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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

    • G

      Google Cloud

      Work with Gemini Models in BigQuery - 繁體中文

      Skills you'll gain: Generative AI, Google Cloud Platform, Big Data, Customer Relationship Management, SQL, Business Modeling, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, Natural Language Processing

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Work with Gemini Models in BigQuery - 简体中文

      Skills you'll gain: Applied Machine Learning, Big Data, Business Intelligence, Generative AI, Customer Relationship Management, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), SQL, Prompt Engineering, Data Analysis, Python Programming

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Work with Gemini Models in BigQuery - 日本語版

      Skills you'll gain: Customer Relationship Management, Google Cloud Platform, Generative AI, Big Data, Predictive Modeling, Prompt Engineering, Artificial Intelligence and Machine Learning (AI/ML), SQL, Data Analysis

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      App Deployment, Debugging, and Performance - 日本語版

      Skills you'll gain: Google Cloud Platform, Cloud Applications, Infrastructure as Code (IaC), Application Deployment, Continuous Deployment, Platform As A Service (PaaS), Application Performance Management, Debugging, Development Environment, Containerization, Serverless Computing

      Intermediate · Course · 1 - 3 Months

    • P

      Pontificia Universidad Católica de Chile

      Certificado en Introducción a la Ciencia de Datos

      Skills you'll gain: Predictive Analytics, Unsupervised Learning, Data Cleansing, Exploratory Data Analysis, Data Visualization, Dimensionality Reduction, Data Science, Descriptive Analytics, Supervised Learning, Regression Analysis, Scientific Visualization, Data-Driven Decision-Making, Data Processing, Time Series Analysis and Forecasting, Pandas (Python Package), Data Visualization Software, Statistical Machine Learning, Data Manipulation, Statistical Visualization, Machine Learning

      Credit offered

      Mastertrack · 6 - 12 Months

    • U

      University of Michigan

      Master of Applied Data Science

      Skills you'll gain: Data Ethics, Data Storytelling, Database Design, Reinforcement Learning, Supervised Learning, Experimentation, Interactive Data Visualization, PySpark, Generative AI, Pandas (Python Package), Network Analysis, Deep Learning, Cloud Services, Linear Algebra, Natural Language Processing, JSON, Data Mining, Applied Machine Learning, Qualitative Research, Statistical Visualization

      Earn a degree

      Degree · 1 - 4 Years

    • U

      University of Colorado Boulder

      Data Science Graduate Certificate

      Skills you'll gain: Data Mining, Statistical Modeling, Unsupervised Learning, Supervised Learning, Deep Learning, Machine Learning Algorithms, Statistical Inference, Statistical Hypothesis Testing, Service Level, Performance Testing, Probability, Dimensionality Reduction, Applied Machine Learning, Data Warehousing, Statistical Machine Learning, Data Pipelines, Data Processing, Probability & Statistics, Bash (Scripting Language), Data Science

      Credit offered

      Graduate Certificate · 6 - 12 Months

    • I

      Imperial College London

      Master of Science in Machine Learning and Data Science

      Skills you'll gain: Data Ethics, Supervised Learning, Exploratory Data Analysis, Unsupervised Learning, Student Support and Services, PySpark, Data Pipelines, Linear Algebra, Ggplot2, Dimensionality Reduction, Student Services, Data Processing, Big Data, Agentic systems, Graphing, A/B Testing, Unstructured Data, Deep Learning, Bayesian Statistics, Applied Machine Learning

      Earn a degree

      Degree · 1 - 4 Years

    • U

      Universidad de los Andes

      Principios de ingeniería de software automatizada y ágil Certificado MasterTrack®

      Skills you'll gain: User Story, Maintainability, Test Automation, Software Testing, Version Control, Test Driven Development (TDD), Git (Version Control System), Software Architecture, Continuous Integration, Software Design, Unit Testing, Acceptance Testing, Usability, Regression Testing, Software Design Patterns, Web Content Accessibility Guidelines, Agile Software Development, Quality Assurance, Angular, Unified Modeling Language

      Credit offered

      Mastertrack · 6 - 12 Months

    • U

      University of Pittsburgh

      Master of Data Science

      Skills you'll gain:

      Earn a degree

      Degree · 1 - 4 Years

    • U

      Universidad de los Andes

      Metodologías ágiles de desarrollo de software Certificado MasterTrack®

      Skills you'll gain: Test Automation, Android Jetpack, User Story, Software Testing, Kotlin, Agile Software Development, Team Building, Security Requirements Analysis, Continuous Integration, Cloud Applications, Infrastructure As A Service (IaaS), Unit Testing, Acceptance Testing, Usability, Software Engineering, Sprint Retrospectives, Application Security, Software Architecture, Web Content Accessibility Guidelines, Platform As A Service (PaaS)

      Credit offered

      Mastertrack · 6 - 12 Months

    • U

      University of Colorado Boulder

      Master of Science in Data Science

      Skills you'll gain: User Story, Systems Engineering, Real-Time Operating Systems, New Product Development, Field-Programmable Gate Array (FPGA), Failure Analysis, Delegation Skills, Object Oriented Design, Sampling (Statistics), Supplier Management, Sustainability Reporting, Accountability, Data Ethics, Data Mining, Statistical Modeling, Unsupervised Learning, Proposal Writing, Generative AI, Process Capability, Diversity Equity and Inclusion Initiatives

      Earn a degree

      Degree · 1 - 4 Years

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

    • Work with Gemini Models in BigQuery - 繁體中文: Google Cloud
    • Work with Gemini Models in BigQuery - 简体中文: Google Cloud
    • Work with Gemini Models in BigQuery - 日本語版: Google Cloud
    • App Deployment, Debugging, and Performance - 日本語版: Google Cloud
    • Certificado en Introducción a la Ciencia de Datos: Pontificia Universidad Católica de Chile
    • Master of Applied Data Science: University of Michigan
    • Data Science Graduate Certificate: University of Colorado Boulder
    • Master of Science in Machine Learning and Data Science: Imperial College London
    • Principios de ingeniería de software automatizada y ágil Certificado MasterTrack®: Universidad de los Andes
    • Master of Data Science: University of Pittsburgh

    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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