When you enroll in this course, you'll also be asked to select a specific program.
Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Meta
There are 5 modules in this course
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.
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.
In this module you will be introduced to Python and how it can be used in data analytics. You will also learn how to use the Jupyter Notebook programming environment.
Approaching Data Analysis with the OSEMN Framework•4 minutes
Why Python for Data Analysis•3 minutes
Jupyter Notebook: Where We Write Our Code•1 minute
Basics of Using Jupyter Notebook•7 minutes
Using Jupyter Notebook on Coursera•3 minutes
Reviewing Example of a Typical Notebook on Coursera Activity•5 minutes
4 readings•Total 35 minutes
Course Syllabus•5 minutes
Join the Meta Marketing Analytics Community or the Meta Data Analyst Community!•10 minutes
How to be Successful in this Program•10 minutes
Tips for Using Jupyter Notebook•10 minutes
2 assignments•Total 25 minutes
Review Your Community Knowledge•10 minutes
Practice Quiz: Python for Data Analysis•15 minutes
1 programming assignment•Total 30 minutes
Activity: Example of a Typical Notebook on Coursera•30 minutes
Basic Python Concepts
Module 2•5 hours to complete
Module details
In this module, 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.
Python Syntax and Dot Notation Reference•10 minutes
3 assignments•Total 80 minutes
Graded Quiz: Obtaining and Scrubbing Data with Pandas•50 minutes
Knowledge Check on Libraries•15 minutes
Knowledge Check on Pandas•15 minutes
4 programming assignments•Total 120 minutes
Activity: Using Pandas•30 minutes
Activity: Selective Subsets•30 minutes
Activity: Removing Data•30 minutes
Activity: Modifying and Replacing Values•30 minutes
Exploring Data with Python
Module 4•5 hours to complete
Module details
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.
What's included
17 videos4 assignments4 programming assignments
Show info about module content
17 videos•Total 101 minutes
Why Exploration?•2 minutes
Exploring Relates to Scrubbing•2 minutes
Exploration: Basic Statistics•11 minutes
Exploration: Filtering Data•16 minutes
Reviewing Basic Exploration Activity•6 minutes
A Picture is Worth a Thousand Words•3 minutes
Introduction to the Purpose of Visualizations•1 minute
Types of Exploratory Visualizations: Distributions•3 minutes
Types of Exploratory Visualizations: Category•2 minutes
Types of Exploratory Visualizations: Relationship•3 minutes
Using Pandas and Matplotlib to Create Visualizations•11 minutes
Understanding Visualizations for Exploration•8 minutes
Reviewing Exploring with Visualization Activity•6 minutes
Where Aggregations Help Us Understand Data•2 minutes
Working with Groups in Pandas•12 minutes
Reviewing Aggregations Activity•5 minutes
4 assignments•Total 95 minutes
Graded Quiz: Exploring Data with Python•50 minutes
Knowledge Check on Exploration•15 minutes
Knowledge Check on Basic Statistics•15 minutes
Knowledge Check on Exploratory Visualizations•15 minutes
4 programming assignments•Total 130 minutes
Activity: Basic Exploration•30 minutes
Activity: Creating Visualizations•40 minutes
Activity: Exploring With Visualizations•30 minutes
Activity: Aggregations•30 minutes
Modeling and Interpreting Data with Python
Module 5•4 hours to complete
Module details
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.
Meta builds technologies that help people connect with friends and family, find communities, and grow businesses. The Meta Professional Certificates create opportunities so that anyone regardless of education, background or experience can learn high-quality skills to land a high-growth career—no degree or experience required to get started. Meta also offers training courses on the metaverse to educate people, brands, businesses and professionals on the opportunities it presents and what it means for our world today and into the future.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.