Predictive Analytics: Intermediate Predictive Analytics (2019)
Expertise:
Technology:
- 18 Courses | 11h 54m 22s
- 7 Books | 35h 7m
- 2 Courses | 1h 21m 41s
- 5 Books | 31h 22m
- 1 Course | 1h 25m 57s
- 8 Books | 53h 20m
Discover how to identify and analyze data and use it to predict trends and patterns with Predictive Analytics
GETTING STARTED
Process & Applications
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1.What Is Predictive Analytics?3m 51sNOW PLAYING
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2.Shedding Light with Predictive Analytics5m 1sUP NEXT
GETTING STARTED
Predictive Modeling: Predictive Analytics & Exploratory Data Analysis
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1.Course Overview1m 30sNOW PLAYING
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2.Predictive Analytics8m 23sUP NEXT
GETTING STARTED
Applying Predictive Analytics
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1.Course Overview1m 34sNOW PLAYING
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2.Overview of Predictive Analytics3m 16sUP NEXT
COURSES INCLUDED
Process & Applications
Predictive analytics uses techniques, such as statistics and machine learning, to build predictive models, often using big data to test and validate these models. Explore key features of predictive analytics and big data.
8 videos |
32m
Assessment
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Key Statistical Concepts
For any organization, predictive analytics is quickly becoming a key component for organizational success. Discover the application of predictive analytics to various industries, and the process and roles involved.
12 videos |
51m
Assessment
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Data Considerations in Analytics
Predictive analytics involves a wide range of statistical tools and methods that allow an analyst to build a powerful predictive model. Explore the importance of statistics and probability theory in predictive analytics.
12 videos |
55m
Assessment
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Correlation & Regression
Predictive analytics involves widely accepted tools and techniques that enable organizations to make informed decisions regarding potential future events. Examine how correlation and regression are employed in predictive analytics.
8 videos |
29m
Assessment
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Data Collection & Exploration
Most data that organizations collect doesn't offer much value. However, by applying the right techniques, you can extract powerful insights from the stockpile of data. Discover data collection and exploration for best possible prediction.
10 videos |
39m
Assessment
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Data Mining, Data Distributions, & Hypothesis Testing
Purposeful information can be extracted from large data sets to determine what has, could, or should happen. Explore descriptive, predictive, and prescriptive analytics, including data mining, distribution models, and hypothesis testing.
10 videos |
37m
Assessment
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Data Preprocessing
Predictive analytics delivers the greatest value when the data being modeled is relevant to the business goals. Examine the preprocessing phase of data collection to provide the best predictive model.
7 videos |
25m
Assessment
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Data Reduction & Exploratory Data Analysis (EDA)
With predictive analytics, relevant data should be stored for easy retrieval and kept up-to-date, with attributes selected contingent on their predictive potential. Explore data reduction and graphic tools for exploratory data analysis.
11 videos |
40m
Assessment
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K-Nearest Neighbor (k-NN) & Artificial Neural Networks
Choosing the appropriate technique to deliver confident predictions can be challenging for analysts. Examine algorithms used for predictive analytics, including the K-Nearest Neighbor (k-NN) algorithm and artificial neural network modeling.
9 videos |
38m
Assessment
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A/B Testing, Bayesian Networks, & Support Vector Machine
At the core of predictive analytics lie the models used to make predictions after the data has been collected and preprocessed. Explore predictive techniques, including A/B testing, Bayesian Networks, and the support vector machine (SVM).
11 videos |
41m
Assessment
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Clustering Techniques
The key to meaningful analysis is the ability to choose the right methods that provide the greatest predictive power. Discover how data clustering, such as K-Means, hierarchical, and DBSCAN, is used to combine similar subsets of data.
10 videos |
35m
Assessment
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Linear & Logistic Regression
Regression modeling investigates relationships between dependent and independent variables and is heavily relied upon for predictive analytics and data mining applications. Explore both the linear and logistic regression models.
10 videos |
41m
Assessment
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Text Mining & Social Network Analysis
Text mining facilitates social network analysis, giving analysts the ability to capture people's sentiments about various topics. Examine how text mining and social network analysis can greatly impact many diverse areas.
11 videos |
48m
Assessment
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Time Series Modeling
Time series modeling is a common forecasting method, such as making stock market predictions. It has made its way into many varied applications, including inventory management and healthcare. Explore the features of time series modeling.
8 videos |
33m
Assessment
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Machine Learning, Propensity Score, & Segmentation Modeling
Both supervised and unsupervised machine learning techniques are at the forefront of the predictive analytics and data mining industry. Discover machine learning features and tools, propensity scoring, and segmentation modeling.
12 videos |
46m
Assessment
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Random Forests & Uplift Models
Nestled within machine learning are ensemble techniques, enabling the combination of multiple models to reduce prediction error and improve forecasting ability. Examine machine learning methods, including random forests and uplift models.
8 videos |
33m
Assessment
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Model Life Cycle Management
Analysts must continuously manage analytical models, such as monitoring performance over time and interacting with various stakeholders. Explore the operational decision-making stages of model life cycle management.
7 videos |
31m
Assessment
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Model Development, Validation, & Evaluation
Analytic model management ensures that models are not only superior to alternatives, but they also meet or exceed current business needs. Examine the process of building, validating, and evaluating a predictive analytics model.
13 videos |
53m
Assessment
Badge
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COURSES INCLUDED
Predictive Modeling: Predictive Analytics & Exploratory Data Analysis
Explore the machine learning predictive analytics, exploratory data analytics, and different types of data sets and variables in this 9-video course. Discover how to implement predictive models and manage missing values and outliers by using Python frameworks. Key concepts covered in this course include predictive analytics, a branch of advanced analytics, and its process flow, and learning how analytical base tables can be used to build and score analytical models. Next, you will discover business problems that can be resolved by using predictive modeling; how to build predictive models with the Python framework; and learn the essential features of exploratory data analysis. Then learn about data sets, collections of data corresponding to the content of a single database or a single statistical data matrix, and then learn the variables of the different types of data sets including univariate, bivariate, and multivariate data and analytical approaches that can be implemented with them. Finally, you will learn about methods that can be used to manage missing values and outliers in data sets.
9 videos |
40m
Assessment
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Predictive Modeling: Implementing Predictive Models Using Visualizations
Explore how to work with machine learning feature selection, general classes of feature selection algorithms, and predictive modeling best practices. In this 12-video course, learners discover how to implement predictive models with scatter plots, boxplots, and crosstabs by using Python. Key concepts examined here include the benefits of feature selection and the general classes of feature selection algorithms; the different types of predictive models that can be implemented and associated features; and how to implement scatterplots and the capability of scatterplots in facilitating predictions. Next, you will learn about Pearson's correlation measures and the possible ranges for Pearson's correlation; learn to recognize the anatomy of a boxplot, a visual representation of the statistical five-number summary of a given data set; and observe how to create and interpret boxplots with Python. Then see how to implement crosstabs to visualize categorical variables; learn statistical concepts that are used for predictive modeling; and learn tree-based methods used to implement regression and classification. Finally, you will learn best practices for implementing predictive modeling.
12 videos |
41m
Assessment
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COURSES INCLUDED
Applying Predictive Analytics
This 13-video course explores machine learning predictive analytics, and how its application can drive revenues, reduce costs, and provide a competitive advantage to businesses. Learners will observe the predictive modeling process and how to apply tools and techniques for performing predictive analytics, and how to use historical data to identify trends and patterns to forecast future events. First, you will learn about the predicative modeling process, the statistical concepts for predictive modeling, and regression techniques. This course uses two examples to demonstrate commonly used methods of predictive analytics, by examining decision trees and SVMs (support vector machines). Next, you will learn about survival analysis, market basket analysis, and how to apply data for cluster models. You will learn about random forests in predictive analytics, and you will examine probabilistic graphical models. Learn about classification models, and how to organize data into groups based on predicting the class of the data points. Finally, you will explore some best practices for predictive modeling.
14 videos |
1h 25m
Assessment
Badge
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Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.
Digital badges are yours to keep, forever.BOOKS INCLUDED
Book
Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and OpportunitiesWhile highlighting the current issues in data extraction, readers will learn new methodologies comprising of different algorithms that automate the multidimensional schema that remove the manual processes.
3h 3m
By M. Usman (eds), Muhammad Usman
Book
Data Mining: Practical Machine Learning Tools and Techniques, Fourth EditionTeaching readers everything they need to know to get going, this comprehensive resource offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations.
13h 23m
By Christopher J. Pal, Eibe Frank, Ian H. Witten, Mark A. Hall
Book
Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second EditionBased on the authors' practical experience in implementing data analysis and data mining, this proven go-to guide focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects.
3h 20m
By Glenn J. Myatt, Wayne P. Johnson
Book
A/B Testing: The Most Powerful Way to Turn Clicks into CustomersA guide to delivering a better user experience through A/B testing, this handy book outlines a simple way to test several different versions of a web page with live traffic, and then measure the effect each version has on visitors.
1h 51m
By Dan Siroker, Pete Koomen
Book
Working with Text: Tools, Techniques and Approaches for Text MiningProviding cross-disciplinary perspectives on text mining and its applications, this book offers focused studies describing text mining on historical texts, automated indexing using constrained vocabularies, and the use of natural language processing to explore the climate science literature.
6h 19m
By Emma L. Tonkin, Gregory J.L. Tourte (eds)
Book
Machine Learning: Algorithms and ApplicationsExplaining the concepts of machine learning algorithms, this practical book describes the application areas of each algorithm discussed, and uses simple, practical examples to help readers understand each algorithm.
2h 6m
By Eihab Bashier Mohammed Bashier, Mohssen Mohammed, Muhammad Badruddin Khan
Book
Text Mining in Practice with RWith the help of numerous real-world examples and case studies, this book takes a practical, hands-on approach to teaching you a reliable, cost-effective method to mining the vast, untold riches buried within all forms of text using R.
5h 5m
By Ted Kwartler
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BOOKS INCLUDED
Book
Applied Analytics through Case Studies Using SAS and R: Implementing Predictive Models and Machine Learning TechniquesIncluding industrial case studies of various domains, this book will help you examine business problems using a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language.
4h 46m
By Deepti Gupta
Book
Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Third EditionWritten for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling.
6h 12m
By Kattamuri S. Sarma
Book
Machine Learning with Spark and Python: Essential Techniques for Predictive Analysis, Second EditionDesigned specifically for those without a specialized math or statistics background, this book simplifies machine learning by focusing on two algorithm families that effectively predict outcomes, and by showing you how to apply them using the Python programming language.
5h 19m
By Michael Bowles
Book
Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Second EditionProviding exercises at the end of each chapter, this book offers the theory behind, programming steps for, and examples of predictive modeling with SAS Enterprise Miner.
7h 11m
By Kattamuri S. Sarma
Book
Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second EditionProviding simple yet insightful quantitative techniques, this book contains essays offering detailed background, discussion, and a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.
7h 54m
By Bruce Ratner
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BOOKS INCLUDED
Book
Predictive Analytics for Marketers: Using Data Mining for Business AdvantageIncluding comprehensive coverage of an array of predictive analytic tools and techniques, this book enables readers to harness patterns from past data, to make accurate and useful predictions that can be converted to business success.
4h 22m
By Barry Leventhal
Book
Fundamentals of Predictive Analytics with JMP, Second EditionGoing beyond the theoretical foundation, this step-by-step book gives you the technical knowledge and problem-solving skills that you need to perform real-world multivariate data analysis.
5h 22m
By B. D. McCullough, Ron Klimberg
Book
Predictive Analytics for Dummies, 2nd EditionProviding tips on outlining business goals and approaches, this friendly guide will help you discover the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data.
7h 12m
By Anasse Bari, Mohamed Chaouchi, Tommy Jung
Book
Effective CRM using Predictive AnalyticsIncluding numerous real-world case studies, this step-by-step book bridges the gap between analytics and their use in everyday marketing, providing guidance on solving real business problems using data mining techniques.
5h 5m
By Antonios Chorianopoulos
Book
Predictive Analytics and Data Mining: Concepts and Practice with RapidMinerWhether you are brand new to data mining or working on your tenth project, this easy-to-understand book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions.
6h 56m
By Bala Deshpande, Vijay Kotu
Book
Predictive Analytics, Data Mining and Big Data: Myths, Misconceptions and MethodsHelping managers make the most of data technologies in their business area, this easy to read, in-depth guide provides readers with a solid understanding of predictive analytics, and how it should be applied to improve business decision-making and operational efficiency.
5h 51m
By Steven Finlay
Book
Data Mining and Predictive Analytics, Second EditionApplying a unified "white box" approach to data mining methods and models, this detailed second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis.
11h 17m
By Chantal D. Larose, Daniel T. Larose
Book
Applied Predictive Analytics: Principles and Techniques for the Professional Data AnalystClearly explaining the theory behind predictive analytics, this guide teaches the methods, principles, and techniques for conducting predictive analytics projects, and offers tips and tricks that are essential for successful predictive modeling.
7h 15m
By Dean Abbott
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