4.4
Beginner
4h 10min
Updated 2 months ago
Introduction to Data Science with Python
Delve into foundational Python programming, explore libraries like pandas and Matplotlib, and gain insights into data management, analysis, and visualization with practical projects.
Python is one of the most popular programming languages for data science and analytics. It’s used across a wide range of industries. It’s easy to learn, highly flexible, and its various libraries can expand functionality to natively perform statistical functions and plotting.
This course is a comprehensive introduction to statistical analysis using Python. You’ll start with a step-by-step guide to the fundamentals of programming in Python. You’ll learn to apply these functions to numerical data. You’ll first look at strings, lists, dictionaries, loops, functions, and data maps. After mastering these, you’ll take a deep dive through various Python libraries, including pandas, NumPy, Matplotlib, Seaborn, and Plotly. You’ll wrap up with guided projects to clean, analyze, and visualize unique datasets using these libraries.
By the end of this course, you will be proficient in data science, including data management, analysis, and visualization.
Python is one of the most popular programming languages for data science and analytics. It’s used across a wide range of industr...Show More
WHAT YOU'LL LEARN
A deep familiarity with various data functions of Python
The ability to visualize statistical data using Matplotlib and Plotly libraries
A working knowledge of the pandas and NumPy libraries for data cleaning and analysis
A strong proficiency in the basics of data science and the Python programming language
A deep familiarity with various data functions of Python
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Content
2.
Python Essentials
14 Lessons
Get started with essential Python data types, operators, looping, functions, and challenges.
3.
NumPy: Data Analysis
10 Lessons
Work your way through NumPy essentials, manipulating arrays, and performing Boolean masking and arithmetic operations.
4.
Pandas: Data Analysis
12 Lessons
Apply your skills to manipulate, clean, merge, and analyze data using pandas efficiently.
5.
Matplotlib: Data Visualization
11 Lessons
Deepen your knowledge of using Matplotlib for creating and customizing data visualizations.
6.
Seaborn: Statistical Data Visualization
14 Lessons
Focus on mastering statistical data visualization using Seaborn's diverse plotting capabilities.
7.
Pandas: Data Visualization
5 Lessons
Practice using Pandas' robust data visualization tools to create professional, customized plots.
8.
Plotly: Interactive Data Visualization
3 Lessons
Try out Plotly for creating interactive visualizations and geographical plotting using maps.
9.
Project 1: Oil vs Banks During Recession
7 Lessons
Get started with analyzing bank and oil stocks using EDA, visualizations, and moving averages.
10.
Project 2: Emergency Calls Dataset
7 Lessons
Work your way through emergency call data analysis with advanced visualization techniques.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Course Author:
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