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    • Matplotlib

    Matplotlib Courses Online

    Explore Matplotlib for data visualization in Python. Learn to create a variety of plots and charts to represent data effectively.

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    Explore the Matplotlib Course Catalog

    • Status: Free
      Free
      C

      Coursera Project Network

      Choisir la Meilleure Méthode pour Illustrer les Données

      Skills you'll gain: Datamaps, Interactive Data Visualization, Heat Maps, Data Visualization Software, Statistical Visualization, Data Storytelling, Data Presentation, Data Wrangling, Data Access, Correlation Analysis, Scatter Plots, Exploratory Data Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      10 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      C

      Codio

      Data Science and Analysis Tools - from Jupyter to R Markdown

      Skills you'll gain: Rmarkdown, Plot (Graphics), Box Plots, Descriptive Statistics, Scatter Plots, Histogram, Jupyter, Matplotlib, Data Presentation, Ggplot2, Statistical Visualization, Statistical Hypothesis Testing, Correlation Analysis, Data Visualization Software, Dashboard, Tidyverse (R Package), Data Analysis, Interactive Data Visualization, Data Import/Export, Data Visualization

      3.9
      Rating, 3.9 out of 5 stars
      ·
      22 reviews

      Beginner · Specialization · 3 - 6 Months

    • C

      Coursera Project Network

      Auto Machine Learning (AutoML) Using AutoGluon

      Skills you'll gain: Applied Machine Learning, Machine Learning, MLOps (Machine Learning Operations), Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Amazon Web Services, Prototyping

      Beginner · Guided Project · Less Than 2 Hours

    • N

      Northeastern University

      Data Visualization with Python & R for Engineers

      Skills you'll gain: Data Storytelling, Statistical Visualization, Data-Driven Decision-Making, Data Visualization Software, Data Mining, Exploratory Data Analysis, Data Cleansing, Data Manipulation, Graphing, Big Data, Data Transformation, Programming Principles, Python Programming, Data Structures, Scripting

      Mixed · Course · 1 - 4 Weeks

    • N

      National Taiwan University

      用 Python 做商管程式設計(三)(Programming for Business Computing in Python (3))

      Skills you'll gain: Statistical Visualization, Matplotlib, Web Scraping, Business Logic, Machine Learning, Operational Analysis, Business Analytics, Python Programming, Programming Principles, Business Economics, User Interface (UI) Design, Computational Thinking, UI Components, Object Oriented Programming (OOP), Data Analysis

      4.9
      Rating, 4.9 out of 5 stars
      ·
      161 reviews

      Mixed · Course · 1 - 3 Months

    • Status: New
      New
      S

      Simplilearn

      Data Analytics with Python

      Skills you'll gain: Matplotlib, NumPy, Python Programming, Data Presentation, Pandas (Python Package), Data Analysis, Data Visualization Software, Scripting, Analytics, Numerical Analysis, Data Manipulation, Real Time Data, Data Processing, Programming Principles, Scripting Languages, Data Cleansing

      Beginner · Course · 1 - 4 Weeks

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

      Edureka

      Applied Data Analytics

      Skills you'll gain: Power BI, Data Analysis Expressions (DAX), Data Visualization, Exploratory Data Analysis, Matplotlib, Data Visualization Software, Web Scraping, Probability Distribution, Predictive Modeling, Seaborn, Statistical Visualization, SQL, Plotly, Interactive Data Visualization, Statistical Inference, Pandas (Python Package), Database Management, Data Analysis, Data Presentation, Databases

      3.9
      Rating, 3.9 out of 5 stars
      ·
      8 reviews

      Intermediate · Specialization · 3 - 6 Months

    • K

      Korea Advanced Institute of Science and Technology(KAIST)

      Practical Python for AI Coding 2

      Skills you'll gain: Matplotlib, Data Visualization, Tensorflow, NumPy, Pandas (Python Package), Object Oriented Programming (OOP), Seaborn, Python Programming, Keras (Neural Network Library), Artificial Intelligence, Scikit Learn (Machine Learning Library), Data Manipulation, Development Environment

      4.6
      Rating, 4.6 out of 5 stars
      ·
      25 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      L

      LearnQuest

      Demand Forecasting Using Time Series

      Skills you'll gain: Time Series Analysis and Forecasting, Demand Planning, Trend Analysis, Data Visualization, Customer Demand Planning, Regression Analysis, Matplotlib, Forecasting, Predictive Modeling, Supply Chain Management, Data Analysis, Exploratory Data Analysis, Pandas (Python Package), Statistical Modeling

      3.4
      Rating, 3.4 out of 5 stars
      ·
      35 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      AI Workflow: Data Analysis and Hypothesis Testing

      Skills you'll gain: Data Visualization, Exploratory Data Analysis, Data Presentation, Statistical Hypothesis Testing, Dashboard, Data Analysis, Data Science, Probability & Statistics, Statistical Analysis, Jupyter, Matplotlib, Data Cleansing, Pandas (Python Package), Statistical Inference, Statistics, Data Manipulation

      4.3
      Rating, 4.3 out of 5 stars
      ·
      123 reviews

      Advanced · Course · 1 - 4 Weeks

    • Status: New
      New
      C

      Coursera Project Network

      Scripting with Alteryx: Python and R for Advanced Workflows

      Skills you'll gain: Alteryx, Predictive Modeling, Scripting, R Programming, Predictive Analytics, Advanced Analytics, Trend Analysis, Exploratory Data Analysis, Applied Machine Learning, Data Manipulation, Data Analysis, Employee Retention, Data Transformation, Risk Modeling

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      D

      Databricks

      Introduction to Computational Statistics for Data Scientists

      Skills you'll gain: Bayesian Statistics, Databricks, Sampling (Statistics), Statistical Modeling, Probability, Classification And Regression Tree (CART), Jupyter, Regression Analysis, Statistical Programming, Predictive Modeling, Statistical Analysis, Statistical Machine Learning, Probability Distribution, Data Science, Markov Model, Statistics, NumPy, Simulations, Mathematical Software, Statistical Inference

      4
      Rating, 4 out of 5 stars
      ·
      109 reviews

      Beginner · Specialization · 1 - 3 Months

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

    • Choisir la Meilleure Méthode pour Illustrer les Données: Coursera Project Network
    • Data Science and Analysis Tools - from Jupyter to R Markdown: Codio
    • Auto Machine Learning (AutoML) Using AutoGluon : Coursera Project Network
    • Data Visualization with Python & R for Engineers: Northeastern University
    • 用 Python 做商管程式設計(三)(Programming for Business Computing in Python (3)): National Taiwan University
    • Data Analytics with Python: Simplilearn
    • Applied Data Analytics: Edureka
    • Practical Python for AI Coding 2: Korea Advanced Institute of Science and Technology(KAIST)
    • Demand Forecasting Using Time Series: LearnQuest
    • AI Workflow: Data Analysis and Hypothesis Testing: IBM

    Frequently Asked Questions about Matplotlib

    Matplotlib is a data visualization program that uses Python programming language to plot 2D graphs. The graphs may be static, interactive, or animated. It's used by developers and data scientists for creating publishable documents that are easy to understand. Tasks that are associated with Matplotlib include data virtualization, NumPy, and text mining. It's a tool that can be used by data analysts to predict pricing or to incorporate customer segmentation for marketing purposes.‎

    It's important to learn Matplotlib as a way to turn your data into a chart or visual aid that makes it easy to understand the data and to make accurate statistical inferences. Seeing the information presented in a graph or charted format can make it easier to understand and use raw data, both for you as a data scientist using the program and for others with whom you want to share data. It may also help you advance your career or begin a new career in data science or data analysis.‎

    Career opportunities that arise from learning Matplotlib include developer jobs, analyst careers, science jobs, and engineer careers. Developer jobs you may be able to work toward after learning Matplotlib include software developer and Python developer. Data analysts and research analysts are among the jobs in the analysis field that use this program. Two other career areas that use Matplotlib are data science and software engineering.‎

    Taking courses on Coursera can help you learn Matplotlib by offering beginner courses that you can use to learn the foundational developer skills and how to use this open-source program. You can then move through the intermediate and advanced data science and data analysis courses to develop even more hands-on skills, such as hierarchical clustering and scalable data science, both of which may make your service more valuable to your employer.‎

    Online Matplotlib courses offer a convenient and flexible way to enhance your knowledge or learn new Matplotlib skills. Choose from a wide range of Matplotlib courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Matplotlib, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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