Master Data Science with Python: NumPy, Pandas, Matplotlib & Seaborn

What you will learn:

Master the fundamentals of NumPy, Pandas, Matplotlib, and Seaborn libraries.
Gain proficiency in manipulating arrays, DataFrames, and Series.
Learn to perform data cleaning, transformation, and aggregation.
Create visually appealing and informative visualizations.
Prepare your data for machine learning and other advanced analysis.

Description

Dive deep into the essential Python libraries for data science and machine learning. This comprehensive course will equip you with the skills to handle data, perform in-depth analysis, and create compelling visualizations.

You'll gain mastery over NumPy, Pandas, Matplotlib, and Seaborn, covering everything from basic operations to advanced techniques. Learn to:

Manipulate data using NumPy's powerful arrays and matrices
Analyze and process data efficiently with Pandas DataFrames
Create visually engaging plots and charts with Matplotlib and Seaborn
Prepare your data for machine learning and more!

This course is ideal for anyone seeking a solid foundation in Python for data science, aspiring machine learning practitioners, or individuals looking to enhance their data analysis skills.

Curriculum

Python Fundamentals Refresher

This section serves as a quick review of fundamental Python concepts essential for data science. We'll cover variables, conditional statements (if, else, elif), loops (while, for), and common data structures such as lists, tuples, sets, and dictionaries. This ensures you have a solid grasp of the basics before diving into data manipulation libraries.

Data Manipulation with NumPy

Unleash the power of NumPy for efficient numerical computations. We'll cover creating and manipulating arrays, understanding indexing and slicing, performing mathematical operations, sorting, searching, and filtering data. You'll gain expertise in manipulating arrays of various dimensions and working with matrices.

Data Analysis with Pandas

Pandas is the cornerstone of data analysis in Python. Learn to create and work with Series and DataFrames, perform data cleaning, transformation, and aggregation, and handle missing values. You'll master techniques for querying, filtering, and grouping data, making data analysis seamless and efficient.

Data Visualization with Matplotlib

Visualize your data effectively using Matplotlib, the go-to library for plotting in Python. Learn to create line graphs, bar graphs, scatter plots, histograms, pie charts, and 3D plots. Explore various customization options to create visually appealing and informative charts.

Enhancing Visualizations with Seaborn

Seaborn builds upon Matplotlib to create visually stunning and informative statistical visualizations. We'll explore popular visualizations like swarm plots, violin plots, and heatmaps. These visualizations help you gain deeper insights into your data's distributions and relationships.

Hands-on Projects and Real-World Applications

Put your newfound knowledge to the test through a series of real-world projects. Analyze datasets like airline data, identifying patterns and insights. These practical exercises will solidify your understanding and prepare you for real-world data science challenges.