Online or onsite, instructor-led live Pandas training courses demonstrate through interactive hands-on practice how to use Pandas to perform data analysis, predictive analysis, and machine learning.
Pandas training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Ostrava onsite live Pandas trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
Pandas is also known as Python Pandas.
NobleProg -- Your Local Training Provider
Ostrava
NobleProg Ostrava, Října 205/45, Ostrava, Czech Republic, 70200
You'll reach Platan Office thanks to the bus stop at Divadlo Loutek, just a 2-minute walk away. Leoš Janáček Airport Ostrava is located 25 km away. Platan Office have breakout area for time away from your desk or get fresh air on the rooftop terrace.
This instructor-led, live training in Ostrava (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.
This instructor-led, live training in Ostrava (online or onsite) is aimed at data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis.
By the end of this training, participants will be able to:
Set up the necessary environment to start developing Pandas workflows at scale with Modin.
Understand the features, architecture, and advantages of Modin.
Know the differences between Modin, Dask, and Ray.
Perform Pandas operations faster with Modin.
Implement the entire Pandas API and functions.
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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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