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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.

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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

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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

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

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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

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

Browse courses on NumPy

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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

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

Browse courses on NumPy

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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

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Follow tutorials on NumPy's indexing and array manipulation

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

Browse courses on Array Manipulation

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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

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

Browse courses on NumPy

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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

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

Browse courses on NumPy

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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

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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

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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