Predictive Analytics Course in Columbia

Predictive Analytics Training Course Outline

Module 1: Introduction to Predictive Analytics

• What is Predictive Analytics?
• How Predictive Analytics Works?
• Business Intelligence
• Business Intelligence Lifecycle
• Predictive Analytics Vs Business Intelligence
• Predictive Analytics Challenges

Module 2: Setting Up the Problem

• Predictive Analytics Processing Steps
• Target Variable
• Success Measures for Predictive Models
• Data for Predictive Modeling

Module 3: Understanding the Data

• Single and Multiple Variables         
• Data Visualization
• Histograms

Module 4: Data Preparation

• Data Cleaning
• Feature Creation

Module 5: Itemsets and Association Rules

• Association Rules
• Parameter Settings
• Data Organization Techniques
• Deploying Association Rules
• Making Classification Rules from Association Rules

Module 6: Descriptive Modeling

• Introduction to Descriptive Modeling
• Principal Component Analysis
• Clustering Algorithms

Module 7: Interpreting Descriptive Models

• Introduction to Descriptive Analytics
• How does Descriptive Analytics Work?
• Advantages of Descriptive Analytics

Module 8: Predictive Modeling

• Introduction to Predictive Modeling
• Decision Tree
• Types of Decision Tree
• Logistic Regression
• Neural Networks
• K-Nearest Neighbour
• Naïve Bayes
• Linear Regression

Module 9: Predictive Models Assessment

• Introduction to Predictive Models Assessment
• Metrics to Evaluate Predictive Models

Module 10: Model Ensembles

• Ensemble Modeling
• Types of Model Ensembles
• Bias Variance Trade-Off
• Bagging and Boosting
• Interpreting Model Ensembles

Module 11: Text Mining

• Introduction to Text Mining
• Structured Vs Unstructured Data
• Text Mining Applications
• Steps of Data Preparation
• Regular Expressions

Module 12: Predictive Model Deployment

• Introduction to Predictive Model Deployment
• Building Predictive Models

Who should attend this Predictive Analytics Training Course?

This Predictive Analytics Course in Columbia aims to provide professionals with the core concepts, techniques, and tools used to predict future events based on historical data and delves into the various stages of the analytics life cycle. This course can help various professionals, including:

• Data Scientists
• Business Analysts
• Marketing Analysts
• Financial Analysts
• Business Intelligence Professionals
• Risk Managers
• CRM Professionals

Prerequisites of the Predictive Analytics Training Course

There are no formal prerequisites required for attending this Predictive Analytics Course.

Predictive Analytics Training Course Overview

Predictive analytics is a powerful tool in the data science domain that plays a crucial role in foreseeing unknown future events that organizations must navigate. Utilizing techniques like data mining, modeling, statistics, artificial intelligence, and machine learning, Predictive Analytics Course in Columbia empowers organizations to identify forthcoming risks and opportunities by deciphering patterns within transactional and historical data.

Proficiency in Predictive Analytics is indispensable for a range of professionals in Columbia, including Data Scientists, Business Analysts, Marketing Experts, Financial Analysts, and decision-makers in diverse industries. As organizations seek a competitive edge, predictive analytics offers a strategic advantage, allowing professionals to anticipate market trends, customer behaviors, and operational efficiencies.

The 2-day course in Columbia provides delegates with knowledge on essential aspects like data cleaning, feature creation, item sets, and association rules. This course equips delegates with the knowledge to uncover valuable patterns and associations within data. Regardless of their field, individuals keen on augmenting their data science skill set will benefit from this training, gaining familiarity with predictive modeling techniques

Course Objectives

• To master the Predictive Analytics process, including data cleaning and feature creation
• To gain proficiency in uncovering valuable patterns and associations using itemsets and association rules
• To explore various predictive modeling techniques, such as logistic regression and Naïve Bayes
• To develop the skills to apply predictive models effectively in real-world scenarios
• To enhance decision-making by leveraging data-driven predictions and insights
• To empower organizations to become forward-looking and proactive using Predictive Analytics

By the end of this course in Columbia, the delegates will possess the skills to develop and apply predictive models effectively, enabling them to make data-driven predictions, optimize decision-making processes, and unlock new avenues for organizational growth.

What’s included in this Predictive Analytics Training Course?

• World-Class Training Sessions from Experienced Instructors
• Predictive Analytics Certificate
• Digital Delegate Pack