The 10 best Data Cleaning & Wrangling courses in 2026

This is the fourth course in the Google Data Analytics Certificate. In this course, you’ll continue to build your understanding of data analytics and the concepts and tools that data analysts use in their work. You’ll learn how to check and clean your data using spreadsheets and SQL, as well as how to verify and report your data cleaning results. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources. Learners who complete this certificate program will be equipped to apply for introduc

Tired of spending hours on tedious data cleaning? Imagine if AI could handle the heavy lifting for you, turning days of work into minutes. From detecting errors to organizing vast datasets, Generative AI can not only save you time but also elevate your data quality to new heights. Dive into this course to learn how to transform data prep from a chore into a game-changing advantage! This short course was created to help you leverage Generative AI to simplify data cleaning and preparation, making workflows faster, more efficient, and accurate. By completing this course, you’ll gain hands-on kn

This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.

This course is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this course will introduce you to problem definition and data preparation in a machine learning project. By the end of the course, you will be able to clearly define a machine learning problem using two approaches. You will learn to survey available data resources and identify potential ML applications. You will learn to take a business need and turn it into a machine learning app

This course guides you through the process of transforming raw financial data into a clean, trustworthy dataset using Python and pandas. You’ll begin by exploring how to load data into a notebook environment and conduct quick inspections to identify structural issues, formatting inconsistencies, unusual numeric patterns, and missing values. Building on these observations, you’ll apply essential cleaning techniques used by analysts every day—fixing data types, standardizing text categories, resolving or documenting missingness, and removing duplicates. Through guided walkthroughs, hands-on prac

In Data Cleaning, Transformation, and Manipulation, you’ll learn to turn messy data into analysis- and modeling-ready datasets using Python (pandas) and SQL. This is a skill-based path organized around real workplace tasks. Each module mirrors responsibilities you see in job descriptions and focuses on the exact steps you’ll perform on the job. You’ll begin with a quick skills check, then personalize your journey: double down on new topics, or skip what you already know. For each skill, you’ll review concise lessons curated from expert instructors with explanations and demos for filtering and

Cloud Dataprep is Google's self-service data preparation tool. In this lab, you will learn how to use Cloud Dataprep to clean and enrich multiple datasets using a mock use case scenario of customer info and purchase history.

Expand your understanding of H2O's GenAI platform with the Ecosystem Overview - Level 2 course, presented by H2O's very own Sanyam Bhutani! This course provides an in-depth comprehensive exploration of the tools, applications, and methodologies tailored for artificial intelligence (AI) and machine learning (ML) within the H2O ecosystem. You will delve deeper into efficient data preparation techniques, advanced model training, deployment strategies, and real-time monitoring solutions, covering the full spectrum of all the capabilities available. Through engaging modules, you will soon master t

University of Michigan's beginner-friendly path covering Python programming, data structures, web data, and databases.

Google's job-ready data analytics path: spreadsheets, SQL, Tableau, R, and data storytelling.