The 9 Best Data Wrangling Courses and Online Training for 2021

The Best Data Wrangling Courses and Online Training

The editors at Solutions Review have compiled this list of the best data wrangling courses and online training to consider.

Data wrangling is the process of cleaning, structuring and enriching raw data into the desired format. The practice has become increasingly important as data volumes and varieties continue to grow larger. Data wrangling typically involves six iterative steps, including data discovery, structuring, data cleaning, data enrichment, data validation, and publishing. The end-result of this time-consuming process is curated data sets that are easy to access, analyze and generate insights from.

With this in mind, we’ve compiled this list of the best data wrangling courses and online training to consider if you’re looking to grow your data management or analytics skills for work or play. This is not an exhaustive list, but one that features the best data wrangling courses and online training from trusted online platforms. We made sure to mention and link to related courses on each platform that may be worth exploring as well. Click Go to training to learn more and register.

Data Wrangling, Analysis and AB Testing with SQL

Platform: Coursera

Description: This course allows you to apply the SQL skills taught in “SQL for Data Science” to four increasingly complex and authentic data science inquiry case studies. Students will learn how to convert timestamps of all types to common formats and perform date/time calculations. You’ll also select and perform the optimal JOIN for a data science inquiry and clean data within an analysis dataset by deduping, running quality checks, backfilling, and handling nulls.

Related path/track: Process Data from Dirty to Clean

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Feature Engineering with PySpark

Platform: DataCamp

Description: The real world is messy and your job is to make sense of it. Toy datasets like MTCars and Iris are the result of careful curation and cleaning, even so, the data needs to be transformed for it to be useful for powerful machine learning algorithms to extract meaning, forecast, classify, or cluster. This course will cover the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

Related path/track: Interactive Data Visualization with rbokeh

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Machine Learning Certification Training

Platform: Edureka

Description: Edureka’s Machine Learning Certification Training using Python will help you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes, and Q-Learning. This module will also help you understand the concepts of statistics, time-series, and different classes of machine learning algorithms like supervised, unsupervised, and reinforcement algorithms.

Related path/track: Data Science Certification Course using R

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Excel for Everyone: Core Foundations

Platform: edX

Description: This introductory Excel course will equip you with a strong foundational knowledge of Excel to organize, analyze and work with data. You will develop essential Excel skills, such as simple data wrangling and managing spreadsheets, along with a foundational understanding of business data analysis.

Related paths/tracks: Excel for Everyone: Data Analysis Fundamentals, Excel for Everyone: Data Management, Data Science: R Basics, Data Analytics Basics for Everyone, Learning Analytics Fundamentals, Data Science: Wrangling

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Data Wrangling in R

Platform: Experfy

Description: This course will teach you from start to finish how to get your data into R efficiently and polish it up so that it is as good as it can be. This will let you or your team focus after this step on the statistical modeling, visualization, reporting, sharing, or any other post-processing task you wish to perform. Confidence, reliability, and reproducibility in your data acquisition and preparation are the kingpins to being able to maximize your data’s value.

Related paths/tracks: Data Pre-Processing, Data Curation for Decision Making

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Data Wrangling in R

Platform: LinkedIn Learning

Description: In this course, learn about the principles of tidy data, and discover how to create and manipulate data tibbles—transforming them from source data into tidy formats. Instructor Mike Chapple uses the R programming language and the tidyverse packages to teach the concept of data wrangling—the data cleaning and data transformation tasks that consume a substantial portion of analysts’ time.

Related path/track: R Essential Training: Wrangling and Visualizing Data

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Data Wrangling with Python

Platform: Pluralsight

Description: This course, Data Wrangling with Python, is aimed at helping you do exactly that. First, you’ll see how to merge data from different sources using the methods concat, append, and merge. Next, you’ll discover how to combine data into groups. The primary function used here is groupby. In the next two sections, you’ll explore how to transform and normalize data. You’ll learn why these processes are necessary, and then proceed to see how they work in practice.

Related paths/tracks: SQL Data Wrangling in Oracle: Table Data, Data Wrangling with Pandas for Machine Learning Engineers

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Become a Data Analyst Nanodegree

Platform: Udacity

Description: Advance your programming skills and refine your ability to work with messy, complex datasets. You’ll learn to manipulate and prepare data for analysis, and create visualizations for data exploration. Finally, you’ll learn to use your data skills to tell a story with data.

Related paths/tracks: Predictive Analytics for Business, Data Wrangling with MongoDB, Learn Spark

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Complete Data Wrangling & Data Visualisation With Python

Platform: Udemy

Description: This course enables learners to acquire the knowledge and statistical data analysis wrangling and visualization skills that are most important. The module will take you (even if you have no prior statistical modeling/analysis background) from a basic level to performing some of the most common data wrangling tasks in Python. It will also equip you to use some of the most important Python data wrangling and visualization packages such as seaborn.

Related paths/tracks: Data Wrangling in Pandas for Machine Learning Engineers, Complete Data Wrangling & Data Visualisation in R

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NOW READ: The Best Data Wrangling Books on Our Reading List

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Timothy King

Senior Editor at Solutions Review
Tim is Solutions Review's Editorial Director and leads coverage on big data, business intelligence, and data analytics. A 2017 and 2018 Most Influential Business Journalist and 2021 "Who's Who" in data management and data integration, Tim is a recognized influencer and thought leader in enterprise business software. Reach him via tking at solutionsreview dot com.
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