Complete Guide To Numpy, Pandas, Scipy, Matplotlib & Seaborn
Published 7/2025
Created by Sheikh Coding Institute
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 29 Lectures ( 4h 28m ) | Size: 1.55 GB
Boost your data science skills by mastering NumPy, Pandas, SciPy, and powerful visualization tools in Python.
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........
Requirements
Basic understanding of Python programming (variables, data types, loops, functions).
No prior experience with NumPy, Pandas, SciPy, Matplotlib, or Seaborn is required.
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 optimizationPandas - Master dataframes, series, grouping, filtering, merging, and time series dataSciPy - Dive into scientific computing with optimization, statistics, interpolation, signal processing, and moreMatplotlib & Seaborn - Create insightful and beautiful visualizations, from basic plots to advanced chartsData Workflow - Clean, transform, and prepare data for analysis and modelingWhy Take This Course?Taught by experienced data professionalsPractical, hands-on learning with real-world datasetsCovers both the theory and the applicationBuilds a solid foundation for advanced data science and machine learningBy 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!
Who this course is for
Anyone interested in mastering the core Python libraries for data manipulation, analysis, and visualization.
Students and professionals looking to enhance their data driven skills.
Machine Learning Engineers who need to manipulate and understand data effectively.
Python developers looking to transition into data science.
Complete Guide To Numpy, Pandas, Scipy, Matplotlib & Seaborn
