Your Guide to Business Analysis Tools for 2025
January 29, 2025
Article
This course is part of Business Analytics Specialization
Instructors: Ronald Guymon
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Intermediate level
Experience using R to assemble data, summarize data, and visually explore data.
(38 reviews)
Recommended experience
Intermediate level
Experience using R to assemble data, summarize data, and visually explore data.
Implement a conceptual framework of machine learning algorithms for finding actionable insight to business problems.
Apply a conceptual foundation for interpreting machine learning results from regression, classification, and clustering algorithms.
Apply machine learning algorithms to business data.
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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.
Exploratory data analysis (EDA) is a critical step in the business analytic workflow; however, EDA is a time-consuming approach for uncovering complex relationships. Moreover, the visualizations that are often used for EDA do not lend themselves well for quantifying confidence in results or for making predictions.
15 videos6 readings2 assignments1 peer review1 discussion prompt1 plugin
Gain an understanding of machine learning in business and logistic regression
14 videos2 readings1 assignment
Classification algorithms in general, K-nearest neighbors, and decision trees.
12 videos2 readings1 assignment
Clustering algorithms, k-means, and DBSCAN
13 videos4 readings1 assignment1 discussion prompt1 plugin
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
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This course is part of the following degree program(s) offered by University of Illinois Urbana-Champaign. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
This course is part of the following degree program(s) offered by University of Illinois Urbana-Champaign. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
University of Illinois Urbana-Champaign
Degree · 2 – 3 years
University of Illinois Urbana-Champaign
Degree · 6-10 months
University of Illinois Urbana-Champaign
Degree · 8 months
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