1- The prep work

The Practical Data Science program is a 8 weeks part-time micro-class to get you launched into the world of python data analysis 🐍.  

1. The prep work serves to test how comfortable you are with python.

Some of you will breeze through it, some will enjoy the refresher, and others might want to stop by our Python Essentials course before starting this one. Please don't fret about it, and have fun!

👉 Start your prep work 👈

2 . Workstation setup

Make sure to go through workstation setup before the first live course.
The workstation setup should take anywhere from 15mn to 1hr depending on your coding/terminal experience (and how fast your internet connection is cause that conda download is chunky…).  

practical-data-scientist/workstation_setup.md at main · JungleProgram/practical-data-scientist
Contribute to JungleProgram/practical-data-scientist development by creating an account on GitHub.

2- Questions

If you have any questions or need help with the prep work, please book the day and time that works best for you for a 15 min call.

📞 Book a call

3- Alumni

Alumni story: Leonie Malzacher combines aerospace engineering and Data Science 🚀
Read Leonie’s story of how she did her research about aeroelasticity at MIT & TU Berlin, how she does data analysis in aerospace engineering, and you will know more about her new challenges as a Machine Learning engineer in the aerospace industry.
Alumni story: Amine Amanzou, from DevOps to Machine Learning Engineer.
Read Amine’s story of how he started his career as DevOps at Orange, his passion for building drones, and you will know how he’s using data science and machine learning skill tree to capture the emotions through his drone in dangerous environments.
Alumni story: Sofiane Kab, when Data Science Meets Epidemiology 🦠
Read Sofiane’s story. You will know how he is using a massive database for his research about hypertension and cardiovascular diseases. The importance of gaining skills in data visualisation with Python. His favorite project combining data science & epidemiology.