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Complete Guide to NumPy, Pandas, SciPy, Matplotlib & Seaborn

4.30
11,497 students
4h 28m
Updated Apr 2026

What you'll learn

Introduction to Python for Data Science
Overview of NumPy, Pandas, Matplotlib, and SciPy
Creating NumPy Arrays
Mathematical Operations with NumPy Arrays
Working with Random Numbers and Simulations
Advanced Array Manipulation and Linear Algebra
NumPy for Statistical Computations (Mean, Median, Standard Deviation)
Performance Optimization with NumPy
Loading and Saving Data with Pandas (CSV, Excel, SQL, etc.)
Indexing, Selecting, and Filtering Data in DataFrames
Advanced Pandas Techniques
Matplotlib Data Visualization
Seaborn Advanced Visualization Techniques
SciPy Scientific Computing
Combining Libraries for Real World Data Science
And more........

Course Description

Are you ready to unlock the full potential of Python for data science, analytics, and scientific computing? Whether you're a beginner eager to enter the world of data or an experienced programmer looking to deepen your skills, this course is your complete resource for mastering the core Python libraries: NumPy, Pandas, SciPy, and Matplotlib/Seaborn.


This hands-on, project-driven course is designed to take you from the basics all the way to advanced techniques in data analysis, numerical computing, and data visualization. You'll learn how to work with real-world datasets, perform complex data operations, and create stunning, publication-quality visualizations.


What You’ll Learn:

  • NumPy – Work with multidimensional arrays, broadcasting, indexing, and performance optimization

  • Pandas – Master dataframes, series, grouping, filtering, merging, and time series data

  • SciPy – Dive into scientific computing with optimization, statistics, interpolation, signal processing, and more

  • Matplotlib & Seaborn – Create insightful and beautiful visualizations, from basic plots to advanced charts

  • Data Workflow – Clean, transform, and prepare data for analysis and modeling


Why Take This Course?

  • Taught by experienced data professionals

  • Practical, hands-on learning with real-world datasets

  • Covers both the theory and the application

  • Builds a solid foundation for advanced data science and machine learning


By the end of this course, you'll be confident in your ability to manipulate, analyze, and visualize data using Python’s most essential libraries — a skill set that's in high demand across industries.


Enroll now and start your journey into data mastery today!

Requirements

  • Basic understanding of Python programming (variables, data types, loops, functions).
  • No prior experience with NumPy, Pandas, SciPy, Matplotlib, or Seaborn is required.
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Complete Guide to NumPy, Pandas, SciPy, Matplotlib & Seaborn

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Course Details

  • Level All Levels
  • Lectures 29
  • Duration 4h 28m