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    • Python Pandas

    Python Pandas Courses Online

    Learn Pandas for data manipulation in Python. Understand how to use Pandas for data cleaning, transformation, and analysis.

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    Explore the Python Pandas Course Catalog

    • I

      IBM

      Cloud Application Development Foundations

      Skills you'll gain: Node.JS, Cloud Computing Architecture, Server Side, Cloud-Native Computing, React Redux, Cloud Services, NoSQL, MongoDB, React.js, Agile Methodology, Front-End Web Development, JavaScript Frameworks, Cloud Security, Hypertext Markup Language (HTML), HTML and CSS, Cloud Infrastructure, Restful API, Web Development, Web Development Tools, Back-End Web Development

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.6K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Data Science Methodology

      Skills you'll gain: Jupyter, Data Modeling, Data Science, Application Deployment, Data-Driven Decision-Making, User Feedback, Data Mining, Data Cleansing, Business Research, Data Manipulation, Business Analysis, Data Processing, Predictive Modeling, Continuous Improvement Process

      4.6
      Rating, 4.6 out of 5 stars
      ·
      21K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      Imperial College London

      Introduction to Python for Researchers

      Skills you'll gain: Programming Principles, Microsoft Visual Studio, Computer Programming, Python Programming, Debugging, Scripting, Development Environment, Scripting Languages

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Python for Data Visualization:Matplotlib & Seaborn(Enhanced)

      Skills you'll gain: Matplotlib, Seaborn, Plot (Graphics), Scatter Plots, Histogram, Data Visualization, Data Visualization Software, Statistical Visualization

      4.6
      Rating, 4.6 out of 5 stars
      ·
      25 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • U

      University of Michigan

      Statistics with Python Using NumPy, Pandas, and SciPy

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Probability & Statistics, NumPy, Probability, Probability Distribution, Statistical Analysis, Data Analysis, Exploratory Data Analysis, Histogram, Scatter Plots, Regression Analysis, Pandas (Python Package), Linear Algebra, Python Programming

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      U

      Universidade de São Paulo

      Introdução à Ciência da Computação com Python Parte 2

      Skills you'll gain: Object Oriented Programming (OOP), Computer Programming, Python Programming, Algorithms, Data Structures, Computer Science, Computational Thinking, Maintainability, Data Storage, Performance Testing

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.5K reviews

      Beginner · Course · 1 - 3 Months

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      D

      DeepLearning.AI

      Generative AI with Large Language Models

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Artificial Intelligence, Applied Machine Learning, Scalability, Natural Language Processing, Machine Learning Methods, Application Deployment, Reinforcement Learning, User Feedback, Performance Tuning, Application Performance Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.2K reviews

      Intermediate · Course · 1 - 4 Weeks

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      G

      Google

      Go Beyond the Numbers: Translate Data into Insights

      Skills you'll gain: Exploratory Data Analysis, Data Storytelling, Data Visualization Software, Data Presentation, Data Transformation, Data Ethics, Tableau Software, Data Manipulation, Data Cleansing, Data Analysis, Data Processing, Stakeholder Communications, Matplotlib, Pandas (Python Package), Jupyter, Data Validation, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      756 reviews

      Advanced · Course · 1 - 3 Months

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      U

      University of Pennsylvania

      Computational Thinking for Problem Solving

      Skills you'll gain: Computational Thinking, Algorithms, Pseudocode, Analytical Skills, Computer Science, Python Programming, Data Structures, Computer Hardware, Computer Programming, Analysis, Computer Architecture, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 4 Weeks

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      N

      Northeastern University

      Basic Programming in Python I

      Skills you'll gain: Object Oriented Programming (OOP), Python Programming, Computer Programming, Development Environment, Scripting, Scripting Languages, Debugging, Program Development, Algorithms, Data Manipulation

      Beginner · Course · 1 - 3 Months

    • Placeholder
      I

      IBM

      IBM Applied DevOps Engineering

      Skills you'll gain: CI/CD, Open Web Application Security Project (OWASP), Istio, Continuous Integration, Agile Software Development, Application Deployment, Test Driven Development (TDD), Gherkin (Scripting Language), Kubernetes, Jenkins, DevOps, Code Coverage, OpenShift, Cloud Applications, Containerization, Agile Methodology, Behavior-Driven Development, Secure Coding, Grafana, System Monitoring

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.9K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Placeholder
      I

      IBM

      Applied Data Science Capstone

      Skills you'll gain: Plotly, Exploratory Data Analysis, Predictive Modeling, Interactive Data Visualization, Data Science, Data-Driven Decision-Making, Data Storytelling, Data Presentation, Data Analysis, Pandas (Python Package), Web Scraping, Statistical Machine Learning, Data Wrangling, Data Collection

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.2K reviews

      Intermediate · Course · 1 - 3 Months

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    In summary, here are 10 of our most popular python pandas courses

    • Cloud Application Development Foundations: IBM
    • Data Science Methodology: IBM
    • Introduction to Python for Researchers: Imperial College London
    • Python for Data Visualization:Matplotlib & Seaborn(Enhanced): Coursera Project Network
    • Statistics with Python Using NumPy, Pandas, and SciPy: University of Michigan
    • Introdução à Ciência da Computação com Python Parte 2: Universidade de São Paulo
    • Generative AI with Large Language Models: DeepLearning.AI
    • Go Beyond the Numbers: Translate Data into Insights: Google
    • Computational Thinking for Problem Solving: University of Pennsylvania
    • Basic Programming in Python I: Northeastern University

    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 Python Pandas

    Python Pandas is a software library for data analysis that is used with the open source Python programming language. By loading data sets into a Pandas DataFrame, a user can manipulate, analyze, and visualize that data for exploratory data analysis. Python Pandas is important to learn about because its flexibility, speed, and power in data processing makes it one of the most widely used Python libraries in data science.

    Pandas is built on the NumPy package, which is the numerical Python library for scientific computing, arrays, and linear algebra. As an example, if you wanted to predict an economic trend with a statistical model, Pandas could be used to import your data set, NumPy machine learning (ML) algorithms could perform the linear regression, and the data visualization library Matplotlib could be used to create your plots and charts. For unstructured data analysis, you could use NLTK (Natural Language Toolkit) to perform text mining for business intelligence applications.‎

    Python Pandas skills have many applications in the real world, as data science is increasingly applied to everything from economics and statistics to neuroscience and advertising. Data scientists are responsible for analyzing massive datasets, designing machine learning algorithms and predictive models, and helping management harness these data-driven insights to answer important business questions.

    Although they often need to be familiar with many data frameworks and programming languages, many data scientists rely on Pandas, NumPy, and other Python programming skills as a foundation for their exploratory data analysis. According to Glassdoor, the national average salary for a data scientist is $113,309 per year.‎

    Yes! Coursera offers a wide range of online courses, Specializations, and professional certificates in data science, including courses that teach the use of Python Pandas for data processing, data analytics, and data visualizations. You can take courses from top-ranked institutions like the University of Michigan as well as industry-leading organizations like IBM, so you can rest assured you’ll get a high-quality education. Coursera’s Guided Projects also allow you to build these skills by completing hands-on tutorials with expert instructors in topics like linear regression and data processing with Python, giving you another way to learn online.‎

    It's necessary to have basic computer skills including how to navigate a cloud desktop and install a computer program before starting to learn Python pandas. It's possible to start learning pandas without any prior knowledge of coding or Python, but having these skills will make learning pandas easier. It's also helpful to have good problem-solving skills, experience organizing and analyzing data, and basic math skills. Experience with statistics can also be helpful but not required. And having prior experience using Jupyter Notebook can also be helpful since you'll likely use it to store and access code as you learn Python pandas.‎

    People who enjoy working with data or coding are well suited for roles in Python pandas, as are people who are analytical thinkers. Important soft skills for someone in a role that uses Python panda include good communication skills, both written and verbal as well as with visualization software; problem-solving skills to troubleshoot technical problems or data errors and collaborate with team members to solve a project issue; and attention to detail to pick out small clues that help draw meaningful conclusions from data.‎

    Learning Python pandas is likely right for you if you plan to enter or are already in the data science field, particularly in roles that require data analysis or software development. You can approach learning pandas in one of two ways: either learning how to access the pandas library without conducting data analysis or using pandas while conducting data analysis. The former is more basic and is for you if want to learn how to clean data, do basic data preprocessing, and handle numeric and text data with pandas. The latter is for you if you are learning data analysis and want to apply real-world exploratory data analysis techniques to advance your knowledge and skills.‎

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

    When looking to enhance your workforce's skills in Python Pandas, 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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