Coursera

Regression Modeling for Marketers (Coursera)

Offered by University of Colorado Boulder,
Regression Modeling for Marketers (Coursera)

"Regression Modeling for Marketers" is a specialized course designed to elevate marketing professionals' analytical skills. Focusing on regression analysis, the course enables learners to quantify, explain, and predict marketing outcomes using both simple and multiple linear regression models. This course stands out by not only teaching the creation and interpretation of market data visualizations but also showing the use of advanced statistical software for gaining marketing insights.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Learners will explore sophisticated analytical techniques like ANOVA, ANCOVA, and MANCOVA, enhancing their ability to dissect the impact of marketing strategies. The course also covers logistic regression and multivariate testing, key tools for anticipating market shifts and consumer choices. Additionally, it emphasizes the application of uplift modeling for targeted and personalized marketing campaigns, making it an essential resource for contemporary marketers.

What you'll learn
Apply regression analysis to understand & predict marketing outcomes. Interpret market data & refine statistical models for real-world application.

Syllabus

Understanding Simple Linear Regression
Grasp the essentials of Simple Linear Regression to predict and influence market outcomes. This module guides you through creating insightful scatter plots and using statistical software, turning data into reliable, predictive tools for marketing success.

Interpreting SLR Output
Learn to decode SLR outputs, enhancing your ability to make precise marketing predictions. Understand the significance of regression coefficients and R-squared values in shaping marketing strategies that are both data-driven and impactful.

Beyond Simple Linear Regression (SLR)
Elevate your predictive modeling with advanced techniques. This module takes you beyond SLR, showing you how to incorporate multiple factors into your analyses for more nuanced and effective marketing insights.

Applying and Generalizing Multiple Linear Regression (MLR)
Discover the power of Multiple Linear Regression in understanding complex market dynamics. Learn to integrate diverse factors into your analysis, using advanced techniques like ANOVA and MANCOVA for deeper market insights and smarter marketing decisions.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Mastering Data Analysis in Excel (Coursera) Coursera
Duke University

Mastering Data Analysis in Excel (Coursera)

Statistics & Data Analysis Data Science

Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality. This course will prepare you to design and implement realistic predictive models based on data. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two different predictive models to determine which applicants for credit cards should be accepted and which rejected. Your first model will focus on minimizing default risk, and your second on maximizing bank profits.

Oct 5th 2026
5-12 Weeks
Business Excel Data Analysis
Details
Julia Scientific Programming (Coursera) Coursera
University of Cape Town

Julia Scientific Programming (Coursera)

Statistics & Data Analysis Data Science

This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more.

Oct 12th 2026
4 Weeks
IPython Data Analysis Computer Programming
Details
Business intelligence and data analytics: Generate insights (Coursera) Coursera
Macquarie University

Business intelligence and data analytics: Generate insights (Coursera)

Business

‘Megatrends’ heavily influence today’s organisations, industries and societies, and your ability to generate insights in this area is crucial to your organisation’s success into the future. This course will introduce you to analytical tools and skills you can use to understand, analyse and evaluate the challenges and opportunities ‘megatrends’ will inevitably bring to your organisation.

Oct 19th 2026
5-12 Weeks
Statistics Charts Analytical Tools
Details
Principios esenciales de diseño en Tableau (Coursera) Coursera
Universidad Austral

Principios esenciales de diseño en Tableau (Coursera)

CS: Information & Technology

En este curso, analizarás y aplicarás principios de diseño esenciales para tus visualizaciones en Tableau. Este curso asume que comprendes las herramientas dentro de Tableau y tienes algún conocimiento de los conceptos fundamentales de visualización de datos. Definirás y examinarás las similitudes y diferencias del análisis exploratorio y estudio, así como comenzarás a hacerte las preguntas correctas sobre lo que se necesita en una visualización.

Oct 12th 2026
4 Weeks
Visual Perception Visualization Data Visualization
Details
L'analyse marketing (Coursera) Coursera
University of Virginia

L'analyse marketing (Coursera)

Marketing & Communication Business

Les organisations, quelle que soit leur taille, sont inondées de données sur les choix des consommateurs. Mais cette abondance d'informations ne se traduit pas toujours en de meilleures décisions. Savoir interpréter les données est le défi à relever, et il est de plus en plus attendu que les professionnels du marketing utilisent l'analyse pour éclairer et justifier leurs décisions.

Oct 12th 2026
5-12 Weeks
Marketing Marketing Strategy Metrics
Details
Foundations of Marketing Practice for Non-Majors (Coursera) Coursera
University of North Texas

Foundations of Marketing Practice for Non-Majors (Coursera)

Marketing & Communication

This course is an introductory survey of marketing terminology, concepts and practices from an applied perspective. Emphasis is on the activities performed by marketing managers to address real world marketing problems. Primary emphasis is on the identification of marketing opportunities and the planning and execution of marketing mix activities required to target these opportunities.

Oct 12th 2026
4 Weeks
Marketing Strategy Market Analysis
Details
Data Storytelling with Power BI (Coursera) Coursera
Edureka

Data Storytelling with Power BI (Coursera)

CS: Information & Technology

Welcome to the Data Storytelling with Power BI course, where you'll embark on a journey to acquire practical expertise in data transformation and visualization. Leverage the potential of Power BI to craft narratives through structured data, leading to the discovery of more profound insights. Throughout this course, you'll explore the industry-specific applications of Power BI and delve into its various features and functionalities.

Oct 12th 2026
5-12 Weeks
Data Management Data Visualization Power BI
Details
Machine Learning (Coursera) Coursera
Stanford University

Machine Learning (Coursera)

Statistics & Data Analysis Data Science

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.

Oct 5th 2026
5-12 Weeks
Artificial Intelligence MATLAB Algorithms
Details
Machine Learning: Concepts and Applications (Coursera) Coursera
University of Chicago

Machine Learning: Concepts and Applications (Coursera)

Data Science

This course gives you a comprehensive introduction to both the theory and practice of machine learning. You will learn to use Python along with industry-standard libraries and tools, including Pandas, Scikit-learn, and Tensorflow, to ingest, explore, and prepare data for modeling and then train and evaluate models using a wide variety of techniques. Those techniques include linear regression with ordinary least squares, logistic regression, support vector machines, decision trees and ensembles, clustering, principal component analysis, hidden Markov models, and deep learning.

Oct 19th 2026
5-12 Weeks
Python Machine Learning Clustering
Details
Fundamentals of Data Analysis in Excel (Coursera) Coursera
Corporate Finance Institute

Fundamentals of Data Analysis in Excel (Coursera)

Economics & Finance Statistics & Data Analysis

Excel is the most widely used analysis tool in the world and a great starting point for diving into data analysis. In this course, you’ll apply Excel’s native tools to structure your data into spreadsheets and tables. You’ll then analyze and produce insights from that data using pivot tables. Finally, you’ll visualize those insights by building a dashboard in Excel. You’ll apply these skills using modern functionality like dynamic array formulas, linked data types, and Ideas in Excel. You’ll work hands-on with real-world scenarios, using datasets pulled from financial statements and retail sales.

Oct 19th 2026
5-12 Weeks
Excel Data Analysis Microsoft Excel
Details