GICT Certified Predictive Modeler course (CPM)

Funding-GICT-Training

Certification in
AI/ML, Big Data, Cloud Computing & IoT

Up to 90% funding for SMEs and professionals (conditions apply)
Special course fee for Tertiary Student/NSF

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Objective of the Predictive Modeler course

GICT Certified Predictive Modeler course (CPM) covers the concept of business analytics with more focus on predictive analytics and its importance to any business organization.

Predictive analytics is a branch of advanced analytics which is used to make predictions about unknown future events. It uses many techniques from data mining, statistics, modeling, machine learning and artificial intelligence to historical and current data to make predictions about the future. 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.

Predictive Modeler course

The course deals with basic principles, concepts, techniques and tools (RapidMiner) used in business analytics landscape. Also, this Certified Predictive Modeler – CPM Certification course covers different types of business analytics with real life use cases. Participants will understand the concept of data mining and analytics through an open source analytical tool. Participants will learn to use the tool for operations like data loading, data cleaning/preparation and building predictive models for a given business data. Through this Certified Predictive Modeler – CPM Certification course participants will acquire knowledge on how to use business analytics strategically in organization and to get the most benefit out of it.

 
 
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

Tools/Software used: MongoDB, RapidMiner, R

Course Outcome
  • Understand business analytics, different types and its impact on enterprises
  • Understand the role of predictive analytics and its importance in industry
  • Learn to apply data loading, data preparation and cleaning techniques
  • Learn to apply the data mining techniques using an open source tool
  • Acquire knowledge on predictive modeling with regression, rule induction, decision tree and neural network
Duration
  • 32 Hours (4 Days) Classroom Training
Pre-Requisites

Participants are preferred to have min. 2 years of experience in software development, business
domain or data/business analysis

Funding

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