Coursera

Predictive Modeling, Model Fitting, and Regression Analysis (Coursera)

Offered by University of California, Irvine,
Predictive Modeling, Model Fitting, and Regression Analysis (Coursera)

Welcome to Predictive Modeling, Model Fitting, and Regression Analysis. In this course, we will explore different approaches in predictive modeling, and discuss how a model can be either supervised or unsupervised. We will review how a model can be fitted, trained and scored to apply to both historical and future data in an effort to address business objectives. Finally, this course includes a hands-on activity to develop a linear regression model.

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

What You Will Learn

  • The application of predictive modeling to professional and academic work
  • Applications of classification analysis: decision trees
  • Applications of regression analysis (linear and logistic)

Course 2 of 4 in the Data Science Fundamentals Specialization

Syllabus

WEEK 1
Predictive Modeling
Welcome to Module 1, Predictive Modeling. In this module we will begin with a comparison of predictive and descriptive analytics, and discuss what can be learned from both. We will also discuss supervised and unsupervised modeling, two foundational models in analytics and machine learning.

WEEK 2
Data Dimensionality and Classification Analysis
Welcome to Module 2, Data Dimensionality and Classification Analysis. In this module we will explore how data can be classified and how decision trees can be leveraged as a fast, easy to use a model that is easy to interpret, explain, and visualize.

WEEK 3
Model Fitting
Welcome to Module 3, Model Fitting. In this module we will explore the concept of model fitting and how creating a generalized model that is able to fit both historical and future data is the ultimate goal. We will also review how a model can be trained or scored to apply to new and unlabeled data.

WEEK 4
Regression Analysis
Welcome to Module 4, Regression Analysis. In this module we will begin with an explanation of regression analytics, a popular technique used by data science professionals to make predictions. We will also discuss how achieving model fit is not a guarantee that a model can help solve a business problem, and how even a good model can sometimes lead to unactionable outcomes.

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

Related Courses

Functional Programming in Scala Capstone (Coursera) Coursera
École Polytechnique Fédérale de Lausanne

Functional Programming in Scala Capstone (Coursera)

Statistics & Data Analysis Data Science

In the final capstone project you will apply the skills you learned by building a large data-intensive application using real-world data. You will implement a complete application processing several gigabytes of data. This application will show interactive visualizations of the evolution of temperatures over time all over the world.

Sep 7th 2026
5-12 Weeks
Interface Scala Interactive
Details
Global Statistics - Composite Indices for International Comparisons (Coursera) Coursera
University of Geneva

Global Statistics - Composite Indices for International Comparisons (Coursera)

Statistics & Data Analysis Data Science

In this course on global statistics, offered by the University of Geneva jointly with the ETH Zürich KOF, you will learn the general approach of constructing composite indices and some of resulting problems. We will discuss the technical properties, the internal structure (like aggregation, weighting, stability of time series), the primary data used and the variable selection methods. These concepts will be illustrated using a sample of the most popular composite indices. We will try to address not only statistical questions but also focus on the distinction between policy-, media- and paradigm-driven indicators.

Aug 31st 2026
5-12 Weeks
Statistics Data Analysis Comparison
Details
Data science perspectives on pandemic management (Coursera) Coursera
Politecnico di Milano

Data science perspectives on pandemic management (Coursera)

Statistics & Data Analysis Data Science

The COVID-19 pandemic is one of the first world-wide scenarios where data made a difference in capturing and analyzing the diffusion and impact of the disease. We offer an introductory course for decision makers, policy makers, public bodies, NGOs, and private organizations about methods, tools, and experiences on the use of data for managing current and future pandemic scenarios.

Sep 7th 2026
5-12 Weeks
Gamification Data Analysis Data Science
Details
Materials Data Sciences and Informatics (Coursera) Coursera
Georgia Institute of Technology

Materials Data Sciences and Informatics (Coursera)

Engineering Sci: Chemistry

This course aims to provide a succinct overview of the emerging discipline of Materials Informatics at the intersection of materials science, computational science, and information science. Attention is drawn to specific opportunities afforded by this new field in accelerating materials development and deployment efforts.

Sep 7th 2026
5-12 Weeks
Statistics Informatics Chemistry
Details
Math for MBA and GMAT Prep (Coursera) Coursera
Emory University

Math for MBA and GMAT Prep (Coursera)

Business

This course gives participants a basic understanding of statistics as they apply in business situations. A fair share of students considering MBA programs come from backgrounds that do not include a large amount of training in mathematics and statistics. Often, students find themselves at a disadvantage when they apply for or enroll in MBA programs. This course will give you the tools to understand how these business statistics are calculated for navigating the built-in formulas that are included in Excel, but also how to apply these formulas in an range of business settings and situations.

Sep 7th 2026
5-12 Weeks
Statistics Excel Statistical Analysis
Details
Data Science in Stratified Healthcare and Precision Medicine (Coursera) Coursera
University of Edinburgh

Data Science in Stratified Healthcare and Precision Medicine (Coursera)

Health & Society Statistics & Data Analysis

An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare. In this course, you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine.

Sep 7th 2026
5-12 Weeks
Medicine Healthcare Machine Learning
Details
From Excel to Power BI (Coursera) Coursera
Knowledge Accelerators

From Excel to Power BI (Coursera)

CS: Information & Technology

Are you using Excel to manage, analyze, and visualize your data? Would you like to do more? Perhaps you've considered Power BI as an alternative, but have been intimidated by the idea of working in an advanced environment. The fact is, many of the same tools and mechanisms exist across both these Microsoft products. This means Excel users are actually uniquely positioned to transition to data modeling and visualization in Power BI! Using methods that will feel familiar, you can learn to use Power BI to make data-driven business decisions using large volumes of data.

Sep 7th 2026
1 Week
Excel Data Analysis Microsoft Excel
Details
Introduction to Statistics (Coursera) Coursera
Stanford University

Introduction to Statistics (Coursera)

Statistics & Data Analysis Data Science

Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You will gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning.

Sep 7th 2026
5-12 Weeks
Statistics Analysis Probability
Details
Data intelligence for businesses and managers (Coursera) Coursera
Institut Mines-Telecom

Data intelligence for businesses and managers (Coursera)

Statistics & Data Analysis Data Science

With the proliferation of connected objects (computers, tablets, watches, etc.), huge masses of data are generated every second. This Big Data has led to the emergence of a data economy, where data is the main source of competitive advantage for companies. In this sense, data and its processing tools have become a strategic priority for companies, and the main gas pedal of their digital transformation.

Sep 7th 2026
5-12 Weeks
Artificial Intelligence Data Management Business Strategy
Details