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Data Processing with Python (February 25)

Master using Python for data munging, processing, visualization, exploratory analysis and extracting data from public APIs.

Registration is now closed


February 25


Thursdays, 10:00AM EST
Thursdays, 10:00AM EDT


Four 2-hour instructor-led sessions via Zoom.

Weekly independent practice projects.

Data Processing with Python (February 25)

Registration is now closed

What will I learn?

Learn the ins and outs of the Pandas and Numpy libraries.

Master building insightful visualizations of your data.

Learn how to do time series analysis in Python.

Perform advanced data transformations using Python.

Learn how to translate everything you do in Excel into Python code.

Get hands-on experience with data processing and analysis using Python.

Course Curriculum

Session 1
Numpy Basics

Learn the basics of ndarrays and how to perform operations with them.

Session 2
Pandas Basics

Learn how to work with data using Pandas series and dataframes.

Session 3
Advanced Pandas and Data Visualization

Practice data cleaning, grouping, pivoting and visualization with Pandas and Matplotlib.

Session 4

With your instructor's guidance, use what you've learned in this class to build an end-to-end data analysis workflow.

Elite instructors

You learn from an elite team of industry experts who have taught at universities such as Harvard, and have trained teams at companies such as Qualcomm.

Sustained practice

You start coding from day one, and get valuable feedback, which is the fastest, most effective way to hone your skills and master programming.

Tailored feedback

You get personalized, live feedback and guidance directly from your instructors.

Fellowship and community

You gain access to a vibrant and engaging community of fellow students and knowledgeable mentors in every class.

Randi S., Edlitera student
Gaston G., Edlitera student

Course Syllabus

Module 1: Numpy Basics

    A: Intro to Numpy Arrays

    B: Operations with Numpy Arrays

Module 2: Pandas Basics

    A: Series and Dataframes

    B: Filtering, Slicing and Summarization

Module 3: Advanced Pandas & Data Visualization

    A: Data Cleaning with Pandas

    B: Grouping and Pivoting Data

    C: Data Visualization with Matplotlib

    D: How to Export Data, Results and Graphs

Module 4: Mini-Project

Frequently Asked Questions

1. Who is this course for?

This course is aimed at those who have a basic familiarity with Python and who want to learn to use Python for data processing, munging, visualization, exploratory analysis and leveraging public data and APIs.

2. Is this a MOOC (Massive Open Online Course)?

Nope. Your instructor is a real live person who talks to you in real time. Imagine you’re enrolled in a remote university course, and you’re attending one of the live classes. That’s the experience you get with this course.

3. What does the fee cover?

Your fee covers:

·      weekly classes taught live by the instructor via webinar

·      materials and resources used in this course

·      constant support and direct feedback on your work and progress from our instructors

4. Can my employer pay for this course on my behalf?

Yes.  Many of our students are employer-sponsored. Check with your employer about tuition benefits.

5. I want my team to take this course. Do you offer private training for companies?

We sure do. Check out our corporate training page for more information on the topics and formats we offer, or shoot us an email at [email protected]

6. I’m interested. What happens after I register?

After you register for this course, you get a confirmation email. You get a second email containing the details you need to hit the ground running on your first class, including:

·      recommended preparation for the first session

·      how to join the live classes

·      invitation to the online class community

7. What happens if I miss a live session?

Our courses are designed to give you the most effective and flexible learning experience available. If you miss a live session, watch the session recording the following day, and work through the weekly assignment as usual. And remember, your instructor is standing by during the week to answer your questions.

8. What if I have a question between sessions?

If you get stuck or have questions, your instructor and mentors are always available and happy to help get you unstuck—just ask.

9. What kind of weekly time commitment should I expect?

In addition to attending the 2-hour, weekly, instructor-led sessions, you should expect to spend around 2-3 hours per week studying and working on practice problems and projects.

10. Can I take this course if I live outside of the US?

Absolutely. All students, everywhere, are welcome to enroll in this English-language course.

11. What is your refund policy?

All course registration sales are final and non-refundable.

12. I have another question.

Drop us a note at [email protected]. We will get back to you ASAP.