Short Description
Improve your Python programming and data science skills and solve over 100 exercises in NumPy!
What you’ll learn
- solve over 100 exercises in NumPy
- deal with real programming problems in data science
- work with documentation and Stack Overflow
- guaranteed instructor support
This course includes:
- On-demand video
- 107 articles
- 103 coding exercises
- Full lifetime access
- Access on mobile and TV
- Certificate of completion
Requirements
- completed course ‘200+ Exercises – Programming in Python – from A to Z’
- completed course ‘210+ Exercises – Python Standard Libraries – from A to Z’
- completed course ‘150+ Exercises – Object Oriented Programming in Python – OOP’
- basic knowledge of NumPy library
Description
RECOMMENDED LEARNING PATH
- 200+ Exercises – Programming in Python – from A to Z
- 210+ Exercises – Python Standard Libraries – from A to Z
- 150+ Exercises – Object Oriented Programming in Python – OOP
- 100+ Exercises – Unit tests in Python – unittest framework
- 100+ Exercises – Python Programming – Data Science – NumPy
- 100+ Exercises – Python Programming – Data Science – Pandas
- 100+ Exercises – Python – Data Science – scikit-learn
- 250+ Exercises – Data Science Bootcamp in Python
COURSE DESCRIPTION
100+ Exercises – Python Programming – Data Science – NumPy
Welcome to the course 100+ Exercises – Python Programming – Data Science – NumPy, where you can test your Python programming skills in data science, specifically in NumPy.
The course is designed for people who have basic knowledge in Python and NumPy library. It consists of 100 exercises with solutions.
This is a great test for people who are learning the Python language and data science and are looking for new challenges. Exercises are also a good test before the interview.
If you’re wondering if it’s worth taking a step towards Python, don’t hesitate any longer and take the challenge today.
Who this course is for:
- everyone who wants to learn by doing
- everyone who wants to improve their Python programming skills
- everyone who wants to improve their data science skills
- everyone who wants to prepare for an interview
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