Python for Data Science — Numpy, Pandas, Matplotlib fundamentals

Categories: CSE, Data Science
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About Course

The Python for Data Science course introduces learners to the essential programming and analytical tools used in data science.
You’ll start with Python basics and quickly progress into data manipulation (NumPy & Pandas) and data visualization (Matplotlib & Seaborn) — the foundation of all analytics and machine learning workflows.

Through real datasets, coding exercises, and projects, this course helps you gain hands-on experience in data cleaning, transformation, and visualization, preparing you for advanced courses in Machine Learning, Data Analytics, and AI.

By the end, you’ll have the practical Python skills every data scientist or analyst needs to work with structured and unstructured data effectively.

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What Will You Learn?

  • Understand Python’s role in data science and analytics.
  • Use NumPy for numerical operations and array manipulation.
  • Master Pandas for data cleaning, transformation, and analysis.
  • Create visualizations using Matplotlib and Seaborn.
  • Perform exploratory data analysis (EDA) on real-world datasets.
  • Read, write, and process data from multiple sources (CSV, Excel, JSON).
  • Combine data programming logic with analytical thinking.
  • Build mini analytical projects using Python libraries.

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