Predictive Analytics Predictive Analytics E-Learning
Predictive Analytics E-Learning
Predictive Analytics

Predictive Analytics E-Learning

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Predictive Analytics E-Learning Award-winning E-Learning course Extensive interactive videos with spoken text Certified teachers Practical exercises Certificate

  • E-Learning - Online toegang: 365 dagen
  • Taal: Engels (US)
  • Certificaat van deelname
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Product description

Predictive Analytics E-Learning Training

Order this amazing, award-winning Predictive Analytics E-Learning Training course online, 1 year 24/7 access to extensive interactive videos, speeches, hands-on tasks and progress monitoring. After the course you will receive a certificate of attendance.

Course content

Predictive Analytics & Big Data

Course: 38 Minutes

Course Introduction--Not StartedActions
What is Predictive Analytics?
Shedding Light with Predictive Analytics
Features of Predictive Analytics Models
Big Data
Big Data Considerations and Sources

Process & Application

Course: 59 Minutes

Course Introduction 
Sales, Marketing, and Operations
Banking and Insurance
Technology and Healthcare
Government and Crime Prevention

Key Statistical Concepts

Course: 1 Hour, 2 Minutes

Course Introduction
Predictive Analytics and Statistics
Types of Data
Data Measurement Scales
Descriptive vs. Inferential Statistics

Correlation & Regression

Course: 34 Minutes

Course Introduction
Overview of Correlation
Correlation and Predictive Analytics
Correlation and Causation
Statistical Significance of Correlation
Introduction to Regression Analysis
Best Fit and Residual Analysis
Logistic Regression for Predictive Analytics

Data Collection & Exploration

Course: 47 Minutes

Course Introduction
Choosing Predictive Data
Timing and Quantity of Data
Common Data Sources
Extract, Transform, and Load Data
Data Warehousing and Data Marts
Relational Database Management System and Hadoop

Data Mining, Data Distributions, & Hypothesis Testing

Course: 43 Minutes

Course Introduction
Descriptive Data Analytics
Prescriptive Data Analytics
What Is Data Mining?
Data Mining Concepts and Techniques
Methods for Data Mining

Data Preprocessing

Course: 31 Minutes

Course Introduction
The Need to Clean Messy Data
Outlier Identification and Handling
Transforming, Normalizing, and Scaling Data
Variable Partitioning
Dummy Variables and Variable Removal
Approaches for Handling Missing Data
Imputation for Continuous Data

Data Reduction & Exploratory Data Analysis (EDA)

Course: 45 Minutes

Course Introduction
Dimension Reduction
Principal Component Analysis for Numerical Data
Information Theory Approach to Feature Selection
Chi-square Feature Selection Method
Wrapper Data Reduction Method
Factor Analysis

K-Nearest Neighbor (k-NN) & Artificial Neural Networks

Course: 45 Minutes

Course Introduction
Overview of the k-NN Algorithm
Distance and Weight Measures for Numeric Attributes
Proximity Measures for Non-numeric Attributes
Implementing the k-NN Algorithm

A/B Testing, Bayesian Networks, and Support Vector Machine

Course: 47 Minutes

Course Introduction
Overview of A/B Testing
A/B Testing Features
Implementing A/B Testing

Clustering Techniques

Course: 41 Minutes

Course Introduction
Introduction to Clustering
Types of Clustering Techniques
Proximity Measures for Clustering

Linear and Logistic Regression

Course: 49 Minutes

Course Introduction
Linear Regression Overview
Sum of Squared Errors
Ordinary Least Squares (OLS)
Drawing Inferences

Text Mining & Social Network Analysis

Course: 55 Minutes

Course Introduction
Overview of Text Mining
Assigning within Document Predictor Variables
Text Normalization
Assigning across Document Predictor Variables
Term Frequency and Inverse Document Frequency
Sentiment Analysis
Text Mining Applications

Time Series Modeling

Course: 38 Minutes

Course Introduction--Not StartedActions
Time Series Overview
Stationary and Nonstationary Data Series
Time Series Decomposition

Machine Learning, Propensity Score, & Segmentation Modeling

Course: 54 Minutes

Course Introduction
Machine Learning Overview
Machine Learning Tools and Process
Deep Learning
Supervised vs. Unsupervised Methods
Ensemble Techniques for Machine Learning
Ensemble Performance Considerations and Metrics

Random Forests & Uplift Models

Course: 40 Minutes

Course Introduction
Random Forest Overview
Decision Tree Characteristics
Random Forest Model Error Measurement
Random Forest Model Concepts

Model Life Cycle Management

Course: 36 Minutes

Course Introduction
Understanding Business Objectives and Data
Model Development and Deployment
Model Deployment Planning
Stakeholder Management
User Training and Model Documentation
Model Recalibration and Maintenance
Business Validation and Benchmarks

Model Development, Validation, & Evaluation

Course: 1 Hour, 1 Minute

Course Introduction
Model Building Process and Data Discovery
Data Cleaning and Preparation
Data Preprocessing and Model Building

Availabilty 15:45 hours
Language English
Certificate of participation Yes
Online access 365 days
Progress monitoring Yes
Award Winning E-learning Yes
Suitable for mobile Yes
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