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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

    • C

      Coursera Project Network

      Exception Handling in Python

      Skills you'll gain: Debugging, Secure Coding, Python Programming, Programming Principles, Computer Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      68 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • U

      University of Michigan

      Programmation pour tous (mise en route de Python)

      Skills you'll gain: Programming Principles, Computer Programming, Python Programming, Software Installation, Development Environment

      4.7
      Rating, 4.7 out of 5 stars
      ·
      38 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Coursera Project Network

      Perform exploratory data analysis on retail data with Python

      Skills you'll gain: Data-Driven Decision-Making, Business Analytics, Data Analysis, Data Cleansing, Statistical Analysis, Exploratory Data Analysis, Customer Analysis, Analytical Skills, Trend Analysis, Pandas (Python Package), Python Programming, Jupyter

      4.5
      Rating, 4.5 out of 5 stars
      ·
      15 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • M

      Microsoft

      Project Development in Python

      Skills you'll gain: DevOps, Agile Methodology, Application Deployment, Docker (Software), Project Management, Continuous Integration, Technical Communication, Needs Assessment, Prometheus (Software), Business Requirements, Python Programming, Natural Language Processing, Collaboration, Communication, Professional Networking, Interviewing Skills

      Beginner · Course · 1 - 3 Months

    • D

      Duke University

      DevOps, DataOps, MLOps

      Skills you'll gain: MLOps (Machine Learning Operations), Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Containerization, Rust (Programming Language), DevOps, Cloud Development, Google Cloud Platform, Applied Machine Learning, CI/CD, Cloud Computing, Generative AI, Python Programming, Serverless Computing, Application Frameworks, GitHub

      4.1
      Rating, 4.1 out of 5 stars
      ·
      152 reviews

      Advanced · Course · 1 - 3 Months

    • U

      University of Washington

      Data Science at Scale

      Skills you'll gain: Feature Engineering, Unsupervised Learning, Data Ethics, Data Presentation, Statistical Visualization, Data Storytelling, Big Data, Relational Databases, Supervised Learning, Database Systems, Data Visualization Software, Databases, Data Science, Machine Learning Methods, Predictive Analytics, Analytics, Data Analysis, Exploratory Data Analysis, Predictive Modeling, Data Manipulation

      4.2
      Rating, 4.2 out of 5 stars
      ·
      915 reviews

      Intermediate · Specialization · 3 - 6 Months

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      I

      IBM

      Deep Learning with Keras and Tensorflow

      Skills you'll gain: Keras (Neural Network Library), Reinforcement Learning, Unsupervised Learning, Deep Learning, Tensorflow, Generative AI, Artificial Neural Networks, Artificial Intelligence, Time Series Analysis and Forecasting, Computer Vision, Natural Language Processing, Performance Tuning

      4.4
      Rating, 4.4 out of 5 stars
      ·
      919 reviews

      Intermediate · Course · 1 - 3 Months

    • Placeholder
      M

      Meta

      Django Web Framework

      Skills you'll gain: Django (Web Framework), Web Development, Web Servers, Web Applications, Data Modeling, MySQL, Application Security, Database Development, Object-Relational Mapping, Application Frameworks, Database Management, HTML and CSS, Restful API, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      573 reviews

      Beginner · Course · 1 - 3 Months

    • Placeholder
      C

      Coursera Project Network

      Support Vector Machines in Python, From Start to Finish

      Skills you'll gain: Scikit Learn (Machine Learning Library), Predictive Modeling, Tensorflow, Cloud Computing, Classification And Regression Tree (CART), Supervised Learning, Applied Machine Learning, Pandas (Python Package), Machine Learning, Data Manipulation, Data Visualization

      4.6
      Rating, 4.6 out of 5 stars
      ·
      154 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Placeholder
      U

      University of Michigan

      Sports Performance Analytics

      Skills you'll gain: Forecasting, Statistical Methods, Regression Analysis, Data Cleansing, Scikit Learn (Machine Learning Library), Supervised Learning, Statistical Hypothesis Testing, Correlation Analysis, Predictive Analytics, Predictive Modeling, Matplotlib, Applied Machine Learning, Data Visualization, Kinesiology, Injury Prevention, Data Analysis, Machine Learning Methods, Analytics, Advanced Analytics, Statistical Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      254 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Placeholder
      U

      University of Colorado Boulder

      Fundamental Tools of Data Wrangling

      Skills you'll gain: Pandas (Python Package), Data Wrangling, NumPy, Data Cleansing, Data Structures, Data Analysis, Data Manipulation, Data Synthesis, Data Transformation, Data Quality, Exploratory Data Analysis, Data Integration, Programming Principles, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      16 reviews

      Beginner · Course · 1 - 3 Months

    • Placeholder
      C

      Codio

      Python Object Basics: Functions, Recursion, and Objects

      Skills you'll gain: Object Oriented Programming (OOP), Programming Principles, Computer Programming, Scripting Languages, Python Programming, Scripting

      4.5
      Rating, 4.5 out of 5 stars
      ·
      59 reviews

      Intermediate · Course · 1 - 4 Weeks

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

    • Exception Handling in Python: Coursera Project Network
    • Programmation pour tous (mise en route de Python): University of Michigan
    • Perform exploratory data analysis on retail data with Python: Coursera Project Network
    • Project Development in Python: Microsoft
    • DevOps, DataOps, MLOps: Duke University
    • Data Science at Scale: University of Washington
    • Deep Learning with Keras and Tensorflow: IBM
    • Django Web Framework : Meta
    • Support Vector Machines in Python, From Start to Finish: Coursera Project Network
    • Sports Performance Analytics: University of Michigan

    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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