Harry

“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

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

The Dataquest guarantee

Guarantee

Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.

Money

We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.

Master skills faster with Dataquest

Go from zero to job-ready

Go from zero to job-ready

Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.

Build your project portfolio

Build your project portfolio

Build confidence with our in-depth projects, and show off your data skills.

Challenge yourself with exercises

Challenge yourself with exercises

Work with real data from day one with interactive lessons and hands-on exercises.

Showcase your path certification

Showcase your path certification

Impress employers by completing a capstone project and certifying it with an expert review.

Grow your career with
Dataquest.

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of learners recommend
Dataquest for career advancement
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$30k
Average salary boost
for learners who complete a path
Aaron

Aaron Melton

Business Analyst at Aditi Consulting

“Dataquest starts at the most basic level, so a beginner can understand the concepts. I tried learning to code before, using Codecademy and Coursera. I struggled because I had no background in coding, and I was spending a lot of time Googling. Dataquest helped me actually learn.”

Jessi

Jessica Ko

Machine Learning Engineer at Twitter

“I liked the interactive environment on Dataquest. The material was clear and well organized. I spent more time practicing then watching videos and it made me want to keep learning.”

Victoria

Victoria E. Guzik

Associate Data Scientist at Callisto Media

“I really love learning on Dataquest. I looked into a couple of other options and I found that they were much too handhold-y and fill in the blank relative to Dataquest’s method. The projects on Dataquest were key to getting my job. I doubled my income!”

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