Working with Multidimensional Data Using NumPy from Pluralsight

As working with huge numeric datasets becomes the norm, using the right tools and libraries to work with the data becomes very important. NumPy allows data analysts and data scientists to work with multi-dimensional data to solve these problems.

As machine learning and deep learning techniques become popular, getting the dataset into the right numeric form and engineering the right features to feed into ML models becomes critical.

In this course, Working with Multidimensional Data Using NumPy, you'll learn the simple and intuitive functions and classes that NumPy offers to work with data of high dimensionality.

First, you will get familiar with basic operations to explore multi-dimensional data, such as creating, printing, and performing basic mathematical operations with arrays. You'll study indexing and slicing of array data and iterating over lists and see how images are basically 3D arrays and how they can be manipulated with NumPy.

Next, you will move on to complex indexing functions. NumPy arrays can be indexed with conditional functions as well as arrays of indices. You'll then see how broadcasting rules work which allows NumPy to perform operations on arrays with different shapes as well as, study array operations such as np.argmax() which are very common when working with ML problems.

Finally, you'll study how NumPy integrates with other libraries in the PyData stack. You will also cover specific implementations with SciPy and with Pandas.

At the end of this course, you will be comfortable using the array manipulation techniques that NumPy has to offer to get your data in the right form for extracting insights.

What's inside

Syllabus

Course Overview

Exploring Multidimensional Data Using NumPy

Complex Indexing Using NumPy

Leveraging Other Python Libraries with NumPy

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Builds a strong foundation for beginners interested in exploring multidimensional data

Taught by Janani Ravi, who are recognized for their work in the field of data science

Develops essential skills for data analysts and data scientists who work with large numeric datasets

Examines NumPy's integration with other libraries in the PyData stack, providing a comprehensive understanding of the Python ecosystem for data science

Requires proficiency in Python, which may be a barrier for complete beginners

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 Working with Multidimensional Data Using NumPy with these activities:

Connect with NumPy Experts

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Reach out to experienced professionals in the field of NumPy to gain valuable insights and guidance.

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Identify potential mentors through online platforms like LinkedIn or professional organizations.
Craft a personalized message expressing your interest in learning from them.

Review of Probability and Linear Algebra

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Refresh your understanding of probability and linear algebra, as they are essential mathematical foundations for NumPy.

Browse courses on Probability

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Review basic probability concepts such as probability distributions, random variables, and Bayes' theorem.
Revisit linear algebra concepts including vectors, matrices, and linear transformations.

NumPy Basics Practice

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Reinforce your understanding of NumPy basics by engaging in hands-on practice.

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Create arrays and perform basic arithmetic operations on them.
Practice indexing and slicing arrays to extract specific elements.
Experiment with NumPy functions like np.argmax() and np.mean()

Four other activities

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NumPy Array Manipulation

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Deepen your comprehension of NumPy's array manipulation capabilities by creating a visual representation.

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Create a flowchart or mind map that illustrates the process of creating, manipulating, and visualizing NumPy arrays.
Include examples of array creation, indexing, slicing, and broadcasting.

NumPy Documentation Exploration

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Familiarize yourself with the resources available in the NumPy documentation, enhancing your ability to find information independently.

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Navigate the NumPy documentation to find information on specific functions.
Explore examples and tutorials provided in the documentation.

NumPy Workshop

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Attend a NumPy workshop to gain hands-on experience and interact with experts in the field.

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Register for a NumPy workshop led by experienced instructors.
Participate actively in the workshop, completing exercises and asking questions.

NumPy Data Analysis Project

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Apply your NumPy skills to a real-world data analysis project, showcasing your proficiency in data manipulation and analysis.

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Identify a dataset that aligns with your interests.
Use NumPy to clean, explore, and analyze the dataset.
Create visualizations to present your findings.
Write a report summarizing your analysis and insights.

Career center

Learners who complete Working with Multidimensional Data Using NumPy will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

As a Machine Learning Engineer, you will be responsible for designing, developing, and deploying machine learning systems. NumPy is an essential tool for this role, as it allows you to work with large datasets and build complex machine learning models. This course will provide you with a solid foundation in NumPy, so that you can use it to succeed in your role as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

As a Data Scientist, you will use your skills in mathematics, statistics, and programming to develop and implement machine learning models. NumPy is a fundamental library for data science, as it provides a wide range of functions for working with numerical data. This course will help you master the basics of NumPy, so that you can use it to build and deploy successful machine learning models.

See salaries and explore the career path for Data Scientist

Statistician

As a Statistician, you will use your skills in mathematics, statistics, and programming to collect, analyze, and interpret data. NumPy is a powerful tool for this role, as it allows you to work with large datasets and perform complex statistical operations. This course will help you build a foundation in NumPy, so that you can use it to succeed in your role as a Statistician.

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Quantitative Analyst

As a Quantitative Analyst, you will use your skills in mathematics, statistics, and programming to develop and implement financial models. NumPy is a powerful tool for this role, as it allows you to work with large datasets and perform complex mathematical operations. This course will help you build a foundation in NumPy, so that you can use it to succeed in your role as a Quantitative Analyst.

See salaries and explore the career path for Quantitative Analyst

Financial Modeler

As a Financial Modeler, you will use your skills in mathematics, statistics, and programming to develop and implement financial models. NumPy is a powerful tool for this role, as it allows you to work with large datasets and perform complex financial analysis tasks. This course will help you build a foundation in NumPy, so that you can use it to succeed in your role as a Financial Modeler.

See salaries and explore the career path for Financial Modeler

Quantitative Trader

As a Quantitative Trader, you will use your skills in mathematics, statistics, and programming to develop and implement trading strategies. NumPy is a powerful tool for this role, as it allows you to work with large datasets and perform complex financial analysis tasks. This course will help you build a foundation in NumPy, so that you can use it to succeed in your role as a Quantitative Trader.

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Data Engineer

As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines. NumPy is a useful tool for this role, as it can be used to work with large datasets and perform complex data transformations. This course will help you build a foundation in NumPy, so that you can use it to succeed in your role as a Data Engineer.

See salaries and explore the career path for Data Engineer

Research Scientist

As a Research Scientist, you will use your skills in mathematics, statistics, and programming to conduct research and develop new technologies. NumPy is a valuable tool for this role, as it allows you to work with large datasets and perform complex mathematical operations. This course will provide you with a solid foundation in NumPy, so that you can use it to succeed in your role as a Research Scientist.

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Data Analyst

As a Data Analyst, you will be responsible for collecting, cleaning, and analyzing large datasets to identify trends and patterns. NumPy can be a powerful tool for this role, as it allows you to work with multidimensional data efficiently. This course will help you build a foundation in NumPy, so that you can use it to solve real-world problems in data analysis.

See salaries and explore the career path for Data Analyst

Business Analyst

As a Business Analyst, you will use your skills in mathematics, statistics, and programming to analyze business data and identify opportunities for improvement. NumPy is a useful tool for this role, as it can be used to work with large datasets and perform complex data analysis tasks. This course will help you build a foundation in NumPy, so that you can use it to succeed in your role as a Business Analyst.

See salaries and explore the career path for Business Analyst

Operations Research Analyst

As an Operations Research Analyst, you will use your skills in mathematics, statistics, and programming to solve complex business problems. NumPy is a valuable tool for this role, as it can be used to work with large datasets and perform complex optimization tasks. This course will help you build a foundation in NumPy, so that you can use it to succeed in your role as an Operations Research Analyst.

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Risk Manager

As a Risk Manager, you will use your skills in mathematics, statistics, and programming to identify and assess risks. NumPy is a useful tool for this role, as it can be used to work with large datasets and perform complex risk analysis tasks. This course will help you build a foundation in NumPy, so that you can use it to succeed in your role as a Risk Manager.

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Software Engineer

As a Software Engineer, you will be responsible for designing, developing, and deploying software applications. NumPy is a useful tool for this role, as it can be used to work with large datasets and perform complex mathematical operations. This course will help you build a foundation in NumPy, so that you can use it to succeed in your role as a Software Engineer.

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Financial Analyst

As a Financial Analyst, you will use your skills in mathematics, statistics, and programming to analyze financial data and make investment recommendations. NumPy is a useful tool for this role, as it can be used to work with large datasets and perform complex financial analysis tasks. This course will help you build a foundation in NumPy, so that you can use it to succeed in your role as a Financial Analyst.

See salaries and explore the career path for Financial Analyst

Actuary

As an Actuary, you will use your skills in mathematics, statistics, and programming to assess and manage risk. NumPy is a useful tool for this role, as it can be used to work with large datasets and perform complex risk analysis tasks. This course will help you build a foundation in NumPy, so that you can use it to succeed in your role as an Actuary.

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