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Practical Data Science with Python

This course explores the world of data science and gives you hands-on, practical tutorials on how to use Python at an advanced level.
Difficulty: Advanced
Duration: Up to 13 hours and 32 minutes
Students: 3,500
Rating: 3.7/5
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Content overview
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Content overview

9 steps
There are 5 Courses in this learning path
There are 3 Hands-on Labs in this learning path
There is 1 Exam in this learning path
Difficulty: Intermediate. Duration: 57m 23s.
COURSE
Intermediate
Duration: 57 minutes and 23 seconds
Practical Data Science With Python
This lesson explores what data science is, before moving onto how to use Python in a data science context.
Difficulty: Advanced. Duration: 49m 22s.
COURSE
Advanced
Duration: 49 minutes and 22 seconds
Working with Python
This Lesson explores a variety of Python features in a hands-on way, including functions, loops, dictionaries, and flow control.
Difficulty: Beginner. Duration: Up to 2h.
HANDS-ON LAB
Beginner
Duration: Up to 2 hours
Practical Data Science: Introduction to Python
This Lab provides you with a Jupyter notebook that introduces you to basic concepts in Python by explaining concepts and letting you write and run Python code.
Difficulty: Advanced. Duration: 59m 2s.
COURSE
Advanced
Duration: 59 minutes and 2 seconds
Statistics and NumPy
This Lesson delves into the theories across the topics of statistics, distributions, and standardization, as well as the NumPy library.
Difficulty: Beginner. Duration: Up to 4h.
HANDS-ON LAB
Beginner
Duration: Up to 4 hours
Python Development Playground
This Python development playground provides you with a ready-to-use in-browser Python integrated development environment (IDE) to easily play with Python.
Difficulty: Intermediate. Duration: 57m 18s.
COURSE
Intermediate
Duration: 57 minutes and 18 seconds
Working with Pandas
This Lesson explores Pandas and shows you how it can be used as a powerful data manipulation tool.
Difficulty: Beginner. Duration: Up to 2h 30m.
HANDS-ON LAB
Beginner
Duration: Up to 2 hours and 30 minutes
Using Python to Cleanse and Rationalize Data Challenge
You will put your basic knowledge of Python to work in this lab challenge in order to perform a simple form of data cleansing on text.
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