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Getting Started with NumPy
Amruta Mahajan
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.
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.
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/zak89b/getting
What's inside
Syllabus
Course Overview
Introduction to NumPy
Setting up a Work Environment for NumPy
Understanding the Ndarray Object
Read more
Syllabus
Course Overview
Introduction to NumPy
Setting up a Work Environment for NumPy
Understanding the Ndarray Object
Read more
Creating Ndarrays
Good to know
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
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Activities
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Getting Started with NumPy.
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Career center
Learners who complete Getting Started with NumPy will develop knowledge and skills
that may be useful to these careers:
Quantitative Analyst
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 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 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 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 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 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
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 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 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
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 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 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 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
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 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.
For more career information including salaries, visit:
OpenCourser.com/course/zak89b/getting
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 statistical learning, including coverage of linear regression, logistic regression, and support vector machines.
Provides a comprehensive introduction to machine learning with Python, including coverage of supervised and unsupervised learning, model selection, and evaluation.
Save
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 machine learning with Python, including coverage of supervised and unsupervised learning, model selection, and evaluation.
Provides a comprehensive introduction to machine learning with R, including coverage of supervised and unsupervised learning, model selection, and evaluation.
Save
Provides a comprehensive introduction to data mining, including coverage of data preprocessing, feature selection, and model evaluation.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/zak89b/getting
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Time
54 hours
Level
Introductory
Via
Pluralsight
Instructor
Amruta Mahajan
Language
English
Good to know
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
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