Coursera

Basic Data Analysis and Model Building using Python (Coursera)

Offered by Coursera Project Network,

By the end of this project learners will be able to perform data ingestion using Pandas and Numpy, preprocess and visualize the data using Matplotlib and Seaborn. Learners will also build a binary classification model using Scikit-Learn. Additionally, learners will be introduced to other data science concepts and techniques such as standardization and up- and down-sampling of biased data. It is important to manipulate your data such that it can then be used to build a predictive model.

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

In this Guided Project, you will:

Ingest a dataset into a Jupyter Notebook environment using Pandas and create visualizations using the Matplotlib and Seaborn libraries.
Preprocess data through standardization, resampling using Scikit-Learn.
Build, train and save an accurate binary classification model.

Learn step-by-step

Data ingestion and visualization
Data preprocessing (standardization and scaling)
Data preparation and Principal Component Analysis intro
Build and train a binary classification model
Versioning

Go to Class

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

Related Courses

Coursera

Johns Hopkins University

The Data Scientist's Toolbox (Coursera)

Statistics & Data Analysis Data Science

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

Jun 8th 2026

4 Weeks

Data Github Data Analysis

Coursera

Ball State University

Data Visualization (Coursera)

Statistics & Data Analysis Data Science

In the era of big data, acquiring the ability to analyze and visually represent “Big Data” in a compelling manner is crucial. Therefore, it is essential for data scientists to develop the skills in producing and critically interpreting digital maps, charts, and graphs. Data visualization is an increasingly important topic in our globalized and digital society. It involves graphically representing data or information, enabling decision-makers across various industries to comprehend complex concepts and processes that may otherwise be challenging to grasp.

Jun 9th 2026

5-12 Weeks

R Language Exploratory Data Analysis Data Wrangling

Coursera

University of California, Irvine

Effective Problem-Solving and Decision-Making (Coursera)

Business

Critical thinking – the application of scientific methods and logical reasoning to problems and decisions – is the foundation of effective problem solving and decision making. Critical thinking enables us to avoid common obstacles, test our beliefs and assumptions, and correct distortions in our thought processes. Gain confidence in assessing problems accurately, evaluating alternative solutions, and anticipating likely risks. Learn how to use analysis, synthesis, and positive inquiry to address individual and organizational problems and develop the critical thinking skills needed in today’s turbulent times. Using case studies and situations encountered by class members, explore successful models and proven methods that are readily transferable on-the-job.

Jun 8th 2026

4 Weeks

Data Analysis Decision Making Critical Thinking

Coursera

University of Washington

Data Manipulation at Scale: Systems and Algorithms (Coursera)

Statistics & Data Analysis Data Science

Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales.

Jun 8th 2026

4 Weeks

Algebra Algorithms Databases

Coursera

University of Colorado System

Business Intelligence Concepts, Tools, and Applications (Coursera)

Statistics & Data Analysis Data Science

This is the fourth course in the Data Warehouse for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will gain the knowledge and skills for using data warehouses for business intelligence purposes and for working as a business intelligence developer. You’ll have the opportunity to work with large data sets in a data warehouse environment and will learn the use of MicroStrategy's Online Analytical Processing (OLAP) and Visualization capabilities to create visualizations and dashboards.

Jun 8th 2026

5-12 Weeks

Data Analysis Decision Making Business Intelligence

Coursera

University of California, San Diego

Biology Meets Programming: Bioinformatics for Beginners (Coursera)

CS: Software Engineering CS: Theory

Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python.

Jun 8th 2026

4 Weeks

Health Biology Programming

Coursera

University of Pennsylvania

Introduction to Spreadsheets and Models (Coursera)

Management & Leadership Business

The simple spreadsheet is one of the most powerful data analysis tools that exists, and it’s available to almost anyone. Major corporations and small businesses alike use spreadsheet models to determine where key measures of their success are now, and where they are likely to be in the future. But in order to get the most out of a spreadsheet, you have know how to use it. This course is designed to give you an introduction to basic spreadsheet tools and formulas so that you can begin harness the power of spreadsheets to map the data you have now and to predict the data you may have in the future.

Jun 8th 2026

4 Weeks

Business Models Spreadsheets

Coursera

Johns Hopkins University

Statistical Inference (Coursera)

Statistics & Data Analysis Data Science

Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference.

Jun 8th 2026

4 Weeks

Statistics Probability Data Analysis

Coursera

Northwestern University

Leadership Through Marketing (Coursera)

Management & Leadership

The success of every organization depends on attracting and retaining customers. Although the marketing concepts for doing so are well established, digital technology has empowered customers, while producing massive amounts of data, revolutionizing the processes through which organizations attract and retain customers. In this course, students will learn how to identify new opportunities to create value for empowered consumers, develop strategies that yield an advantage over rivals, and develop the data science skills to lead more effectively, allocate resources, and to confront this very challenging environment with confidence.

Jun 14th 2026

4 Weeks

Marketing Strategy Leadership

Coursera

University of Washington

Machine Learning: Regression (Coursera)

Statistics & Data Analysis Data Science

Case Study - Predicting Housing Prices. In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression.

Jun 8th 2026

5-12 Weeks

Python Algorithms Machine Learning

Coursera

University of California, San Diego

Graph Analytics for Big Data (Coursera)

Statistics & Data Analysis Data Science

Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data.

Jun 8th 2026

5-12 Weeks

Big Data Data Analysis Graphs

Coursera

University of Maryland, College Park

Framework for Data Collection and Analysis (Coursera)

Statistics & Data Analysis Data Science

This course will provide you with an overview over existing data products and a good understanding of the data collection landscape. With the help of various examples you will learn how to identify which data sources likely matches your research question, how to turn your research question into measurable pieces, and how to think about an analysis plan.

Jun 8th 2026

4 Weeks

Analysis Data Analysis Analytics