Coursera

Python Data Analytics (Coursera)

Offered by Meta,
Python Data Analytics (Coursera)

This course introduces the use of the Python programming language to manipulate datasets as an alternative to spreadsheets. You will follow the OSEMN framework of data analysis to pull, clean, manipulate, and interpret data all while learning foundational programming principles and basic Python functions. You will be introduced to the Python library, Pandas, and how you can use it to obtain, scrub, explore, and visualize data.

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

By the end of this course you will be able to:
• Use Python to construct loops and basic data structures
• Sort, query, and structure data in Pandas, the Python library
• Create data visualizations with Python libraries
• Model and interpret data using Python
This course is designed for people who want to learn the basics of using Python to sort and structure data for data analysis.
You don't need marketing or data analysis experience, but should have basic internet navigation skills and be eager to participate. Ideally, you have already completed course 1: Marketing Analytics Foundation, course 2: Introduction to Data Analytics, and course 3: Data Analysis with Spreadsheets and SQL.
This course is part of the Meta Marketing Analytics Professional Certificate.

Syllabus

Introduction to Python
This week you will be introduced to Python and how it can be used in data analytics. You will learn basic programming principles such as variables and variable types using Python. You’ll also delve into basic Python statements such as Booleans and conditional statements.

Obtaining and Scrubbing Data with Pandas
This week is focused on using a Python library called Pandas. You will learn how to use Pandas to load, select, and clean data.

Exploring Data with Python
This week you will further explore and analyze datasets with Python. You will learn how to calculate basic statistics and create data visualizations with Pandas and Matplotlib, another Python library.

Modeling and Interpreting Data with Python
This week you will focus on modeling data with Python and interpreting the model results. You complete a data analytics challenge that applies the knowledge of Python and the application of the OSEMN framework you have gained throughout the course.

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

Related Courses

Algorithmic Thinking (Part 1) (Coursera) Coursera
Rice University

Algorithmic Thinking (Part 1) (Coursera)

CS: Theory

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Oct 5th 2026
4 Weeks
Python Computing Algorithms
Details
An Introduction to Interactive Programming in Python (Part 1) (Coursera) Coursera
Rice University

An Introduction to Interactive Programming in Python (Part 1) (Coursera)

CS: Programming

This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple.

Oct 5th 2026
5-12 Weeks
Programming Python Interactive Applications
Details
Supply Chain Analytics Essentials (Coursera) Coursera
Rutgers University

Supply Chain Analytics Essentials (Coursera)

Business

In this introductory course to Supply Chain Analytics, I will take you on a journey to this fascinating area where supply chain management meets data analytics. You will learn real life examples on how analytics can be applied to various domains of a supply chain, from selling, to logistics, production and sourcing, to generate a significant social / economic impact.

Oct 5th 2026
4 Weeks
Data Analysis Supply Chain Supply Chain Analytics
Details
Spatial Data Science and Applications (Coursera) Coursera
Yonsei University

Spatial Data Science and Applications (Coursera)

Statistics & Data Analysis Data Science

Spatial (map) is considered as a core infrastructure of modern IT world, which is substantiated by business transactions of major IT companies such as Apple, Google, Microsoft, Amazon, Intel, and Uber, and even motor companies such as Audi, BMW, and Mercedes. Consequently, they are bound to hire more and more spatial data scientists. Based on such business trend, this course is designed to present a firm understanding of spatial data science to the learners, who would have a basic knowledge of data science and data analysis, and eventually to make their expertise differentiated from other nominal data scientists and data analysts.

Oct 5th 2026
5-12 Weeks
Hadoop Geographic Information Systems GIS
Details
Principles of Computing (Part 2) (Coursera) Coursera
Rice University

Principles of Computing (Part 2) (Coursera)

CS: Software Engineering CS: Theory

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Understanding these principles is crucial to the process of creating efficient and well-structured solutions for computational problems. To get hands-on experience working with these concepts, we will use the Python programming language. The main focus of the class will be weekly mini-projects that build upon the mathematical and programming principles that are taught in the class.

Oct 5th 2026
4 Weeks
Programming Python Computing
Details
Practical Time Series Analysis (Coursera) Coursera
The State University of New York

Practical Time Series Analysis (Coursera)

Statistics & Data Analysis Data Science

Many of us are "accidental" data analysts. We trained in the sciences, business, or engineering and then found ourselves confronted with data for which we have no formal analytic training. This course is designed for people with some technical competencies who would like more than a "cookbook" approach, but who still need to concentrate on the routine sorts of presentation and analysis that deepen the understanding of our professional topics.

Oct 5th 2026
5-12 Weeks
Statistics Probability Equations
Details
Foundations of Data Science: K-Means Clustering in Python (Coursera) Coursera
University of London,Goldsmiths, University of London

Foundations of Data Science: K-Means Clustering in Python (Coursera)

Data Science

This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Science courses. It focuses on the basic mathematics, statistics and programming skills that are necessary for typical data analysis tasks.

Oct 5th 2026
5-12 Weeks
Programming Python Machine Learning
Details
Python and Statistics for Financial Analysis (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Python and Statistics for Financial Analysis (Coursera)

Economics & Finance Business

Python is now becoming the number 1 programming language for data science. Due to python’s simplicity and high readability, it is gaining its importance in the financial industry. The course combines both python coding and statistical concepts and applies into analyzing financial data, such as stock data.

Oct 5th 2026
4 Weeks
Python Statistics Inference
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.

Oct 5th 2026
1 Week
Excel Data Analysis Microsoft Excel
Details