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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.

4.5

85 Lessons

2 Projects

4h 10min

Join 2.9 million developers at

LEARNING OBJECTIVES

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

Learning Roadmap

85 Lessons7 Quizzes11 Challenges

Introduction

Get familiar with essential data science skills using Python for business intelligence.

About the Course

Python Essentials

Get started with essential Python data types, operators, looping, functions, and challenges.

Tuples, Sets and Booleans

Comparisons

Loops

Functions

Lambda Expression, Map and Filter

Challenge 1: Python Essentials

Solution: Python Essentials

Challenge 2: Python Essentials

Solution 2: Python Essentials

Quiz: Python’s Essentials

NumPy: Data Analysis

10 Lessons

Work your way through NumPy essentials, manipulating arrays, and performing Boolean masking and arithmetic operations.

Pandas: Data Analysis

12 Lessons

Apply your skills to manipulate, clean, merge, and analyze data using pandas efficiently.

Matplotlib: Data Visualization

11 Lessons

Deepen your knowledge of using Matplotlib for creating and customizing data visualizations.

Seaborn: Statistical Data Visualization

14 Lessons

Focus on mastering statistical data visualization using Seaborn's diverse plotting capabilities.

Data Visualization with Seaborn for Walmart Sales Projection

Project

Premium

Pandas: Data Visualization

5 Lessons

Practice using Pandas' robust data visualization tools to create professional, customized plots.

Data Visualization with Seaborn for Walmart Sales Projection

Project

Premium

Plotly: Interactive Data Visualization

3 Lessons

Try out Plotly for creating interactive visualizations and geographical plotting using maps.

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.

11.

In Closing

Grasp the fundamentals of data visualization, plot management, and combining datasets effectively.

Conclusion

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Developed by MAANG Engineers

ABOUT THIS COURSE

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.

ABOUT THE AUTHOR

Dr. Junaid Qazi

Dr. Junaid Qazi is a subject matter specialist, data science, machine learning and blockchain consultant. He is a team builder, advisor, professional development coach, mentor, author, technical writer, and invited speaker in his domain of expertise.

Learn more about Dr.

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