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Predictive Analytics

Курс от Illinois Tech

Средний≈ 55.8 чАнглийский

О курсе

Modern enterprises capture significant amounts of data about its customers, suppliers, and partners. The challenge, however, is to transform this vast data repository into actionable business intelligence. This course introduces predictive analytics tools that can provide valuable business insights. Analysis tools include decision trees, neural networks, market basket analysis, and discriminant analysis. Both data cleaning and analyses will be discussed and applied to sample data.

Навыки, которые вы освоите

Classification Algorithms Decision Tree Learning Artificial Neural Networks Unsupervised Learning Predictive Analytics Data Mining Machine Learning Algorithms Data Science Machine Learning Data Cleansing Applied Machine Learning Supervised Learning Analytics Data Transformation Predictive Modeling Statistical Machine Learning R (Software)Data Preprocessing Data Analysis

Программа курса

9 модулей · 111 учебных материалов

01Module 1: R Basics22 материалов

Course Welcome

Course OverviewВидео Instructor IntroductionВидео SyllabusЧтение Meet and Greet DiscussionОбсуждение

Module 1 Introduction

Учитесь у экспертов

Dinakar Jayarajan

Clinical Associate Professor of Marketing and Director of Graduate Business Programs

Predictive Analytics

О курсе

Навыки, которые вы освоите

Программа курса

Course Welcome

Module 1 Introduction

Учитесь у экспертов

Dinakar Jayarajan

Lesson 1: R Basics

Lesson 2: R Dataframe

Lesson 3: R File I/O and Data Structures

Module 1 Summative Assessment

Module 1 Summary

Module 2 Introduction

Lesson 1: Classification

Lesson 2: kNN

Lesson 3: kNN Demo

Module 2 Summative Assessment

Module 2 Summary

Module 3 Introduction

Lesson 1: Principle behind the NB classifier

Lesson 2: NB Classification

Module 3 Summative Assessment

Module 3 Summary

Module 4 Introduction

Lesson 1: Principles behind the Decision Tree method

Lesson 2: C5.0 Algorithm

Module 4 Summative Assessment

Module 4 Summary

Module 5 Introduction

Lesson 1: Introduction to Neural Networks

Lesson 2: ANN Computation

Module 5 Summative Assessment

Module 5 Summary

Module 6 Introduction

Lesson 1: SVM Terminology

Lesson 2: SVM classification

Module 6 Summative Assessment

Module 6 Summary

Module 7 Introduction

Lesson 1: Distinguish Clustering and Classification

Lesson 2: kMeans Clustering

Module 7 Summative Assessment

Module 7 Summary

Module 8 Introduction

Lesson 1: Association Rule Mining

Lesson 2: Apriori Alogrithm

Module 8 Summative Assessment

Module 8 Summary

Summative Course Assessment