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.
4.4
85 Lessons
4h 10min
Updated 1 month ago
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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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