This course is part of the Advanced Business Analytics Specialization

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570 ratings

Dan Zhang

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Offered By

Advanced Business Analytics SpecializationUniversity of Colorado Boulder

About this Course

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Welcome to the second course in the Data Analytics for Business specialization! 
This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. By taking this course, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business. 

You’ll also learn how to summarize and visualize datasets using plots so that you can present your results in a compelling and meaningful way. We will use a practical predictive modeling software, XLMiner, which is a popular Excel plug-in. This course is designed for anyone who is interested in using data to gain insights and make better business decisions. The techniques discussed are applied in all functional areas within business organizations including accounting, finance, human resource management, marketing, operations, and strategic planning. 

The expected prerequisites for this course include a prior working knowledge of Excel, introductory level algebra, and basic statistics.

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Course 2 of 5 in the

Advanced Business Analytics Specialization

Approx. 10 hours to complete

English

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Skills you will gain

Regression Analysis
Data Cleansing
Predictive Modelling
Exploratory Data Analysis

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 2 of 5 in the

Advanced Business Analytics Specialization

Approx. 10 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

3.04/5 (100 Ratings)

Dan Zhang

Professor

Leeds School of Business

44,587 Learners

3 Courses

Offered by

University of Colorado Boulder

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Syllabus - What you will learn from this course

Content Rating60%(1,648 ratings)

Week1

Week 1

3 hours to complete

Exploratory Data Analysis and Visualizations

At the end of this module students will be able to: 1. Carry out exploratory data analysis to gain insights and prepare data for predictive modeling 2. Summarize and visualize datasets using appropriate tools 3. Identify modeling techniques for prediction of continuous and discrete outcomes. 4. Explore datasets using Excel 5. Explain and perform several common data preprocessing steps 6. Choose appropriate graphs to explore and display datasets

3 hours to complete

8 videos (Total 38 min), 1 reading, 3 quizzes

8 videos

Introduction to the Course1m0. Introduction to the Module. Why Exploratory Data Analysis is Important3m1. Data Cleanup and Transformation4m2. Dealing With Missing Values6m3. Dealing with Outliers3m4. Adding and Removing Variables4m5. Common Graphs7m6. What is Good Data Visualization?4m

1 reading

2 practice exercises

Week 1 Quiz30mWeek 1 Application Assignment 1 (optional): Data Cleanup30m

Week2

Week 2

2 hours to complete

Predicting a Continuous Variable

2 hours to complete

8 videos (Total 41 min)

Week3

Week 3

2 hours to complete

Predicting a Binary Outcome

This module introduces logistic regression models to predict the value of binary variables. Unlike continuous variables, a binary variable can only take two different values and predicting its value is commonly called classification. Several important concepts regarding classification are discussed, including cross validation and confusion matrix, cost sensitive classification, and ROC curves. You will also learn how to build classification models using the software tool XLMiner.

2 hours to complete

8 videos (Total 33 min)

8 videos

0. Introduction to classification1m1. Introduction to Logistic Regression4m2. Building Logistic Regression Model6m3. Multiple Logistic Regression3m4. Cross Validation and Confusion Matrix5m5. Cost Sensitive Classification2m6. Comparing Models Independent of Costs and Cutoffs3m7. Building Logistic Regression Models using XLMiner6m

2 practice exercises

Week 3 Quiz30mWeek 3 Application Assignment30m

Week4

Week 4

4 hours to complete

Trees and Other Predictive Models

4 hours to complete

8 videos (Total 32 min)

Reviews

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210 reviews

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TOP REVIEWS FROM PREDICTIVE MODELING AND ANALYTICS

by SKFeb 15, 2017

Its an excellent course and thanks to Professor for making this course so practice oriented.

by CCSep 8, 2018

Really like the course and learned a lot. Wish that the quizzes didn't offer as much guidance on the steps to use XL Miner. Because this is given, it's not fully testing students on the material

by TMApr 14, 2020

Good course to give a basic understanding of predictive modelling and analytics. Good assignments and opportunity to review peer submissions help reinforce the learnings.

by RMSep 10, 2019

Professor is a little tough to understand, so I had to read the transcript during some of the videos. However, once I got the XLMiner issues resolved, it continued to be a great class and experience.

View all reviews

About the Advanced Business Analytics Specialization

The Advanced Business Analytics Specialization brings together academic professionals and experienced practitioners to share real world data analytics skills you can use to grow your business, increase profits, and create maximum value for your shareholders. Learners gain practical skills in extracting and manipulating data using SQL code, executing statistical methods for descriptive, predictive, and prescriptive analysis, and effectively interpreting and presenting analytic results.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Predictive Modeling and Analytics

About this Course

Skills you will gain