We may earn an affiliate commission when you visit our partners.

Operations on Arrays with NumPy

This course will teach you how to leverage NumPy to up your game in scientific programming, and show you how to use NumPy for numerical processing, including array indexing, math operations, and search.

Ideal for data scientists in any field, this overview shows you how to use NumPy for numerical processing, including array indexing, math operations, and search. In this course, Operations on Arrays with NumPy, you’ll learn how to interact and manipulate NumPy Arrays at will. First, you’ll explore how to do indexing, slicing and mask with binary operators. Next, you’ll discover how to perform both linear algebra as well as statistical operations with NumPy arrays. Finally, you’ll learn how to sort and search in them any element. When you’re finished with this course, you’ll have the skills and knowledge of NumPy arrays needed to manipulate them in any application you may need.

Enroll now

Or start your subscription today

And complete this course over a free trial

Here's a deal for you

We found an offer that may be relevant to this course.

Save money when you learn. All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

Valid for a limited time only

Future-proof your career

Access O'Reilly books, live events, courses, and more. Save with an annual subscription.

Take

15%

off

What's inside

Syllabus

Course Overview

Intoduction

Slicing and Indexing NumPy Arrays

Operating with NumPy Arrays

Searching in NumPy Arrays

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops data science skills, which are necessary for working with data and making informed decisions

Begins with fundamental data manipulation techniques, making it suitable for those new to the field

Examines statistical operations, which learners may use in professional roles

Facilitates array indexing and manipulation, crucial for working with arrays efficiently

Prepares learners for applying NumPy arrays in real-world scenarios, enhancing problem-solving abilities

Covers core principles of NumPy effectively, building a solid foundation for further learning

Save this course

Save Operations on Arrays with NumPy to your list so you can find it easily later:

Save

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Operations on Arrays with NumPy with these activities:

Review Linear Algebra topics

Show steps

Review the fundamental concepts of linear algebra to build a strong foundation for the course.

Browse courses on Linear Algebra

Show steps

Revisit concepts of vectors, matrices, and determinants.
Practice solving systems of linear equations.
Refresh your understanding of vector spaces and subspaces.

Build a NumPy cheat sheet for quick reference

Show steps

Create a concise cheat sheet that summarizes key NumPy functions and concepts for easy reference during the course.

Browse courses on NumPy

Show steps

Gather and organize essential NumPy functions and concepts.
Design and format the cheat sheet for clarity and accessibility.
Utilize the cheat sheet as a reference tool throughout the course.

Join a study group to discuss NumPy concepts

Show steps

Engage in peer discussions to enhance your understanding of NumPy concepts and exchange ideas.

Browse courses on NumPy

Show steps

Find or form a study group with fellow learners.
Schedule regular meetings to discuss course material.
Actively participate in discussions and contribute to the group's learning.

Three other activities

Expand to see all activities and additional details

Show all six activities

Follow tutorials on NumPy's indexing and array manipulation

Show steps

Reinforce your understanding of NumPy's indexing and array manipulation capabilities by following guided tutorials.

Browse courses on Array Manipulation

Show steps

Locate tutorials on NumPy indexing and array manipulation.
Follow the tutorials step-by-step, practicing the techniques.
Apply the learned techniques to solve exercises or small projects.

Solve practice problems on NumPy functions

Show steps

Enhance your proficiency in using NumPy functions through dedicated practice drills.

Browse courses on NumPy

Show steps

Identify practice problems that cover various NumPy functions.
Attempt to solve the problems independently.
Review your solutions and identify areas for improvement.

Contribute to an open-source NumPy project

Show steps

Deepen your understanding of NumPy and contribute to the community by participating in an open-source project.

Browse courses on NumPy

Show steps

Identify areas within NumPy projects where you can make contributions.
熟悉项目代码库并理解贡献指南.
Develop and test your proposed changes or additions.

Career center

Learners who complete Operations on Arrays with NumPy will develop knowledge and skills that may be useful to these careers:

Data Analyst

Working with large sets of structured data is a key part of a Data Analyst's job. NumPy can help make the manipulation and analysis of such data much simpler and this course provides a good foundation in the use of NumPy. Once you enroll in this course, you'll discover how to index, slice, and operate on NumPy arrays. You'll also learn linear algebra, statistical operations, and how to sort and search in NumPy arrays.

See salaries and explore the career path for Data Analyst

Data Scientist

NumPy is a foundational dependency among Data Scientists. This course can help you in the early stages of your Data Science career. By learning to use NumPy for numerical processing, including array indexing, math operations, and search, you'll lay a strong groundwork for future success.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

NumPy is a core dependency in the field of Machine Learning. This course can help you build a foundation for your Machine Learning Engineering career by teaching you how to use NumPy for numerical processing, including array indexing, math operations, and search.

See salaries and explore the career path for Machine Learning Engineer

Quantitative Analyst

Quantitative Analysts often work with complex datasets that need to be carefully analyzed. NumPy is useful for working with such datasets, and this course can help provide a grounding in the use of NumPy.

See salaries and explore the career path for Quantitative Analyst

Statistician

Statisticians often use NumPy for data analysis. This course can provide a valuable grounding in the use of NumPy and help Statisticians perform their jobs more efficiently.

See salaries and explore the career path for Statistician

Quantitative Researcher

Quantitative Researchers must be able to manage large amounts of data and NumPy is a popular tool for doing just that. This course can help build the necessary skills for a career as a Quantitative Researcher.

See salaries and explore the career path for Quantitative Researcher

Financial Analyst

Performing mathematical and statistical analyses of financial data is a fundamental task of a Financial Analyst. NumPy can help automate many of these operations, and this course can help develop the skills needed to do so.

See salaries and explore the career path for Financial Analyst

Investment Analyst

Investment Analysts often use NumPy to perform data analysis and modeling. This course can help build the skills needed to work as an Investment Analyst and potentially accelerate career growth.

See salaries and explore the career path for Investment Analyst

Actuary

Actuaries use NumPy for financial computations and analysis. This course can provide a valuable grounding in the use of NumPy, which can help support Actuarial work.

See salaries and explore the career path for Actuary

Risk Analyst

Risk Analysts must be able to effectively work with data. NumPy can help Risk Analysts to perform their jobs more efficiently. This course can help build the skills for working with NumPy.

See salaries and explore the career path for Risk Analyst

Data Engineer

Working with big data often requires an understanding of NumPy. This course can provide the necessary grounding that may be required for success as a Data Engineer.

See salaries and explore the career path for Data Engineer

Operations Research Analyst

Operations Research Analysts often utilize NumPy for optimization and modeling. This course may be helpful for Operations Research Analysts who need to understand the fundamentals of working with NumPy.

See salaries and explore the career path for Operations Research Analyst

Financial Risk Manager

Financial Risk Managers may find NumPy to be a useful tool for data analysis. This course can develop the skills required to use NumPy on the job.

See salaries and explore the career path for Financial Risk Manager

Business Analyst

Business Analysts use NumPy to process and analyze business data. This course can help in building skills that may be useful as a Business Analyst.

See salaries and explore the career path for Business Analyst

Software Engineer

A Software Engineer must be proficient in many areas of programming. Many Software Engineers who work with data may find NumPy to be a useful library and this course may be helpful to them.

See salaries and explore the career path for Software Engineer

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Operations on Arrays with NumPy.

Python for Data Analysis

Save

Comprehensive guide to NumPy. While this book does require some knowledge of Python programming to read and understand, it covers almost everything you need to know about NumPy. This book covers all the topics of this course as well as many more.

Operations on Arrays with NumPy

Here's a deal for you

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

Share

Similar courses