard for statistical analysis and predictive analytics, fast overtaking SAS, while SQL remains the stalwart language for mining data from the enterprise. The cost efficiency of the R 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.
The Training Course
The training course is delivered in the meeting facilities of a high quality hotel brand in various locations around the world (typically The Westin hotel chain and where not available, an equivalent standard hotel such as the JW Marriot).
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:
- Five days of hands-on, in-person training.
- Over 900 pages of 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.
- Free annual subscription to Jube Machine Learning Datasets for US Equities worth $1200 which is a dataset referenced in this training course.
- Guaranteed small class size. The course is confirmed with a minimum of two participants and sealed at a maximum of six 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: Monday
The first day of the training course will focus on numeric prediction and will use simple techniques to produce Predictive Analytics based upon market datasets. Day one of the training course 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: Basic Statistics with Palisade StatTools
- Training Case Study: Stock Portfolio Selection
- Training Module: Abstraction and Transformations
- Training Case Study: Abstraction of Stock Price Data
- Training Module: Linear Regression
- Training Case Study: Stock Price Prediction with Linear Regression
Training Day 2: Tuesday
The second day of the training course will focus on predictive analytics using more advanced techniques and machine learning. Day two of the training course 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: Credit Card Risk of Default with Logistic Regression
- Training Module: Probability, Product and Decision Tree Introduction
- Training Module: Exhaustive Search with Exhaustive Jube.io
- Training Case Study: Logistic Regression and Activation Rules
- Training Module: Norsys Netica and Bayesian Analysis.
- Training Case Study: Credit Card Risk of Default with Baysian Network
Training Day 3: Wednesday
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: Neural Networks with Neurosolutions
- Training Case Study: Stock Market Prediction with Neural Networks
- Training Module: Automated Processing with NeuroSolutions Infinity
- Training Module: Getting Started with R.
- Training Case Study: Working with Off the Shelf Scripts
- Training Module: Data Structures
- Training Module: Loading and Merging Data
Training Day 4: Thursday
The fourth day of the training course shadows the first two days of the training course, transitioning to R while building upon these concepts with more advanced analytical techniques care of R's extensive package library:
- Training Module: Summary Statistics and Plots in R
- Training Case Study: Stock Portfolio Selection.
- Training Module: SQL Offloading and Abstraction.
- Training Case Study: Stored Procedure Abstraction
- Training Module: Linear Regression in R
- Training Case Study: Stock Price Prediction with Linear Regression in R
- Training Module: Logistic Regression with R
- Training Case Study: Credit Card Risk of Default with Logistic Regression
Training Day 5: Friday
The final day of the training course will continue in the same manner as the fourth day of the training course, steadily improving R fluency. The training course culminates in an exploration of the real-time deployments of models created during the training course.
- Training Module: Regression and C5 Decision Trees
- Training Case Study: Decision Trees for Credit Risk Prediction.
- Training Module: Naive Bayesian Networks in R
- Training Case Study: Credit Card Risk of Default with a Naive Bayesian Network in R.
- Training Module: Neural Networks in R.
- Training Case Study: Stock Market Prediction with Neural Networks in R.
- Training Module: Real Time Recall with Jube.io Model Execution Utility (includes Source Code)
Buy Upcoming Training Courses
Get a 20% discount when booking more than three weeks in advance (see Promo Codes below). Get a 30% discount for groups of three people or more (Promo Code DIVVC2D).
Austin, TX, USA | Sao Paulo, Brazil | Krakow, Poland | Miami,FL, USA | Atlanta, GA, USA | Las Vegas, NV, USA | Toronto, Canada | Taipei, Taiwan | Port Louis, Mauritius.