The Best Data Wrangling Online Courses

Banner Image The Best Data Wrangling Online Courses

Has the overwhelming world of data got you feeling like you’re drowning in oceans of numbers, charts, and SQL databases? Fear not, my inquisitive friend! Welcome to a safe haven where we’ll sail through the wild waves of data wrangling, and come out on the other side with the skills to make sense of the sea of information out there. Data wrangling may seem like a daunting task, but it doesn’t have to be, especially when you have the right resources at your fingertips – and that’s where online courses come in.

In this blog post, we’ve curated a list of the best data wrangling online courses that’ll help you become the data-savvy hero the world needs. From beginner to advanced levels, we’ve got you covered. So grab your virtual life jacket and let’s dive into the world of data wrangling! Your journey to becoming an exceptional data wrangler starts right here, right now. Let’s explore together.

Data Wrangling Courses – Table of Contents

  1. Complete Data Wrangling & Data Visualisation With Python
  2. Data Analysis Bootcamp™ 21 Real World Case Studies
  3. Data Visualization & Data Wrangling Masterclass with Python
  4. The Data Science Course: Complete Data Science Bootcamp
  5. Data Wrangling with Python
  6. Data Wrangling in Pandas for Machine Learning Engineers
  7. PySpark Essentials for Data Scientists (Big Data + Python)
  8. Data science with R: tidyverse

Disclosure: This post contains affiliate links, meaning at no additional cost for you, we may earn a commission if you click the link and purchase.

Complete Data Wrangling & Data Visualisation With Python

Course Preview Complete Data Wrangling & Data Visualisation With Python


4.3 out of 5

Minerva Singh, a graduate of both Oxford and Cambridge Universities with a background in Tropical Ecology, Conservation, and Geography, has created an online course designed to make data wrangling and visualization accessible for beginners. Minerva has years of experience in statistical modeling and publication in international peer-reviewed journals. This course aims to help you master statistical data analysis, focusing on practical data science and offering tons of applicable information.

Throughout the course, you’ll learn important Python data wrangling and visualization packages such as Seaborn, and gain knowledge on various data visualization concepts. You’ll be guided with real-life examples, like analyzing Olympic and Nobel Prize winners’ data, ensuring you can apply your newfound skills to practical scenarios. The course comes with Minerva’s continuous support, assignments, and practical quizzes to help reinforce your learning process. And if you’re not satisfied, there’s a 30-day money-back guarantee. Make sure to take advantage of this opportunity and enhance your data wrangling and visualization skills with this comprehensive course.

Skills you’ll learn in this course:

  1. Perform basic data wrangling tasks in Python.
  2. Utilize important Python data wrangling and visualization packages, such as seaborn.
  3. Apply data visualization concepts for practical data analysis and interpretation.
  4. Determine the best wrangling and visualization techniques for specific research questions and data types.
  5. Interpret results from data visualizations.
  6. Implement techniques on real-life data, such as Olympic and Nobel Prize winners.
  7. Reinforce learning through practical quizzes and assignments.
  8. Receive continuous support and guidance from the instructor.

Data Analysis Bootcamp™ 21 Real World Case Studies

Course Preview Data Analysis Bootcamp™ 21 Real World Case Studies


4.3 out of 5

Looking for a way to become invaluable in your career? Look no further! This online course will teach you all about data analytics, a skill that’s becoming increasingly important in the current job market. Throughout the course, you’ll learn how to use data, analytics, statistics, probability, and basic data science to give yourself an edge in both your career and daily life. Get ready to dive into real-world data sets and modern-day tools like Python, Google Colab, and Google Data Studio to gain valuable insights and make data-based predictions.

The comprehensive learning path includes topics such as data manipulation, probability, statistics, data visualization, machine learning, and practical case studies, among others. Additionally, you’ll get hands-on experience by working on Python, Pandas, and Google Data Studio projects that cover a wide range of industries and applications. By the end of this course, you’ll be able to create amazing dashboards, tell stories with data and visualizations, and make informed predictions based on your newfound data analytics skills. So, why not seize this opportunity to become a fully-fledged Data Analyst and make your career shine?

Skills you’ll learn in this course:

  1. Data manipulation and wrangling with Pandas
  2. Probability and statistics application
  3. Hypothesis testing
  4. Data visualization techniques
  5. Geospatial data visualization
  6. Storytelling with data
  7. Basic machine learning – supervised and unsupervised
  8. Practical analytical case studies

Data Visualization & Data Wrangling Masterclass with Python

Course Preview Data Visualization & Data Wrangling Masterclass with Python


3.7 out of 5

Welcome to the comprehensive online course on Data Visualization! This course not only offers advanced knowledge on Data Visualization, but also starts with a complete guide on Python programming language. As a student, you’ll master all essential concepts of Python needed for this field, such as variables, data types, loops, conditionals, strings, and regular expressions. You will also become skilled at using libraries like Numpy and Pandas, and get a solid foundation in query analysis. This will make you an expert in analyzing data using cutting-edge libraries like Dabl and Sweetviz.

But wait, there’s more! This one-stop course covers various aspects of data visualization, including basic, advanced (faceted grids, polar charts, waffle charts, maps, and statistical charts), and animated visualizations (bubble plots, facets, scatter maps, and choropleth maps). You’ll also gain expertise on miscellaneous charts like sunburst charts, parallel-coordinate charts, and Gantt charts. On top of all this, you’ll have access to three bonus projects – Startup Case Study and Analysis, Player Performance Reviewer, and IPL Data Science Analyzer! Expect lots of quizzes and exercises along the way, with access to all resources used throughout the course. Plus, quick instructor support will be available if you have any questions. Enroll now and become an expert in data visualizations!

Skills you’ll learn in this course:

  1. Python programming fundamentals
  2. Advanced knowledge of Numpy and Pandas libraries
  3. Query analysis techniques
  4. Basic data visualization concepts
  5. Advanced data visualization techniques (facet grids, polar charts, etc.)
  6. Animated data visualization methods
  7. Application of data visualization in real-life projects
  8. Efficient use of data visualization tools (Dabl and Sweetviz)

The Data Science Course: Complete Data Science Bootcamp

Course Preview The Data Science Course: Complete Data Science Bootcamp


4.6 out of 5

Introducing “The Data Science Course 2023,” a comprehensive online training program designed to address the challenges of entering the data science field. This program ensures that students acquire the necessary skills in the right order, taking you from an absolute beginner to a qualified data scientist at a fraction of the cost and time of traditional programs. The Data Science Course 2023 covers a broad range of topics, including data science fundamentals, mathematics, statistics, Python programming, data visualization with Tableau, advanced statistics, machine learning with TensorFlow, and deep learning.

The course is structured to flow smoothly and complement previous topics, starting with an introduction to data and data science, progressing through essential mathematics and statistics concepts, Python programming, Tableau visualization, advanced statistical techniques, and ultimately machine learning and deep learning. Not only will you gain the practical knowledge needed to become a data scientist, but you’ll also develop a strong foundation in thinking like a scientist with a focus on problem-solving and hypothesis testing. So why wait? Click the “Buy Now” button and begin your journey to becoming a data scientist from scratch today.

Skills you’ll learn in this course:

  1. Comprehensive understanding of data science concepts and methods
  2. Proficiency in mathematics, particularly calculus and linear algebra
  3. Strong foundation in statistics and hypothesis testing
  4. Python programming skills for data manipulation and analysis
  5. Data visualization using Tableau for effective storytelling
  6. Mastery of advanced statistics for predictive modeling
  7. Practical knowledge of machine learning techniques
  8. Deep learning methods implementation with TensorFlow

Data Wrangling with Python

Course Preview Data Wrangling with Python


4.1 out of 5

Data Wrangling with Python is a course designed to teach you the fundamentals of data cleaning and manipulation using Python. Throughout the course, you’ll gain knowledge of popular tools and techniques in the domain, starting with the basics of Python and its data structures. As you progress, you’ll delve into essential data wrangling libraries like NumPy and Pandas while learning to avoid traditional data cleaning methods used in other languages. The course guides you on how to extract and transform data from various sources such as the Internet, large databases, and Excel financial tables, as well as how to handle missing or incorrect data.

The course’s real-world examples and datasets ensure you grasp key concepts effectively. By the end of the course, you’ll be proficient in extracting, cleaning, transforming, and formatting data from diverse sources. The course’s authors include Samik Sen, a Ph.D. holder in Theoretical Physics with experience in high-performance computing; Dr. Tirthajyoti Sarkar, a senior principal engineer applying data science and machine learning techniques in the semiconductor industry; and Shubhadeep Roychowdhury, a senior software engineer at a Paris-based cybersecurity startup specializing in computer vision and data engineering algorithms.

Skills you’ll learn in this course:

  1. Understanding Python’s data structures.
  2. Utilizing NumPy and Pandas libraries for data wrangling.
  3. Extracting and transforming data from various sources.
  4. Efficiently cleaning data and avoiding traditional methods.
  5. Handling missing or incorrect data.
  6. Formatting data for downstream analytics tools.
  7. Grasping concepts through real-world examples and datasets.
  8. Applying data science techniques in various industries such as finance, sports, and online education.

Data Wrangling in Pandas for Machine Learning Engineers

Course Preview Data Wrangling in Pandas for Machine Learning Engineers


4.2 out of 5

Looking for a course that’ll help you become a machine learning engineer? You might want to check out “Data Wrangling in Pandas for Machine Learning Engineers.” It’s the second course in a series designed to teach important skills for aspiring machine learning engineers, starting with Pandas, one of the most essential Python libraries for data wrangling.

This course is perfect for those who want to learn the art of cleansing and transforming data for machine learning purposes. It offers a complete guide to Pandas, from A-Z, through an interactive, lab-based approach. Alongside this, the course will prepare you for real-world interview questions, making sure you’re ready to show off your data wrangling skills. Just remember, it’s better to take the courses in this series in order; otherwise, you might struggle to keep up with the knowledge that’s expected from you. So, go ahead and dive into the world of data wrangling and get a leg up in your machine learning career!

Skills you’ll learn in this course:

  1. A complete understanding of data wrangling vernacular.
  2. Mastering Pandas library from A-Z.
  3. The ability to completely cleanse a tabular data set in Pandas.
  4. Hands-on experience with lab integrated sessions.
  5. Understanding real-world interview questions.
  6. Efficiently modifying all of the values in a given column.
  7. Merging multiple columns together.
  8. Transforming data programmatically into a format that makes it easier to work with.

PySpark Essentials for Data Scientists (Big Data + Python)

Course Preview PySpark Essentials for Data Scientists (Big Data + Python)


4.5 out of 5

If you’re a data scientist (or aspiring to be one) looking for practical training in PySpark, this course is definitely for you! With over 100 lectures, hundreds of example problems, quizzes, and more than 100,000 lines of code, you’ll gain valuable insights into the world of Python for Apache Spark. Designed by an experienced data scientist who has consulted for clients like the IRS, US Department of Labor, and United States Veterans Affairs, this course promises to teach you the essentials of PySpark and make you an expert by the end.

Structured for real-world application, the course is filled with code-along activities, problem sets, and real consulting projects using authentic datasets. Along with concept review lectures and custom functions, you’ll also explore MLlib API and MLflow, making the process of building machine learning models a breeze! Furthermore, you’ll receive condensed review notebooks and handouts for future reference. So, get ready to dive deep into the world of PySpark and excel in your field with practical knowledge and skills. See you in the lectures!

Skills you’ll learn in this course:

  1. Gain practical knowledge in PySpark for real-world data analysis.
  2. Learn to read, manipulate, and analyze real-world datasets.
  3. Master the essentials of PySpark for data scientists.
  4. Explore custom functions and MLlib API for building machine learning models.
  5. Discover the use of MLflow for model management and tracking.
  6. Engage in hands-on coding activities and structured problem sets.
  7. Apply learned concepts to real-world consulting projects.
  8. Access condensed review materials for easy reference in the future.

Data science with R: tidyverse

Course Preview Data science with R: tidyverse


4.7 out of 5

Are you seeking a comprehensive online course to enhance your data science skills using R and tidyverse? Look no further! This course has got you covered on applied statistics and data-related tasks, providing a strong foundation in R and its collection of libraries called tidyverse. As one of the most in-demand programming languages for data science and exploration, R paired with tidyverse offers a deadly combination guaranteed to help you finish projects faster and more efficiently.

Course content includes over 25 hours of lecture videos, R scripts and additional data, assignments at the end of each chapter, and assignments walkthrough videos. Topics range from tidy data, data wrangling, importing and parsing data, dealing with strings and categorical variables, data visualization with ggplot2, functional programming with purrr, and a final practical data science project. Enroll today and become a master of R’s tidyverse, all while learning at your own pace through Udemy’s comprehensive and easy-to-understand course material. Happy learning!

Skills you’ll learn in this course:

  1. Tidy data cleaning with tidyverse
  2. Data wrangling using dplyr and tidyr
  3. Importing and parsing data with readr
  4. String manipulation using stringr and Regular Expressions
  5. Handling categorical variables with forcats
  6. Data visualization with ggplot2
  7. Functional programming and map functions using purrr
  8. Managing relational data and understanding tidy evaluation

In conclusion, data wrangling online courses have become an essential resource for individuals who are eager to break new grounds in their careers or simply striving to deepen their understanding of data manipulation and preprocessing. There’s no denying the power of knowing how to clean, organize, and analyze data effectively in today’s data-driven world. Thankfully, there’s a plethora of online courses available to suit a variety of needs, preferences, and budgets.

As you decide on the perfect data wrangling course for you, keep your specific learning goals, time commitment, and budget in mind. Furthermore, don’t be afraid to reach out to instructors or fellow learners to gain a deeper understanding of the course content and get the most out of your experience. Remember, the more you invest in your learning journey, the more rewarding the outcome will be. So go ahead, and take the plunge – your data-savvy future self will thank you.