Whether delivered online or on-site, our instructor-led live Pandas training programs utilize interactive, hands-on exercises to demonstrate how to leverage Pandas for data analysis, predictive analytics, and machine learning tasks.
This Pandas training is offered as either "online live training" or "onsite live training." Online live training, also referred to as "remote live training," is conducted through an interactive remote desktop session. Onsite live training can be hosted locally at your customer premises in Lille or at NobleProg's corporate training centers in Lille.
Pandas is commonly referred to as Python Pandas.
NobleProg – Your Regional Training Provider
Lille, Gare Flandres
NobleProg Lille, 21 Avenue le Corbusier, Lille, france, 59800
In front of Flandres TGV Train Station
From Lille train stations
From Lille-Flandres: the address is essentially right next to the station — about 1–3 minutes on foot.
From Lille-Europe: walk toward Lille-Flandres along Avenue Le Corbusier. It is roughly 5–10 minutes on foot.
So you don't need a bus or metro if you're arriving by train.
If you're coming by bus
The nearest bus stops to Avenue Le Corbusier include Lion d'Or and Jacquet. Several local lines serve the area, including 13, 86, L5 and L91.
This instructor-led, live training in Lille (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.
By the end of this training, participants will be able to:
Set up a development environment that includes Python, Pandas, and NumPy.
Create a data analysis application using Pandas and NumPy.
Perform advanced data wrangling, sorting, and filtering operations.
Conduct aggregate operations and analyze time series data.
Visualize data using Matplotlib and other visualization libraries.
Debug and optimize their data analysis code.
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Testimonials (1)
Trainer develops training based on participant's pace
Farris Chua
Course - Data Analysis in Python using Pandas and Numpy
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