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

NumPy is a powerful python library that provides N-dimensional arrays and functions to perform scientific computing. In this course, you’ll learn the basics of NumPy, its data types and attributes, and NumPy array creation in different scenarios.

NumPy, which is short for Numerical Python, is a very crucial library of Python when working in the field of data science.

In this course, Getting Started with NumPy, you'll learn everything about NumPy and the N-dimensional array (ndarray).

First, you'll start by understanding what NumPy is and do an in-depth study on its history, purpose, usage, advantages, etc.

Read more

NumPy is a powerful python library that provides N-dimensional arrays and functions to perform scientific computing. In this course, you’ll learn the basics of NumPy, its data types and attributes, and NumPy array creation in different scenarios.

NumPy, which is short for Numerical Python, is a very crucial library of Python when working in the field of data science.

In this course, Getting Started with NumPy, you'll learn everything about NumPy and the N-dimensional array (ndarray).

First, you'll start by understanding what NumPy is and do an in-depth study on its history, purpose, usage, advantages, etc.

Next, you'll see how to install the NumPy library into your system.

Then, you'll take a look into ndarray and study its attributes and some basic but important functions.

Finally, you'll dive into creating NumPy arrays in different ways, like creating an empty array, an array with a specified range, or an array from existing data, depending upon your requirements.

When you’re finished with this course, you'll have a good understanding of NumPy and ndarray with the skills to create and maintain ndarray in various scenarios, and will be ready to move on to the next step where you can perform complex scientific computations using NumPy functions or use ndarray as an input in other Python libraries.

Enroll now

What's inside

Syllabus

Course Overview
Introduction to NumPy
Setting up a Work Environment for NumPy
Understanding the Ndarray Object
Read more
Creating Ndarrays

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores NumPy, which is standard in industry scientific computing
Teaches NumPy, which helps learners perform efficient scientific computing operations
Examines NumPy arrays, which are core to scientific computing in Python
Develops skills in creating NumPy arrays in various ways, which is a fundamental skill for scientific computing

Save this course

Save Getting Started 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 Getting Started with NumPy with these activities:
Review NumPy fundamentals
Refresh your understanding of NumPy's data types, attributes, and basic functions to ensure a strong foundation for the course.
Browse courses on NumPy
Show steps
  • Revisit the NumPy documentation for refresher
  • Complete practice exercises on creating and manipulating arrays
Explore NumPy documentation and tutorials
Deepen your understanding of NumPy's capabilities by exploring its official documentation and external tutorials.
Browse courses on NumPy
Show steps
  • Review the NumPy User Guide for comprehensive information
  • Find beginner-friendly tutorials on creating and manipulating Ndarrays
  • Experiment with code examples to reinforce your learning
Attend NumPy conferences and meetups
Expand your knowledge and network by participating in NumPy-related events.
Browse courses on NumPy
Show steps
  • Identify upcoming NumPy conferences or meetups in your area or online
  • Attend sessions led by industry experts and researchers
  • Network with other attendees to exchange ideas and learn about their experiences
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve NumPy coding challenges
Challenge yourself with coding exercises to refine your skills in creating, manipulating, and analyzing Ndarrays.
Browse courses on NumPy
Show steps
  • Identify online coding platforms or repositories with NumPy challenges
  • Attempt to solve challenges independently
  • Review solutions and discuss approaches with peers or mentors
Seek guidance from NumPy experts
Enhance your learning journey by seeking mentorship from experienced NumPy users or developers.
Browse courses on NumPy
Show steps
  • Identify potential mentors through online platforms or professional networks
  • Reach out to mentors and express your interest in guidance
  • Schedule regular meetings to discuss your progress and receive feedback
Create a NumPy project
Apply your NumPy skills by developing a project that showcases your ability to solve a real-world problem or create a tool.
Browse courses on NumPy
Show steps
  • Identify a problem or need that can be addressed with NumPy
  • Design and implement a solution using NumPy functions and arrays
  • Test and refine your project to ensure accuracy and efficiency
  • Present your project to peers or mentors for feedback and evaluation
Contribute to NumPy community
Reinforce your understanding of NumPy by actively participating in the open-source community.
Browse courses on NumPy
Show steps
  • Review NumPy's GitHub repository to identify areas for contribution
  • Submit bug reports or feature requests to improve the library
  • Collaborate on code improvements or documentation updates

Career center

Learners who complete Getting Started with NumPy will develop knowledge and skills that may be useful to these careers:
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. NumPy is essential for Quantitative Analysts because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Quantitative Analyst.
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models. NumPy is essential for Machine Learning Engineers because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Machine Learning Engineer.
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. NumPy is essential for data analysis because it provides tools for manipulating and processing large datasets. This course will help you build a strong foundation in NumPy, which will be essential for success as a Data Analyst.
Data Scientist
Data Scientists use data to build models and make predictions. NumPy is an essential tool for Data Scientists because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Data Scientist.
Financial Analyst
Financial Analysts use financial data to make investment decisions. NumPy is essential for Financial Analysts because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Financial Analyst.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. NumPy is essential for Operations Research Analysts because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as an Operations Research Analyst.
Statistician
Statisticians collect, analyze, and interpret data. NumPy is essential for Statisticians because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Statistician.
Software Engineer
Software Engineers design, develop, and maintain software systems. NumPy is essential for Software Engineers because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Software Engineer.
Data Engineer
Data Engineers design, build, and maintain data pipelines. NumPy is essential for Data Engineers because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Data Engineer.
Actuary
Actuaries use mathematical and statistical models to assess risk. NumPy is essential for Actuaries because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as an Actuary.
Data Visualization Specialist
Data Visualization Specialists create visual representations of data. NumPy is essential for Data Visualization Specialists because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Data Visualization Specialist.
Business Analyst
Business Analysts use data to help businesses make informed decisions. NumPy is essential for Business Analysts because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Business Analyst.
Data Journalist
Data Journalists use data to tell stories and inform the public. NumPy is essential for Data Journalists because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Data Journalist.
Consultant
Consultants provide advice and guidance to businesses on a variety of topics. NumPy is essential for Consultants because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Consultant.
Market Researcher
Market Researchers collect and analyze data about consumer behavior. NumPy is essential for Market Researchers because it provides tools for working with large datasets and performing complex calculations. This course will help you build a strong foundation in NumPy, which will be essential for success as a Market Researcher.

Reading list

We've selected 13 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 Getting Started with NumPy.
Provides a comprehensive overview of NumPy, covering the basics of array handling, indexing, and operations, as well as more advanced topics such as broadcasting and linear algebra. It valuable resource for anyone who wants to learn more about NumPy and its applications in data science.
Covers a wide range of topics in data science, including NumPy, pandas, and scikit-learn. It great resource for anyone who wants to learn more about the Python data science ecosystem.
Provides a comprehensive introduction to data analysis with pandas, including coverage of data cleaning, manipulation, and visualization.
Provides a practical introduction to data science for business professionals, including coverage of data collection, analysis, and visualization.
Provides a comprehensive introduction to machine learning with Python, including coverage of supervised and unsupervised learning, model selection, and evaluation.
Provides a comprehensive introduction to deep learning with Python, including coverage of neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive introduction to machine learning with Python, including coverage of supervised and unsupervised learning, model selection, and evaluation.
Provides a comprehensive introduction to deep learning, including coverage of neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive introduction to machine learning with Python, including coverage of supervised and unsupervised learning, model selection, and evaluation.
Provides a comprehensive introduction to data mining, including coverage of data preprocessing, feature selection, and model evaluation.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Getting Started with NumPy.
Python Data Analysis: NumPy & Pandas Masterclass
Most relevant
Programming Numerical Methods in Python
Most relevant
Python for Excel: Use xlwings for Data Science and Finance
Complete Machine Learning & Reinforcement learning 2023
Python for Time Series Data Analysis
Working with Multidimensional Data Using NumPy
Geospatial Analysis With Python (Vector Data)
Analyzing Data with Python
Python for Data Science Project
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser