This course is part of the Business Analytics Specialization

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Business Analytics SpecializationUniversity of Illinois at Urbana-Champaign

About this Course

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One of the most exciting aspects of business analytics is finding patterns in the data using machine learning algorithms. In this course you will gain a conceptual foundation for why machine learning algorithms are so important and how the resulting models from those algorithms are used to find actionable insight related to business problems. Some algorithms are used for predicting numeric outcomes, while others are used for predicting the classification of an outcome. Other algorithms are used for creating meaningful groups from a rich set of data. Upon completion of this course, you will be able to describe when each algorithm should be used. You will also be given the opportunity to use R and RStudio to run these algorithms and communicate the results using R notebooks.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 4 of 6 in the

Business Analytics Specialization

Intermediate Level

Experience using R to assemble data, summarize data, and visually explore data.

Approx. 13 hours to complete

English

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What you will learn

1. Conceptual framework of ML algorithms
2. Conceptual foundation for interpreting ML results
3. Practice applying ML algorithms to business data

Skills you will gain

clustering
regression
R Programming
classification
prediction

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.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 4 of 6 in the

Business Analytics Specialization

Intermediate Level

Experience using R to assemble data, summarize data, and visually explore data.

Approx. 13 hours to complete

English

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

Try Coursera for Business

Instructors

Ronald Guymon

Senior Lecturer of Accountancy

Accountancy

55,484 Learners

5 Courses

Gies College of Business, University of Illinois

73,457 Learners

21 Courses

Offered by

University of Illinois at Urbana-Champaign

Get a head start on your degree

This course is part of the Master of Business Administration (iMBA) from University of Illinois at Urbana-Champaign. If you are admitted to the full program, your coursework will count towards your degree learning and all of your progress will transfer with you.

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Syllabus - What you will learn from this course

Week1

Week 1

6 hours to complete

Course Orientation and Module 1: Regression Algorithm for Testing and Predicting Business Data

6 hours to complete

16 videos (Total 111 min), 5 readings, 3 quizzes

16 videos

Course Introduction5mAbout Professor Jessen Hobson1mAbout Professor Ronald Guymon2mLearn on Your Terms30sModule 1 Introduction5mWhy Isn't EDA Enough?6mBusiness Problem3mData13mWhat Problems Can Regression Answer?7mCorrelation11mLinear Models10mSimple Regression13mResiduals and Predictions9mMultiple Regression9mDummy Variables8mModule 1 Conclusion1m

5 readings

Syllabus10mAbout the Discussion Forums10mLearn More About Flexible Learning Paths10mModule 1 Overview10mModule 1 Readings10m

2 practice exercises

Orientation QuizModule 1 Quiz30m

Week2

Week 2

2 hours to complete

Module 2: Framework for Machine Learning and Logistic Regression

2 hours to complete

14 videos (Total 98 min), 2 readings, 1 quiz

14 videos

Module 2 Introduction8mInference, Prediction, and Experimentation6mCategories of ML Models, Part 1, Types of Data and Terms7mCategories of ML Models, Part 2, Categories of Algos7mHow Machine Learning Works in General9mEvaluating ML Model Quality6mIntroduce the Business Problem to Solve3mIntroduce the Data4mIntroduction to Logistic Regression6mLogistic Regression Hands on - One Variable (Part1)8mLogistic Regression Hands on - One Variable (Part2)8mLogistic Regression Hands on - One Variable (Part3)10mLogistic Regression Hands on - Multiple Variables7mModule 2 Conclusion2m

2 readings

Module 2 Overview10mModule 2 Reading10m

1 practice exercise

Module 2 Quiz30m

Week3

Week 3

2 hours to complete

Module 3: Classification Algorithms

2 hours to complete

12 videos (Total 82 min), 2 readings, 1 quiz

12 videos

Module 3 Introduction3mIntroduce the Data4mIntroduction to Classification2mIntroduce the Business Problem4mIntroduction to K-Nearest Neighbors8mCreating KNN Model (Part 1)8mCreating KNN Model (Part 2)6mCreating KNN Model (Part 3)8mIntroduction to Decision Trees10mCreating Decision Tree Models10mEvaluating Results from Decision Trees9mModule 3 Conclusion3m

2 readings

Module 3 Overview10mModule 3 Reading10m

1 practice exercise

Module 3 Quiz30m

Week4

Week 4

3 hours to complete

Module 4: Clustering Algorithms

3 hours to complete

13 videos (Total 84 min), 4 readings, 1 quiz

13 videos

Module 4 Introduction5mIntroduce the Data4mIntroduction to Clustering and Questions that Clustering Can Answer6mIntroduce the Business Problem3mIntroduction to K-Means Clustering9mCreating K-Means Clusters9mEvaluating K-Means Clusters8mIntroduction to Density-Based Clustering5mCreating Density-Based Clusters8mEvaluating Density-Based Clusters9mModule 4 Conclusion4mCourse Conclusion4mGies Online Programs3m

4 readings

Module 4 Overview10mModule 4 Reading10mCongratulations10mGet Your Course Certificate10m

1 practice exercise

Module 4 Quiz30m

About the Business Analytics Specialization

Our world has become increasingly digital, and business leaders need to make sense of the enormous amount of available data today. In order to make key strategic business decisions and leverage data as a competitive advantage, it is critical to understand how to draw key insights from this data. The Business Analytics specialization is targeted towards aspiring managers, senior managers, and business executives who wish to have a well-rounded knowledge of business analytics that integrates the areas of data science, analytics and business decision making.

The courses in this Specialization will focus on strategy, methods, tools, and applications that are widely used in business. Topics covered include: Data strategy at firms Reliable ways to collect, analyze, and visualize data–and utilize data in organizational decision making Understanding data modeling and predictive analytics at a high-level Learning basic methods of business analytics by working with data sets and tools such as Power BI, Alteryx, and RStudio Learning to make informed business decisions via analytics across key functional areas in business such as finance, marketing, retail & supply chain management, and social media to enhance profitability and competitiveness.

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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Machine Learning Algorithms with R in Business Analytics

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