Python Data Analytics

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Python Data Analytics

This course is part of multiple programs.

Instructor: Victor Geislinger

30,064 already enrolled

Included with

5 modules

Gain insight into a topic and learn the fundamentals.

244 reviews

Beginner level

Recommended experience

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

87%

Most learners liked this course

5 modules

Gain insight into a topic and learn the fundamentals.

244 reviews

Beginner level

Recommended experience

Flexible schedule

2 weeks at 10 hours a week

Learn at your own pace

87%

Most learners liked this course

What you'll learn

Sort, query, and structure data in Pandas, the Python library
Describe how to model and interpret data using Python
Create basic data visualizations with Python libraries

Skills you'll gain

Category: Scripting
Category: Data Visualization
Category: Data Analysis
Category: Data Cleansing
Category: Programming Principles
Category: Regression Analysis
Category: Data Visualization Software
Category: Exploratory Data Analysis
Category: Data Manipulation
Category: Matplotlib

Tools you'll learn

Category: Python Programming
Category: Pandas (Python Package)
Category: Jupyter

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

15 assignments

Taught in English

Build your subject-matter expertise

This course is available as part of

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.

What's included

8 videos4 readings2 assignments1 programming assignment

8 videosTotal 31 minutes

Introduction to the Program6 minutes
Instructor Introduction Video2 minutes
Approaching Data Analysis with the OSEMN Framework4 minutes
Why Python for Data Analysis3 minutes
Jupyter Notebook: Where We Write Our Code1 minute
Basics of Using Jupyter Notebook7 minutes
Using Jupyter Notebook on Coursera3 minutes
Reviewing Example of a Typical Notebook on Coursera Activity5 minutes

4 readingsTotal 35 minutes

Course Syllabus5 minutes
Join the Meta Marketing Analytics Community or the Meta Data Analyst Community!10 minutes
How to be Successful in this Program10 minutes
Tips for Using Jupyter Notebook10 minutes

2 assignmentsTotal 25 minutes

Review Your Community Knowledge10 minutes
Practice Quiz: Python for Data Analysis15 minutes

1 programming assignmentTotal 30 minutes

Activity: Example of a Typical Notebook on Coursera30 minutes

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.

What's included

12 videos1 reading3 assignments5 programming assignments

12 videosTotal 82 minutes

What Does a Variable Mean in Python?10 minutes
Variable Types5 minutes
Working with Types in Python7 minutes
Reviewing Variables in Python Activity2 minutes
Lists & Tuples12 minutes
Reviewing Lists & Tuples Activity7 minutes
Dictionaries7 minutes
Reviewing Dictionaries Activity4 minutes
Booleans in Python7 minutes
Reviewing Using Booleans Activity6 minutes
Conditional Statements11 minutes
Reviewing Using Conditionals Activity5 minutes

1 readingTotal 10 minutes

Other Python Data Structures10 minutes

3 assignmentsTotal 80 minutes

Graded Quiz: Basic Python Concepts50 minutes
Knowledge Check on Variable Types15 minutes
Knowledge Check on Conditionals15 minutes

5 programming assignmentsTotal 150 minutes

Activity: Variables in Python30 minutes
Activity: Using Lists & Tuples30 minutes
Activity: Using Dictionaries30 minutes
Activity: Using Booleans30 minutes
Activity: Using Conditionals30 minutes

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

What's included

12 videos1 reading3 assignments4 programming assignments

12 videosTotal 87 minutes

Introduction to Libraries8 minutes
What is Pandas?8 minutes
Working with Pandas Series & DataFrames9 minutes
Reviewing Pandas Activity6 minutes
Subsets with Pandas9 minutes
Reviewing Selective Subsets Activity6 minutes
What is Scrubbing?2 minutes
Removing Data10 minutes
Reviewing Removing Data Activity7 minutes
Modifying Values7 minutes
Replacing Values5 minutes
Reviewing Replacing Values Activity10 minutes

1 readingTotal 10 minutes

Python Syntax and Dot Notation Reference10 minutes

3 assignmentsTotal 80 minutes

Graded Quiz: Obtaining and Scrubbing Data with Pandas50 minutes
Knowledge Check on Libraries15 minutes
Knowledge Check on Pandas15 minutes

4 programming assignmentsTotal 120 minutes

Activity: Using Pandas30 minutes
Activity: Selective Subsets30 minutes
Activity: Removing Data30 minutes
Activity: Modifying and Replacing Values30 minutes

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

17 videosTotal 101 minutes

Why Exploration?2 minutes
Exploring Relates to Scrubbing2 minutes
Exploration: Basic Statistics11 minutes
Exploration: Filtering Data16 minutes
Reviewing Basic Exploration Activity6 minutes
A Picture is Worth a Thousand Words3 minutes
Introduction to the Purpose of Visualizations1 minute
Types of Exploratory Visualizations: Distributions3 minutes
Types of Exploratory Visualizations: Category2 minutes
Types of Exploratory Visualizations: Relationship3 minutes
Using Pandas and Matplotlib to Create Visualizations11 minutes
Reviewing Creating Visualizations Activity8 minutes
Understanding Visualizations for Exploration8 minutes
Reviewing Exploring with Visualization Activity6 minutes
Where Aggregations Help Us Understand Data2 minutes
Working with Groups in Pandas12 minutes
Reviewing Aggregations Activity5 minutes

4 assignmentsTotal 95 minutes

Graded Quiz: Exploring Data with Python50 minutes
Knowledge Check on Exploration15 minutes
Knowledge Check on Basic Statistics15 minutes
Knowledge Check on Exploratory Visualizations15 minutes

4 programming assignmentsTotal 130 minutes

Activity: Basic Exploration30 minutes
Activity: Creating Visualizations40 minutes
Activity: Exploring With Visualizations30 minutes
Activity: Aggregations30 minutes

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.

What's included

9 videos3 assignments1 programming assignment1 discussion prompt

9 videosTotal 76 minutes

Modeling & Interpreting Data2 minutes
Overview of Modeling3 minutes
Modeling with Python14 minutes
Overview of Interpreting5 minutes
Interpreting Model Results8 minutes
Exploratory vs. Explanatory Visualizations4 minutes
Creating Explanatory Visualizations12 minutes
OSEMN: Tying It All Together12 minutes
Reviewing Full OSEMN Activity18 minutes

3 assignmentsTotal 80 minutes

Graded Quiz: Modeling and Interpreting Data with Python50 minutes
Knowledge Check on Modeling & Interpreting15 minutes
Knowledge Check on Interpreting15 minutes

1 programming assignmentTotal 90 minutes

Activity: Full OSEMN90 minutes

1 discussion promptTotal 10 minutes

Share Your Thoughts!10 minutes

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Instructor

Instructor ratings

(63 ratings)

Victor Geislinger

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5 stars
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1 star
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Showing 3 of 244

Reviewed on Nov 21, 2024

very interesting and easy for first time learner , with real world examples

Reviewed on Mar 1, 2025

Great course for learning Meta Marketing Analytics

Reviewed on Aug 30, 2024

A great course for beginners with goo course outline.

Frequently asked questions

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