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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

    • É

      École Polytechnique Fédérale de Lausanne

      Digital Signal Processing 4: Applications

      Skills you'll gain: Digital Communications, Image Analysis, Electrical Engineering, Electrical and Computer Engineering, Embedded Systems, Computer Engineering, Linear Algebra, Python Programming, Real Time Data, Applied Mathematics, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      79 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      Generative AI and LLMs: Architecture and Data Preparation

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Natural Language Processing, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Deep Learning, Jupyter, Data Processing, Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      151 reviews

      Intermediate · Course · 1 - 4 Weeks

    • E

      Edureka

      Learn Generative AI with LLMs

      Skills you'll gain: Generative AI, ChatGPT, Natural Language Processing, Computer Vision, Deep Learning, Predictive Modeling, Text Mining, Data Ethics, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Tensorflow, OpenAI, Supervised Learning, Artificial Neural Networks, Software Development Tools, GitHub, Artificial Intelligence, Python Programming, Information Privacy

      3.7
      Rating, 3.7 out of 5 stars
      ·
      34 reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Data-Oriented Python Programming and Debugging

      Skills you'll gain: Debugging, NumPy, Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Pandas (Python Package), Data Structures, Probability & Statistics, Probability, Probability Distribution, Statistical Analysis, Data Analysis, Program Development, Scientific Visualization, Code Review, Data Manipulation, Programming Principles, Computer Programming, Jupyter, Python Programming

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Prediction Models with Sports Data

      Skills you'll gain: Forecasting, Predictive Analytics, Predictive Modeling, Data Analysis, Analytics, Regression Analysis, Statistical Analysis, Business Ethics, Python Programming, Probability & Statistics, Data Ethics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      38 reviews

      Intermediate · Course · 1 - 3 Months

    • D

      Duke University

      Cloud Computing Foundations

      Skills you'll gain: Technical Communication, Cloud Infrastructure, CI/CD, Cloud Computing, Agile Software Development, Technical Documentation, Infrastructure As A Service (IaaS), Continuous Delivery, Infrastructure as Code (IaC), Serverless Computing, Software Development, Amazon Web Services, Google Cloud Platform, Platform As A Service (PaaS), GitHub

      4.5
      Rating, 4.5 out of 5 stars
      ·
      267 reviews

      Beginner · Course · 1 - 3 Months

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      U

      University of Minnesota

      Engineering Practices for Building Quality Software

      Skills you'll gain: Software Design Patterns, Software Engineering, Application Security, Object Oriented Design, Software Architecture, Software Quality (SQA/SQC), Threat Modeling, Maintainability, Code Review, Quality Assurance, Continuous Integration, CI/CD, Software Technical Review, Test Driven Development (TDD), Software Development Tools, Software Documentation, Version Control

      4.5
      Rating, 4.5 out of 5 stars
      ·
      417 reviews

      Intermediate · Course · 1 - 3 Months

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      C

      Coursera Project Network

      Practical Data Wrangling with Pandas

      Skills you'll gain: Exploratory Data Analysis, Data Wrangling, Pandas (Python Package), Data Visualization, Descriptive Statistics, Data Manipulation, Data Transformation, Data Analysis, Statistics

      Beginner · Guided Project · Less Than 2 Hours

    • Placeholder
      L

      LearnQuest

      Machine Learning for Supply Chains

      Skills you'll gain: Image Analysis, Exploratory Data Analysis, Time Series Analysis and Forecasting, Data Wrangling, Operations Research, NumPy, Data Manipulation, Feature Engineering, Supervised Learning, Inventory Management System, Supply Chain, Applied Machine Learning, Trend Analysis, Data Visualization, Customer Demand Planning, Demand Planning, Matplotlib, Regression Analysis, Predictive Modeling, Anomaly Detection

      3.6
      Rating, 3.6 out of 5 stars
      ·
      74 reviews

      Intermediate · Specialization · 3 - 6 Months

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      U

      Universidad Austral

      Manejo de bases de datos con Python

      Skills you'll gain: Relational Databases, Object-Relational Mapping, Database Management, Database Design, SQL, Databases, Query Languages, Data Integrity, Data Manipulation, Data Migration, Transaction Processing

      4.3
      Rating, 4.3 out of 5 stars
      ·
      179 reviews

      Beginner · Course · 1 - 4 Weeks

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      L

      LearnQuest

      Test-Driven Development Overview

      Skills you'll gain: Test Driven Development (TDD), Unit Testing, Code Review, Acceptance Testing, Integration Testing, Debugging, Software Development, Python Programming, Agile Methodology

      4.3
      Rating, 4.3 out of 5 stars
      ·
      59 reviews

      Intermediate · Course · 1 - 4 Weeks

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      Status: Free
      Free
      T

      The University of Chicago

      Global Warming II: Create Your Own Models in Python

      Skills you'll gain: Mathematical Modeling, Environmental Issue, NumPy, Physical Science, Jupyter, Time Series Analysis and Forecasting, Simulations, Numerical Analysis, Environment, Interactive Data Visualization

      4.1
      Rating, 4.1 out of 5 stars
      ·
      53 reviews

      Mixed · Course · 1 - 3 Months

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

    • Digital Signal Processing 4: Applications: École Polytechnique Fédérale de Lausanne
    • Generative AI and LLMs: Architecture and Data Preparation: IBM
    • Learn Generative AI with LLMs: Edureka
    • Data-Oriented Python Programming and Debugging: University of Michigan
    • Prediction Models with Sports Data: University of Michigan
    • Cloud Computing Foundations: Duke University
    • Engineering Practices for Building Quality Software: University of Minnesota
    • Practical Data Wrangling with Pandas: Coursera Project Network
    • Machine Learning for Supply Chains: LearnQuest
    • Manejo de bases de datos con Python: Universidad Austral

    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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