Updated - Jul 20, 2024
SPECIAL OFFER
Pandas
Purpose: A library for data manipulation and analysis in Python.
Key Features: Provides data structures like DataFrames and Series for
handling tabular data. It supports operations such as filtering, grouping, merging, and reshaping.
Use Case: Ideal for cleaning, transforming, and analyzing structured data.
Price: N50,000
Duration: Two (2) Months
Matplotlib
Purpose: A plotting library for creating static, animated, and interactive visualizations in Python.
Key Features: Offers a variety of plot types, such as line plots, bar charts, and scatter plots. Highly customizable for fine-tuning visuals.
Use Case: Used to generate graphs and charts for data analysis and presentation.
Price: N50,000
Duration: Two (2) Months
Scikit-Learn
Purpose: A library for machine learning in Python.
Key Features: Provides tools for classification, regression, clustering, and dimensionality reduction. Includes algorithms like decision trees, SVMs, and k-means.
Use Case: Useful for building and evaluating predictive models and performing data analysis tasks.
Price: N50,000
Duration: Two (2) Months
NumPy
Purpose: A library for numerical computing in Python.
Key Features: Offers support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays.
Use Case: Essential for performing numerical calculations and handling large datasets efficiently. Often used as a foundation for other scientific computing libraries.
Price: N50,000
Duration: Two (2) Months
These libraries are fundamental tools in the Python data science ecosystem,
each serving a distinct purpose in data analysis, visualization, machine learning,
and numerical computations.
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