Intermediate

Data Analysis with Python (pandas, numpy, matplotlib)

24 hours

Data cleaning with pandas, numerical operations with numpy and visualization with matplotlib — using a real dataset.

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Who It's For

Suitable for both academic researchers and corporate teams.

Prerequisites

Basic Python knowledge (the "Python from Scratch" course or equivalent)

Learning Outcomes

Data manipulation with pandas DataFrames
Cleaning missing/outlier data
Vectorized computation with numpy
Creating charts with matplotlib/seaborn

Program

pandas Basics

DataFrame and Series
Reading data (CSV/Excel)

Data Cleaning

Handling missing data
Outlier detection

Grouping and Merging

groupby/agg
merge/join

Visualization

matplotlib basics
Statistical charts with seaborn

Tools Used

Python (pandas, numpy, matplotlib) Jupyter Notebook

Frequently Asked Questions

Why Python instead of R?

Both can be taught; most participants prefer Python for its general-purpose use and broad library ecosystem, but the course can be adapted to R on request.

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