Data Analysis Using Python, Plotly and Jupyter Notebook

Name: Data Analysis Using Python, Plotly and Jupyter Notebook
Rating: 4.4 (6 reviews)

Learn to Transform, Visualize, and Share Your Data Insights

Created byRebecca Peltz

Last updated 1/2026

English

What you'll learn

Tell Powerful Data Stories
Master Data Import & Exploration
Gain a deep understanding of Python's fundamental data structures
Set Up Your Personalized Data Lab
Share Your Insights Globally
Transform Data with Pandas
Craft Meaningful Visuals with Plotly

Course content

8 sections • 10 lectures • 1h 57m total length

Introduction to Data Analysis8:47

Mac and Linux: Install and Setup to Create a Jupyter Notebook Locally10:37
Watch this video is you are working on a Mac or Linux environment. This lecture video will walk your through installing python and creating a virtual environment. Once you have the virtual environment set up you can use pip ('pip installs packages') to install the Jupyter and Pandas packages. With the installation and setup of the virtual environment in place, you can create a Jupyter notebook locally.
Windows: Install and Setup to Create a Jupyter Notebook Locally9:15
Watch this video is you are working in a Windows environment. This lecture video will walk your through installing python and creating a virtual environment. Once you have the virtual environment set up you can use pip ('pip installs packages') to install the Jupyter and Pandas packages. With the installation and setup of the virtual environment in place, you can create a Jupyter notebook locally.

Data Analysis Using Python Programming Wrap Up6:43
In this video there is a review of what has been learned and challenge to download the code from the course GitHub repository and get it running on a local computer. Once the Jupyter Notebooks are executing locally, students can study the projects ANIMATION and CORRELATION. There is a README markdown file that explains the data transformations and the creation of the visualizations.

Requirements

Introductory Python language skills
Familiarity with GitHub
Experience working with formatted data
Familiarity with basic graph types

Description

With a unique blend of technical expertise and educational insight, I bring real-world software development experience directly into the classroom. As a full-stack developer, I've built complete applications using Java, Python, and JavaScript across diverse industries, giving me practical knowledge of how these tools work in professional settings and how they solve real business challenges.

I specialize in data visualization, having created impactful visual analytics for both healthcare and business sectors. This hands-on experience informs how I teach data analysis—not just the theory, but the practical skills that make a real difference in understanding and communicating data insights. I've seen firsthand how the right visualization can transform complex data into clear, actionable decisions.

My educational background includes an MBA and a Master of Science in Curriculum Development, which means I don't just know the material—I know how to teach it effectively. I understand how people learn technical skills and design my lessons to build understanding step by step.

I'm committed to making programming accessible to everyone, regardless of their technical background, and I design my courses to build confidence alongside competence. I believe that anyone can learn to work with data when concepts are explained clearly and practiced consistently.

Whether you're taking your first steps into data analysis or adding new tools to your skillset, I'm here to guide you through the learning process with clarity, patience, and real-world perspective.

Who this course is for:

Data Analysts who want to use programming to develop custom graphs and dashboards
Python programmers who want to learn data analysis

Data Analysis Using Python, Plotly and Jupyter Notebook

What you'll learn

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Course content

INTRODUCTION: Creating and Sharing Data Analysis with Jupyter Notebooks1 lecture • 9min

INSTALL and SETUP: Python Virtual Environments for Creating Jupyter Notebooks2 lectures • 20min

HOSTING: Rendering Jupyter Notebook Locally and on GitHub1 lecture • 12min

PYTHON: Programming and Data Structures Refresher2 lectures • 31min

PANDAS: Python Package for Data Manipulation1 lecture • 13min

DATA: Accessing Real World and Fake Data1 lecture • 7min

PLOTLY: Python Package for Creating Data Visualizations1 lecture • 20min

WRAP UP: Data Analysis Using Python Programming Projects1 lecture • 7min

Requirements

Description

Who this course is for: