Published 12/2022
Created by Maxime Vandegar
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 27 Lectures ( 3h 34m ) | Size: 1.13 GB
Bottom-up introduction to Python data science frameworks: NumPy and Pandas
What you’ll learn
NumPy arrays
Operations on NumPy arrays
Image processing with NumPy
Vectorial operations
The framework Pandas
Pandas DataFrame
Manipulating Pandas DataFrame
Arithmetic operations and statistical computations
Requirements
Basic programming skills
Description
Are you ready to take your data skills to the next level? Our course on Pandas and NumPy is designed to help you master these powerful libraries and unlock the full potential of your data.Pandas and NumPy are two of the most popular Python libraries for data manipulation and analysis. Together, they provide a powerful toolset for working with structured data in Python and enable you to perform complex data tasks with ease and efficiency.In this course, you will learn the fundamentals of Pandas and NumPy and how to use them to solve real-world data problems. You will learn how to load and manipulate data with Pandas, perform mathematical operations and statistical analyses with NumPy, and use the two libraries together to solve complex data tasks.Our experienced instructors will guide you through the material with hands-on examples and exercises, and you will have the opportunity to apply your knowledge to real-world datasets. By the end of the course, you will have a solid understanding of Pandas and NumPy and be able to use them confidently in your own data projects.Don’t miss this opportunity to learn from the experts and take your data skills to the next level. Enroll now and join our community of data professionals who are mastering Pandas and NumPy and making a difference with data.
Who this course is for
To those interested in data science and machine learning
For those who want to improve their Python knowledge
For those who want to improve the performance of their Python code
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