Course

NumPy for Data Engineering

In this course, you’ll learn the fundamentals of NumPy, one of the most popular Python libraries. It provides support for multi-dimensional arrays, and it allows you to perform a wide variety of calculations on those arrays.

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Part of the Data Engineer (Python) path.

4.8 (359 reviews)

2,841 learners enrolled in this course.

Intermediate friendly
4 hours
Self paced
5 lessons

“Dataquest not only teaches you the fundamentals, but also teaches you how to keep learning…so you’re never stuck.”

Harry Robinson

Head of Business Intelligence @Philips

NumPy for Data Engineering

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Course overview

Python programming skills are critical for data engineering. But for many critical data analysis and processing tasks, using stock Python isn’t the most efficient approach. That’s where NumPy comes in.
In this course, you’ll learn how to manipulate data using NumPy – it’s much more efficient than Python alone if you’re working with large amounts of data.
Best of all, you’ll learn by doing – you’ll practice and get feedback directly in the browser.

Key skills

Manipulating n-dimensional arrays
Performing numeric calculations with n-dimensional arrays
Identifying the differences between NumPy and pure Python

Course outline

NumPy for Data Engineering [5 lessons]

Introduction to NumPy 1h

Lesson Objectives

Import the NumPy module.
What 1-dimensional and 2-dimensional array is.
Alter values in an array
Select parts of a ndarray through slicing

Arithmetic with NumPy Arrays 1h

Lesson Objectives

Make calculations using ndarrays
Identify why these calculations run faster than operations on lists
Define Single Instruction Multiple Data (SIMD)

Broadcasting NumPy Arrays 1h

Lesson Objectives

Perform arithmetic operations between ndarrays and values
Perform arithmetic operations between 1-dimensional arrays and 2-dimensional arrays
Change the shape of a ndarray

Datasets and Boolean Indexing 1h

Lesson Objectives

Load a CSV into a ndarray
Identify NumPy limitations with non-numerical data
Employ comparison operations in NumPy
Employ logical operators in NumPy
Extract data using Boolean masks

NumPy Datatypes 1h

Lesson Objectives

Identify the datatypes available in NumPy
Identify ndarray data type limitations
Set the datatype of a ndarray
Evaluate the memory consumption of a ndarray
Identify the limitations of fixed-bit length number representations

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