Why is it important to learn data wrangling?

Data wrangling is important to learn if you want to be able to gather, select, and transform data to answer a question or solve a problem. This is essential for two reasons. First, the work of data wrangling can speed the time to develop and test models. Second, it allows for faster analysis and more accurate conclusions. Data wrangling makes data more usable in an organization. Understanding it can help your work better and make sounder decisions based on the data. Understanding it can help you with other data science courses, lead to professional certifications, or simply help you do better at your job.

What are typical careers that use data wrangling?

Careers that use data wrangling are usually in data science, data analysis, or data engineering. Data wrangling is usually part of an operational role that includes A/B testing, data visualization, model selection, and debugging. Some people who learn data wrangling go on to study advanced computer science, and others just want to understand how and why data is segmented and analyzed. Jobs in data wrangling call for the use of many different programming languages. Some organizations use SQL, others use Python, and some use pivot tables and other advanced Microsoft Excel spreadsheet functions. As more and more work will be using big data, the ability to clean and manipulate data will become more important.

What kind of people are best suited for roles in data wrangling?

People who are best suited for roles in data wrangling at the entry-level have basic computer literacy, high-school math, comfort with numbers, and willingness to learn. Cleaning and manipulating data call for a sense of logic and order, too. Many people manage data for presentations to others, so the ability to design slide decks and reports may come into play. Data wrangling is a form of communication with others in the organization who want problems solved and need the information to do it. Good data wranglers have an interest in helping others use data better. Their work in debugging and data visualization contributes to the overall organization's success.

What are the benefits of taking an online Data Wrangling course?

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

What Data Wrangling courses are best for training and upskilling employees or the workforce?

When looking to enhance your workforce's skills in Data Wrangling, 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 .

Top Data Wrangling Courses - Learn Data Wrangling Online

Explore the Data Wrangling Course Catalog

Status: Free Trial
Johns Hopkins University
Data Science: Foundations using R
Skills you'll gain: Rmarkdown, Exploratory Data Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Data Wrangling, Data Visualization, Plot (Graphics), Statistical Programming, Ggplot2, Big Data, Git (Version Control System), Data Integration, Knitr, Data Analysis, Data Sharing, Statistical Reporting
4.6
Rating, 4.6 out of 5 stars
48K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
IBM
Data Science Fundamentals with Python and SQL
Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Visualization Software, Statistics, Data Visualization, Statistical Hypothesis Testing, Web Scraping, Relational Databases, Stored Procedure, Python Programming, Data Structures, Databases, Data Science, GitHub
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
72K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
Google
Data Analysis with R Programming
Skills you'll gain: Rmarkdown, Ggplot2, R Programming, Data Visualization, Data Analysis, Tidyverse (R Package), Data Visualization Software, Statistical Programming, Data Cleansing, Data Manipulation, Programming Principles, Data Transformation, Integrated Development Environments, Data Structures
4.8
Rating, 4.8 out of 5 stars
11K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
Johns Hopkins University
Genomic Data Science
Skills you'll gain: Bioinformatics, Unix Commands, Biostatistics, Exploratory Data Analysis, Statistical Analysis, Unix, Data Science, Data Management, Statistical Methods, Molecular Biology, Command-Line Interface, Statistical Hypothesis Testing, Linux Commands, Data Analysis Software, Statistical Modeling, Data Structures, Data Analysis, R Programming, Computational Thinking, Jupyter
4.5
Rating, 4.5 out of 5 stars
6.6K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
IBM
Applied Data Science
Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Visualization, Predictive Modeling, Interactive Data Visualization, Exploratory Data Analysis, Data Wrangling, Data Analysis, Jupyter, Matplotlib, Pandas (Python Package), Seaborn, Data Presentation, Data Import/Export, Web Scraping, Python Programming, Data Structures, Data Science, Data-Driven Decision-Making
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
59K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
University of California, Davis
Learn SQL Basics for Data Science
Skills you'll gain: Data Governance, Presentations, SQL, Apache Spark, Distributed Computing, Descriptive Statistics, Data Lakes, Data Storytelling, Data Analysis, Peer Review, Exploratory Data Analysis, Data Quality, Data Pipelines, Databricks, Statistical Analysis, Database Design, Complex Problem Solving, Query Languages, Data Visualization, JSON
4.6
Rating, 4.6 out of 5 stars
17K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
IBM
IBM Generative AI Engineering
Skills you'll gain: Prompt Engineering, Large Language Modeling, Predictive Modeling, PyTorch (Machine Learning Library), Unsupervised Learning, Generative AI, Keras (Neural Network Library), Supervised Learning, Flask (Web Framework), Exploratory Data Analysis, Feature Engineering, Data Wrangling, Unit Testing, ChatGPT, Data Analysis, Jupyter, Artificial Intelligence, Deep Learning, OpenAI, Natural Language Processing
4.6
Rating, 4.6 out of 5 stars
87K reviews
Beginner · Professional Certificate · 3 - 6 Months
Status: Free Trial
Microsoft
Preparing Data for Analysis with Microsoft Excel
Skills you'll gain: Excel Formulas, Microsoft Excel, Spreadsheet Software, Power BI, Data Analysis, Productivity Software, Data Cleansing, Data Manipulation, Data Management
4.7
Rating, 4.7 out of 5 stars
4.5K reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
IBM
Python Project for Data Engineering
Skills you'll gain: Web Scraping, Data Transformation, Extract, Transform, Load, Data Manipulation, SQL, Integrated Development Environments, Data Processing, Databases, Application Programming Interface (API), Code Review, Restful API, Python Programming, Unit Testing, Style Guides
4.6
Rating, 4.6 out of 5 stars
774 reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
DeepLearning.AI
Deep Learning
Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Natural Language Processing, Artificial Neural Networks, Tensorflow, Supervised Learning, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, Debugging, Performance Tuning, Keras (Neural Network Library), Python Programming, Machine Learning Algorithms, Analysis, Data Processing
Build toward a degree
4.8
Rating, 4.8 out of 5 stars
146K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
Google
Foundations of Data Science
Skills you'll gain: Data Storytelling, Data Ethics, Data Analysis, Workflow Management, Data-Driven Decision-Making, Analytical Skills, Data Science, Project Design, Communication, Business, Business Workflow Analysis, Stakeholder Communications, Machine Learning
4.7
Rating, 4.7 out of 5 stars
3.2K reviews
Advanced · Course · 1 - 3 Months
Status: Free Trial
Google Cloud
Preparing for Google Cloud Certification: Cloud Data Engineer
Skills you'll gain: Data Pipelines, Dataflow, Google Cloud Platform, Real Time Data, Data Maintenance, Data Lakes, Data Storage, MLOps (Machine Learning Operations), Data Analysis, Dashboard, Data Warehousing, Data Processing, Extract, Transform, Load, Cloud Engineering, Data Infrastructure, Cloud Infrastructure, Cloud Storage, Big Data, Tensorflow, Unstructured Data
4.6
Rating, 4.6 out of 5 stars
19K reviews
Intermediate · Professional Certificate · 3 - 6 Months