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  • Numpy

NumPy Courses

NumPy courrses often teach array manipulation, mathematical functions, and data analysis techniques. You can build skills in performing complex calculations, handling large datasets, and optimizing performance for numerical operations. Many courses introduce tools like Jupyter Notebooks and Python libraries, showing how these skills are applied in data science, machine learning, and artificial intelligence projects.

More to explore:

Popular NumPy Courses and Certifications

  • Status: Free Trial
    Free Trial
    I

    IBM

    Python for Data Science, AI & Development

    Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, File I/O, Python Programming, Jupyter, Data Structures, Data Processing, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Scripting, Application Programming Interface (API), Automation, Data Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    43K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    NumPy and Pandas Basics for Future Data Scientists

    Skills you'll gain: Debugging, Data Analysis, Data Preprocessing, Numerical Analysis, Critical Thinking

    4
    Rating, 4 out of 5 stars
    ·
    11 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    I

    IBM

    Data Analysis with Python

    Skills you'll gain: Exploratory Data Analysis, Model Evaluation, Data Transformation, Data Analysis, Data Cleansing, Data Manipulation, Data Import/Export, Predictive Modeling, Data Preprocessing, Regression Analysis, Data Science, Statistical Analysis, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data-Driven Decision-Making, Matplotlib, Data Visualization, NumPy, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
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    20K reviews

    Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    Python for Data Analysis: Pandas & NumPy

    Skills you'll gain: Pandas (Python Package), NumPy, Data Analysis, Data Science, Python Programming, Data Structures, Exploratory Data Analysis, Data Manipulation, Computer Programming

    4.5
    Rating, 4.5 out of 5 stars
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    372 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: New
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    P

    Packt

    Intro to NumPy

    Skills you'll gain: NumPy, Scientific Visualization, Data Visualization, Jupyter, Time Series Analysis and Forecasting, Graphing, Data Structures, Python Programming, Numerical Analysis, Data Manipulation, Mathematical Software, Data Analysis

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    G

    Google

    Get Started with Python

    Skills you'll gain: Object Oriented Programming (OOP), Data Structures, Python Programming, NumPy, Pandas (Python Package), Data Analysis, Scripting, Data Manipulation, Data Visualization, Algorithms, Debugging

    4.8
    Rating, 4.8 out of 5 stars
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    1.8K reviews

    Advanced · Course · 1 - 3 Months

What brings you to Coursera today?

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Data Analysis with NumPy and Pandas

    Skills you'll gain: Pandas (Python Package), Pivot Tables And Charts, Data Manipulation, Data Import/Export, NumPy, Time Series Analysis and Forecasting, Business Reporting, Jupyter, Data Wrangling, Microsoft Excel, Data Transformation, Matplotlib, Data Analysis, Data Cleansing, Data Preprocessing, Analytics, Data Processing, Management Reporting, Business Analytics, Python Programming

    Beginner · Specialization · 1 - 3 Months

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  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    I

    IBM

    IBM Data Science

    Skills you'll gain: Exploratory Data Analysis, Dashboard, Data Visualization Software, Data Visualization, Model Evaluation, SQL, Unsupervised Learning, Plotly, Interactive Data Visualization, Peer Review, Data Transformation, Supervised Learning, Jupyter, Data Analysis, Data Cleansing, Data Manipulation, Data Literacy, Generative AI, Professional Networking, Data Import/Export

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
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    149K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Packt

    Master Python with Real-World Data & Web Projects

    Skills you'll gain: NumPy, Pandas (Python Package), Image Analysis, Data Manipulation, Matplotlib, Computer Vision, Data Analysis, Interactive Data Visualization, Python Programming, Data Visualization, JSON, Programming Principles, Scripting, Scripting Languages, Data Structures, Development Environment, Microsoft Visual Studio, Integrated Development Environments, Computer Programming, Software Installation

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    I

    IBM

    IBM Data Analyst

    Skills you'll gain: Exploratory Data Analysis, Data Storytelling, Dashboard, Data Visualization Software, Plotly, Data Visualization, Data Presentation, Interactive Data Visualization, Generative AI, Model Evaluation, SQL, Data Transformation, Data Analysis, Statistical Visualization, IBM Cognos Analytics, Excel Formulas, Professional Networking, Data Import/Export, Microsoft Excel, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    97K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    MLOps | Machine Learning Operations

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, Responsible AI, Data Manipulation, Exploratory Data Analysis, Containerization, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis

    4.2
    Rating, 4.2 out of 5 stars
    ·
    558 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Mathematics for Machine Learning

    Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Data Preprocessing, Unsupervised Learning, Feature Engineering, Machine Learning Algorithms, Jupyter, Advanced Mathematics, Statistics, Artificial Neural Networks, Algorithms, Mathematical Modeling, Python Programming, Derivatives

    4.6
    Rating, 4.6 out of 5 stars
    ·
    15K reviews

    Beginner · Specialization · 3 - 6 Months

What brings you to Coursera today?

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In summary, here are 10 of our most popular numpy courses

  • Python for Data Science, AI & Development: IBM
  • NumPy and Pandas Basics for Future Data Scientists: University of Michigan
  • Data Analysis with Python: IBM
  • Python for Data Analysis: Pandas & NumPy: Coursera
  • Intro to NumPy: Packt
  • Get Started with Python: Google
  • Data Analysis with NumPy and Pandas: EDUCBA
  • IBM Data Science: IBM
  • Master Python with Real-World Data & Web Projects: Packt
  • IBM Data Analyst: IBM

Skills you can learn in Data Analysis

Analytics (85)
Big Data (64)
Python Programming (47)
Business Analytics (40)
R Programming (37)
Statistical Analysis (36)
Sql (33)
Data Model (29)
Data Mining (27)
Exploratory Data Analysis (26)
Data Modeling (21)
Data Manipulation (20)

Frequently Asked Questions about Numpy

NumPy is a powerful library in Python that provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays. It is essential for scientific computing and data analysis, as it allows for efficient numerical computations and serves as the foundation for many other libraries, such as Pandas and Matplotlib. Understanding NumPy is crucial for anyone looking to work in data science, machine learning, or any field that requires data manipulation and analysis.‎

Proficiency in NumPy can open doors to various job opportunities, particularly in data-centric roles. Positions such as Data Analyst, Data Scientist, Machine Learning Engineer, and Research Scientist often require a solid understanding of NumPy. Additionally, roles in finance, engineering, and academia may also benefit from skills in numerical computing and data manipulation using NumPy.‎

To effectively learn NumPy, you should focus on developing a few key skills. First, a solid understanding of Python programming is essential, as NumPy is a Python library. Familiarity with basic programming concepts, such as loops, functions, and data types, will be beneficial. Additionally, knowledge of mathematical concepts, particularly linear algebra and statistics, will enhance your ability to use NumPy effectively in data analysis and scientific computing.‎

There are several excellent online courses available for learning NumPy. For beginners, the course Intro to NumPy provides a solid foundation. If you're looking to expand your skills further, consider Data Science with NumPy, Sets, and Dictionaries, which covers practical applications of NumPy in data science. Additionally, NumPy and Pandas Basics for Future Data Scientists is a great choice for those interested in combining NumPy with data manipulation techniques.‎

Yes. You can start learning NumPy on Coursera for free in two ways:

  1. Preview the first module of many NumPy courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in NumPy, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn NumPy effectively, start by familiarizing yourself with Python programming if you haven't already. Then, explore online courses that focus on NumPy, such as those mentioned earlier. Practice is key, so work on small projects or exercises that require you to use NumPy for data manipulation and analysis. Engaging with the community through forums or study groups can also provide support and enhance your learning experience.‎

Typical topics covered in NumPy courses include array creation and manipulation, mathematical operations, indexing and slicing, broadcasting, and working with multi-dimensional arrays. Advanced courses may also explore integration with other libraries like Pandas and Matplotlib, as well as applications in data analysis, statistics, and machine learning. These topics provide a comprehensive understanding of how to leverage NumPy for various data-related tasks.‎

For training and upskilling employees, courses like Data Science Foundations: NumPy, Pandas & Visualization are particularly beneficial. This course not only covers NumPy but also integrates it with other essential data science tools. Additionally, Statistics with Python Using NumPy, Pandas, and SciPy can help employees apply statistical methods using NumPy, making it a valuable resource for workforce development.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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