Certified Predictive Modeler (CPM) Course
Course Description
Certified Predictive Modeler program covers the end-to-end concepts for predictive modelling and its strategic importance to derive insight from data to make informed business decisions. It deals with the various principles, concepts, techniques, and tools used in the predictive modelling which comprise data mining, data warehousing, data marts, and business intelligence. This training provides different types of real-life business use cases including which include text analytics. Participants will be able to grasp these concepts and understand from a high-level overview on how they are all inter-connected within an organization.
Upon successful completion CPM program, participants will acquire knowledge on how to address the most appropriate predictive analytics technique that suitable for your business needs by going through the different interactive case studies and real-world problems.
Course Objective
The objective of this course is to equip participants with various predictive modelling concepts including predictive modelling, decision analysis and optimization, transaction profiling, and predictive search (supervised learning). Participants will learn the practical skill of predictive analytics by incorporated decision theory, Bayes rules, probabilistic solution, and information theory. Participants will also be equipped with the main theories applied in predictive modelling such as linear predictors, boosting, model selection and validation, regularization, and nearest neighbor. Participants will also be walking through different use-cases on successful applications in the industry.
Skills Acquired
Participants will be equipped with practical skills to implement predictive modelling using various data analysis methods such as linear regression model, logistic regression models, and decision trees. Participants will also acquire the skills related to the implementation of unsupervised learning algorithms such as k-means clustering and other analytical methods such as correlation analysis and association rules to derive insights from their data. Participants will also acquire the skill set of developing the predictive model with a process-based tool.
Why Predictive Modeling and Analytics?
Predictive analytics helps organizations predict with confidence what will happen next so that we can make smarter decisions and improve business outcomes. With predictive analytics we can transform data into predictive insights to guide front-line decisions and interactions, predict what customers want and will do next to increase profitability and retention, maximize the productivity of people, processes and assets, and detect and prevent threats and fraud before they affect organizations.
Course Outline
- Unit 1: Introduction to Business Analytics
- Unit 2: Types of Analytics
- Unit 3: Predictive Analytics
- Unit 4: Data Mining and Analytics
- Unit 5: Data Mining Tool – RapidMiner
- Unit 6: Data Preparation and Cleaning
- Unit 7: Data Mining Techniques
- Unit 8: Introduction to Predictive Modeling with Regression
- Unit 9: Introduction to Predictive Modeling with Rule Induction
- Unit 10: Introduction to Predictive Modeling with Decision Tree
- Unit 11: Introduction to Predictive Modeling with Neural Network
Course Outcome
- Gain a solid understanding of business analytics, different types and its impact on enterprises
- Gain a solid understanding of the role of predictive analytics and its importance to any businesses
- Acquire knowledge on applying data mining techniques using open-source tool (Rapid Miner)
- Acquire knowledge on predictive modelling with regression, rule induction, decision tree and neural network