About this Course

5,945 recent views

This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives. Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making for their agencies, organizations or clients.

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.

Intermediate Level

Approx. 23 hours to complete

English

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

Try Coursera for Business

Skills you will gain

Predictive Analytics
Decision-Making Software
Geodemographic Segmentation
Validated Learning

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.

Intermediate Level

Approx. 23 hours to complete

English

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

Try Coursera for Business

Instructor

Instructor rating

4.22/5 (30 Ratings)

Sridhar Seshadri

Professor of Business Administration

Business Administration

16,227 Learners

2 Courses

Syllabus - What you will learn from this course

Week1

Week 1

9 hours to complete

Module 0: Get Ready & Module 1: Drowning in Data, Starving for Knowledge

9 hours to complete

13 videos (Total 104 min), 11 readings, 4 quizzes

13 videos

Welcome to Predictive Analytics and Data Mining2mMeet Professor Sridhar Seshadri1mRattle Installation Guidelines for Windows11mR and Rattle Installation Instructions for Mac OS14mOverview of Rattle7mLecture 1-1: Introduction to Clustering11mLecture 1-2: Applications of Clustering7mLecture 1-3: How to Cluster10mLecture 1-4: Introduction to K Means8mLecture 1-5: Hierarchical (Agglomerative) Clustering8mLecture 1-6: Measuring Similarity Between Clusters10mLecture 1-7: Real World Clustering Example6mLecture 1-8: Clustering Practice and Summary3m

11 readings

Syllabus30mAbout the Discussion Forums10mGlossary10mBrand Descriptions10mUpdate Your Profile10mModule 0 Agenda5mRattle Tutorials (Interface, Windows, Mac)30mFrequent Asked Questions10mModule 1 Overview20mModule 1 Readings, Data Sets, and Slides1h 30mModule 1 Peer Review Assignment Answer Key10m

3 practice exercises

Orientation Quiz30mModule 1 Practice Problems10mModule 1 Graded Quiz30m

Week2

Week 2

5 hours to complete

Module 2: Decision Trees

5 hours to complete

7 videos (Total 65 min), 3 readings, 3 quizzes

7 videos

Lecture 2-1: Introduction to Discriminative Classifiers7mLecture 2-2: Model Complexity7mLecture 2-3: Rule Based Classifiers9mLecture 2-4: Entropy and Decision Trees14mLecture 2-5: Classification Tree Example7mLecture 2-6: Regression Tree Example8mLecture 2-7: Introduction to Forests and Spam Filter Exercise9m

3 readings

Module 2 Overview20mModule 2 Readings, Data Sets, and Slides30mModule 2 Peer Review Assignment Answer Key10m

2 practice exercises

Module 2 Practice Problems30mModule 2 Graded Quiz30m

Week3

Week 3

5 hours to complete

Module 3: Rules, Rules, and More Rules

5 hours to complete

8 videos (Total 65 min), 3 readings, 3 quizzes

8 videos

Lecture 3-1: Introduction to Rules4mLecture 3-2: K-Nearest Neighbor9mLecture 3-3: K-Nearest Neighbor Classifier3mLecture 3-4: Selecting the Best K in Rstudio12mLecture 3-5: Bayes' Rule7mLecture 3-6: The Naïve Bayes Trick13mLecture 3-7: Employee Attrition Example5mLecture 3-8: Employee Attrition Example in Rstudio, Exercise, and Summary9m

3 readings

Module 3 Overview20mModule 3 Readings, Data Sets, and Slides30mModule 3 Peer Review Assignment Answer Key10m

2 practice exercises

Module 3 Practice Problems10mModule 3 Graded Quiz30m

Week4

Week 4

5 hours to complete

Module 4: Model Performance and Recommendation Systems

5 hours to complete

8 videos (Total 68 min), 3 readings, 3 quizzes

8 videos

Lecture 4-1: Introduction to Model Performance6mLecture 4-2: Classification Tree Example11mLecture 4-3: True and False Negatives8mLecture 4-4: Clock Example Exercise2mLecture 4-5: Making Recommendations13mLecture 4-6: Association Rule Mining6mLecture 4-7: Collaborative Filtering7mLecture 4-8: Recommendation Example in Rstudio and Summary12m

3 readings

Module 4 Overview20mModule 4 Readings, Data Sets, and Slides1hModule 4 Peer Review Assignment Answer Key10m

2 practice exercises

Module 4 Practice Problems10mModule 4 Graded Quiz30m

Reviews

4.4

31 reviews

5 stars
62.79%
4 stars
24.80%
3 stars
6.97%
2 stars
0.77%
1 star
4.65%

TOP REVIEWS FROM PREDICTIVE ANALYTICS AND DATA MINING

by JKAug 5, 2019

this class was intense but i have learned a lot, glad taking it

by BBSep 13, 2020

Good foundation course to understand Data Aanlytisc

by SKAug 3, 2019

Prof. Seshadri was amazing. Learned how to model and analyze data for various use cases. Excellent course for people looking for a good understanding of data modeling and data mining.

by POct 7, 2020

I have successfully completed the course and it has helped me to upgrade my skills. I am sure that this is going to help me to carry out my future carrier in Data Analytics efficiently.

View all reviews

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 purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, 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.
What is the refund policy?
You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.
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.

Predictive Analytics and Data Mining