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30 Days of Python Code: NumPy Challenge
30天Python代码：NumPy挑战，参加30天NumPy挑战：深入研究Python代码-提升您的技能并掌握NumPy的数据操作！ | Udemy付费课程限时免费 | Udemy Coupon | Udemy优惠码 | Udemy免费课程

Udemy课程介绍

The “30 Days of Python Code: NumPy Challenge” course is a unique, hands-on program designed to elevate your Python programming skills by honing in on one of Python’s most powerful libraries: NumPy. This course is ideal for those already comfortable with Python basics and are looking to deepen their knowledge of numerical computing within the Python ecosystem.

Over the course of 30 days, you’ll undertake a range of coding exercises designed to familiarize you with the power and flexibility of the NumPy library. The course covers NumPy’s core features such as arrays, array indexing, datatypes, array math, broadcasting, and more. Each day presents a new challenge, pushing you to apply and reinforce what you’ve learned, ensuring that your understanding of NumPy is comprehensive and well-rounded.

The course is highly interactive, allowing you to learn by doing, which is widely recognized as one of the most effective ways to learn programming. This approach fosters practical problem-solving skills and creativity, as you are tasked with finding solutions to real-world programming problems.

In addition, the course provides detailed solutions and explanations for each coding exercise, enabling you to compare your solutions with best practices. This way, you not only learn about the correct approach, but also gain insight into the reasoning behind it, improving your coding and debugging skills.

This “30 Days of Python Code: NumPy Challenge” course is perfect for anyone aiming to use Python for data analysis, data science, or machine learning, and wants to leverage the power of NumPy to work with numerical data efficiently.

NumPy – Unleash the Power of Numerical Python!

NumPy, short for Numerical Python, is a fundamental library for scientific computing in Python. It provides support for arrays, matrices, and a host of mathematical functions to operate on these data structures. This course is structured into various sections, each targeting a specific feature of the NumPy library, including array creation, indexing, slicing, and manipulation, along with mathematical and statistical functions.

Topics you will find in the basic exercises:

arrays creation

shapes, reshaping arrays

dimensions

size

indexing

slicing

arrays manipulation

math, statistic & calculations

dates

random

comparing arrays

broadcasting

saving, loading & exporting

appending, concatenating & stacking arrays

sorting, searching & counting

filtering

boolean mask

image as an array

dealing with missing values

iterating over arrays

linear algebra

matrix multiplication

polynomials

solving systems of equations

arrays with characters

functional programming & universal functions

dummy encoding

and other

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