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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

      Scikit-Learn For Machine Learning Classification Problems

      Skills you'll gain: Scikit Learn (Machine Learning Library), Applied Machine Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Supervised Learning, Random Forest Algorithm, Unsupervised Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      15 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      I

      Infosec

      Python for Command-and-control, Exfiltration and Impact

      Skills you'll gain: Threat Modeling, Cyber Operations, Threat Detection, Cybersecurity, Incident Response, Scripting, Command-Line Interface, Python Programming, Encryption, Network Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      40 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Introduction to Machine Learning in Sports Analytics

      Skills you'll gain: Scikit Learn (Machine Learning Library), Supervised Learning, Applied Machine Learning, Statistical Machine Learning, Predictive Analytics, Feature Engineering, Classification And Regression Tree (CART), Machine Learning Algorithms, Predictive Modeling, Analytics, Machine Learning, Data Analysis, Random Forest Algorithm

      4.8
      Rating, 4.8 out of 5 stars
      ·
      24 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      Object Localization with TensorFlow

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Image Analysis, Computer Vision, Artificial Neural Networks, Applied Machine Learning, Deep Learning, Python Programming

      4.3
      Rating, 4.3 out of 5 stars
      ·
      113 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • P

      Pontificia Universidad Católica de Chile

      Python para Ciencia de Datos

      Skills you'll gain: Descriptive Analytics, Data-Driven Decision-Making, Data Analysis, Data Visualization Software, Predictive Analytics, Business Analytics, Database Management, Data Science, Relational Databases, Forecasting, Python Programming

      3.8
      Rating, 3.8 out of 5 stars
      ·
      67 reviews

      Beginner · Course · 1 - 4 Weeks

    • 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

    • Status: Free Trial
      Free Trial
      C

      Codio

      Advanced Django: Introduction to Django Rest Framework

      Skills you'll gain: Django (Web Framework), Postman API Platform, Restful API, Data Validation, Authentications, Authorization (Computing), Application Programming Interface (API), API Design, JSON, Object-Relational Mapping, Model View Controller

      4.6
      Rating, 4.6 out of 5 stars
      ·
      49 reviews

      Advanced · Course · 1 - 4 Weeks

    • U

      University of Michigan

      AI-Powered Data Analysis: A Practical Introduction

      Skills you'll gain: Analytical Skills, Data Analysis, Data Cleansing, Data Manipulation, Generative AI, ChatGPT, Data Visualization Software, Statistical Analysis, Artificial Intelligence, Data Collection, Data Management, GitHub, Technical Support, Git (Version Control System), Integrated Development Environments

      4.3
      Rating, 4.3 out of 5 stars
      ·
      13 reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Machine Learning with ChatGPT: Image Classification Model

      Skills you'll gain: ChatGPT, Keras (Neural Network Library), Applied Machine Learning, Image Analysis, Machine Learning Methods, Data Import/Export, Test Data, Performance Tuning, Artificial Neural Networks, Data Processing, Deep Learning

      4.4
      Rating, 4.4 out of 5 stars
      ·
      32 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      M2M & IoT Interface Design & Protocols for Embedded Systems

      Skills you'll gain: Internet Of Things, API Design, Amazon Web Services, Cloud Computing Architecture, Application Programming Interface (API), Network Protocols, Microservices, Cloud Services, Embedded Systems, Serverless Computing, Cloud Technologies, Cybersecurity, Software Development, Public Cloud, Node.JS

      4.6
      Rating, 4.6 out of 5 stars
      ·
      122 reviews

      Intermediate · Course · 1 - 4 Weeks

    • D

      Duke University

      Web Scraping with Python

      Skills you'll gain: Web Scraping, Extensible Markup Language (XML), Scripting, Hypertext Markup Language (HTML), Web Development, Unstructured Data, Web Applications, Python Programming

      3.2
      Rating, 3.2 out of 5 stars
      ·
      17 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • 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

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

    • Scikit-Learn For Machine Learning Classification Problems: Coursera Project Network
    • Python for Command-and-control, Exfiltration and Impact: Infosec
    • Introduction to Machine Learning in Sports Analytics: University of Michigan
    • Object Localization with TensorFlow: Coursera Project Network
    • Python para Ciencia de Datos: Pontificia Universidad Católica de Chile
    • Introduction to Computational Statistics for Data Scientists: Databricks
    • Advanced Django: Introduction to Django Rest Framework: Codio
    • AI-Powered Data Analysis: A Practical Introduction: University of Michigan
    • Machine Learning with ChatGPT: Image Classification Model: Coursera Project Network
    • M2M & IoT Interface Design & Protocols for Embedded Systems: University of Colorado Boulder

    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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