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Beginner's Guide to Python Arrays

Learn about the power of Python Arrays and how they apply as Data Structures

4.55 / 5.0
2356 students1 hours 15 minutes

Created by Gaurav Singh, offered on Udemy

bestcourses score™

Student feedback

5.1/10

To make sure that we score courses properly, we pay a lot of attention to the reviews students leave on courses and how many students are taking a course in the first place. This course has a total of 2356 students which left 11 reviews at an average rating of 4.55, which is average.

Course length

8.5/10

We analyze course length to see if courses cover all important aspects of a topic, taking into account how long the course is compared to the category average. This course has a length of 1 hours 15 minutes, which is pretty short. This might not be a bad thing, but we've found that longer courses are often more detailed & comprehensive. The average course length for this entire category is 7 hours 54 minutes.

Overall score

5.8/10

This course currently has a bestcourses score of 5.8/10, which makes it an average course. Overall, there are probably better courses available for this topic on our platform.

Description

Arrays are a powerful means of storing variables of the same data type (Integer, Float, String, etc.). Compared to their counterpart Data Structures, they provide many benefits, be it:

  • Faster processing

  • Compact memory usage

  • Easy access to data elements, or

  • Simpler operations with less coding effort

To give you some context, if you have worked on Pandas DataFrames, which is a special case of 2 Dimensional Arrays, you would know what different operations you can perform and how you can handle datasets more effectively. Well with Arrays you can do most of that and much more and for that very reason they are used as the preferred Data Containers to run Machine Learning algorithms (in Modules such as Scipy and Scikit-learn).

To simply put, "A good command on Arrays will take your understanding of Data Structures and their use to the next level", and this is exactly where this course comes in. Even if you've not worked on Arrays earlier, you can use this course to develop your understanding grounds-up.

Here we cover, "Arrays as Data Structures and how they get applied in Python". Below are the key areas that this course addresses :

  1. Intuition of Arrays as Data Containers

  2. Visualizing 2D/3D and higher dimensional Arrays

  3. Array Indexing and Slicing - 2D/3D Arrays

  4. Performing basic operations using Numpy Arrays

By the end of this course, you will be able to use Arrays in common data operations and data analysis. This will also give you a platform and confidence to quickly scale up to learn more advanced topics related to Numpy.

What you will learn

  • Develop understanding of how Python Arrays work and what advantages they offer over other Data Structures
  • Create Arrays of Different Dimensions
  • Arrays Visualization - 2dD, 3D, 4D and higher dimensional Arrays
  • Array Attributes and how to use them to know more about Arrays
  • Use Arrays as Data containers for Common Data Operations

Requirements

  • Basic knowledge of Python (including Data Types and Structures, For Loops, List Comprehension, etc.)
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Frequently asked questions

  • Price: Free
  • Platform: Udemy
  • Language: English
  • 1 hours 15 minutes
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bestcourses score: 5.8/10

There might be better courses available for this topic.