Predictive Analytics E-Learning Training

Bestel deze geweldige, bekroonde Predictive Analytics E-Learning Training cursus online, 1 jaar 24/7 toegang tot uitgebreide interactieve video's, toespraken, praktische taken en voortgangsbewaking. Na de cursus ontvang je een certificaat van deelname.

Voorspellende analyses kunnen een enorme discriminator zijn voor zakelijke besluitvorming. De toepassing ervan in marketing en verkoop, financiën, HR, risicobeheer en beveiliging, en bedrijfsstrategie kan helpen bij het stimuleren van inkomsten, het verlagen van kosten en het bieden van concurrentievoordeel aan bedrijven. Dit pad introduceert voorspellende analyses, belangrijke tools en hun toepassing op gemiddeld tot gevorderd niveau voor een breed scala aan zakelijke en technische gebruikers op alle niveaus in de organisatie. Deze cursussen zijn bedoeld om enkele belangrijke voorspellende analyse- en modelleringsconcepten te leveren, algemene tools en algoritmen te beschrijven, en vooral zakelijke toepassingen van voorspellende analyses. De training zelf is softwareonafhankelijk en maakt gebruik van een of meerdere van deze softwaretools in voorbeelden: Excel, Minitab, R en RapidMiner.

Cursusinhoud

Predictive Analytics & Big Data

Course: 38 Minutes

• Course Introduction
• 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
• 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