Data Science for Everybody Interactive Learning Series

Free Online Interactive Learning Series

Hear what to expect from the 2nd edition of Data Science for Everybody from our Director Shannon Graybill:

If you want to get a grasp on the basics of Python for Data Science, this course is for you. We've built it for beginners who are taking their first steps into the world of data and want to prepare for advanced data science and machine learning courses, like Le Wagon’s Data Science Bootcamps.

Participants who complete this course will have the ability to go further in data collection and analysis using Python to automate certain tasks or data processing. Participants will be able to use modern tools to explore and visualize their data and make better decisions.

Who should take this course?

⚠️ You do not need to know how to code to take this course.

Data curious professionals 🙇🏻‍♀️ who are not yet working in the field of Data Science, but would love to learn more about what it means to work with large amounts of data.
Employees 👩‍💻 wishing to analyze large data sets with the right tools and methods to go beyond analysis in Excel.
Marketing teams 📈 who want to adopt a data-driven approach.
Managers or executives 💼 wishing to understand the challenges of modern data analysis.
Entrepreneurs 🚀 working on a data project.

Learning Modules

(1) Python for Beginners

(2) Handling a notebook

(3) Dictionaries

(4) Exploring data from a CSV

(5) Python Pandas

(6) Data Sourcing with APIs

(7) Data Sourcing with Scraping

How's this going down?

During the month of October, at lunchtime on Mondays, Wednesdays and Fridays, you can join our instructors live as they walk you through a new module each day with Le Wagon’s on demand Data Analytics course.

You will get access to:

- 11 live classroom sessions with our instructors where you can interact and ask questions,
- a private Slack channel with likeminded people and Le Wagon instructors,
- lifetime access to our proprietary platform with exercises, quizzes and everything for you to practice
- your very own certificate in case you show up to at least 9 of the classes and deliver your final project.

And remember... this series is for complete beginners and it's 100% free 🎁

I want to join! How does this work?

First, make sure that the program's schedule fits YOUR schedule!

Class Schedule 📆

The program will run from October 17th to November 6th. Live lectures are held on Monday, Wednesday, and Fridays from 1:00PM to 1:45PM.

Additionally, we'll provide two Buffer/Recap sessions on Thursdays (29/10 & 05/11) to answer your questions if you're struggling.

Attendee selection 🌟

On the first edition of Data-Science for Everybody, our applicants came from a variety of backgrounds! From international top companies data-curious, we want to make sure that the most engaged and motivated applicants receive a seat. Space is limited.

We'll reach out on October 16th with the selection results.

Track Record 💼

On the first edition of Data-Science for Everybody, our applicants came from a variety of backgrounds! From international top companies to data-curious individuals searching for their first introduction into data, we had it all! Employees from these companies took part in the first edition of Data Science for Everybody:

Group 18-2

F.A.Q.

1) What's a "Live Class"?

We'll jump on LiveStorm (a webinar platform) where lecturers will briefly explain the key takeaways of the module of the day. Then, we'll do some Live code together! Throughout the lecture, there are teachers answering to your questions and concerns, live on the same platform.

*Live Classes will be most useful for participants who complete the learn module on their own before the session.

2) What's "Slack"? What will I do there?

Slack is the communication platform we'll use to have all the members engaged and share all the info about the program. We'll use Slack to keep on communicating after each live class is over. You will have space to pose your doubts on code you've been doing, to check out other tech-events or to mingle with your fellow colleagues!

3) How is this different from other typical online courses?

	Your usual Online Course ⚠️	Data Science for Everybody 🤓
Lectures 🖥	Pre-recorded lectures with no live help for queries or doubts. 😫	Lectures are reviewed live and teachers will be answering all your questions during these live sessions. 👨‍🏫
Interaction 🤓	No space to interact with the community after each module.	Dedicated Slack channel with direction for further exercises and community interaction.
Going further ➡️	-	Prepare yourself to join Le Wagon's intensive bootcamps.

Price 💰	50-150€	FREE

4) What will I be able to do in the end?

The objective is for participants to walk away with a more foundational understanding on what it means to program with Python in Data Analytics. Participants who complete this course will have the ability to go further in data collection and analysis using Python to automate certain tasks or data processing. Participants will be able to use modern tools to explore and visualize their data and make better decisions.

This is also a tool for participants who want to do our full-time of part-time Data Science bootcamp to get super prepared before entering the demanding program.

5) What are the selection criteria to chose between candidates?

In the full application form, we’ll ask for your motivation.

Our goal with this program is to teach those that are in most need of new skills. We aim to give out the available seats to those that are more motivated and see the potential in this course.

6) Who's Le Wagon?

Le Wagon is Europe's leading coding school. We are now present in 38 cities worldwide, with over 120 startups in operation, and have been rated the nº1 coding bootcamp worldwide on Course Report & Switchup for 4 years in a row!

Our 9-week or 24-week, data science course equips aspiring data scientists the gives students the skills they need to launch their careers in a data science team. From Pandas to Deep Learning, students finish the course knowing how to explore, clean and transform data into actionable insights and how to implement machine learning models from start to finish in a production environment, working in teams with the best-in-class tool belt.