Best DataCamp Courses 2024

15 Best DataCamp Courses and SkillTracks – Become a Data Scientist.

DataCamp is an excellent and popular online learning platform to build your skills and future in data science. DataCamp offers courses in data science, Python, SQL, R programming, big data, machine learning, deep learning, and applied finance.

In this round-up of the best DataCamp courses, we will look at the most important learning outcomes and structure of popular classes and skill tracks or learning paths. What is the best class for your career prospects and goals? Let’s find out.

*Disclaimer: This post contains affiliate links. Read the full disclosure at the end of this post.

DataCamp Courses – Overview

The need for data scientists is increasing worldwide, and it will keep on growing. The mission of DataCamp is to democratize data skills for everyone. It’s the place to begin your journey in the field and learn more on the go. 

DataCamp offers two learning structures, skill tracks and individual courses. Each skill track includes multiple DataCamp courses and covers the subject in detail, whereas a course is focused on a specific topic. A beginner can start with a course for an introduction and then move on to the respective skill track for more in-depth knowledge. 

Learning – The learning process consists of interactive courses with tests to assess the learner’s progress. Students can also practice with daily challenges and apply their knowledge to create real-world projects. There is also DataCamp Community, which offers in-depth tutorials, cheat sheets, podcasts, and free DataCamp courses in DataScience.

Pricing – You can access the first chapter of all DataCamp courses for free. To access the full course catalog, challenges and live coding environments, you can sign up for the Standard plan for $25/month/annually. For $33/month/annually, Premium additionally offers 80+ real-world projects, Tableau, Power BI, and Oracle content, and priority support.

Best DataCamp Courses 2024 – Top Picks

Python DataCamp Courses	R DataCamp Courses	SQL DataCamp Courses	All DataCamp Courses
Grow Python skills	Grow R skills	Grow SQL skills	All Courses, Tracks
Visit Website	Visit Website	Visit Website	Visit Website

Note: This is a curated list of some of the best DataCamp courses online. We do not aim to cover all classes available. Please visit the website for the full catalog.

DataCamp Courses – Individual Classes

1. Introduction to Python

Python is one of the most popular programming languages for data science. The DataCamp Python course (visit website) is an excellent place to learn its principles as a beginner and create a versatile foundation for various career and skill tracks in technology.

It starts with a chapter on Python Basics like creating a Python script, variables, and data types. The second chapter covers lists, the most popular data structure in Python. Students learn to store, access, and manipulate data in lists. 

How to use functions, packages, and methods to structure and reduce Python code are essential follow-ups to complete the basics. Of course, learning how to import and use popular data science packages in Python such as NumPy will be covered too.

After the course, you can continue with skill tracks to learn more about the subject. This course is a part of Data Science for Everyone, Machine Learning for Everyone, Data Scientist, and Python Fundamentals. The latter builds upon the introduction module. Overall, this is one of the best DataCamp courses to get started on the platform.

Instructor: Hugo Bowne-Anderson | Duration: 4 hours | Videos: 11 | Exercises: 57
Pricing: Standard Plan for $25/month. Premium: $35/month
Info: Visit website. Get a discount on all plans. Free trial.

2. Introduction to R

DataCamp’s introduction to R (visit website) discusses various concepts in the open-source language R. Data Science relies heavily on statistical methods, and R is the ideal tool for implementing statistical operations and visualizing results.

There are six chapters. It starts with an introduction to R basics like assigning variables and using the console as a calculator. The second and third chapters discuss vectors and matrices in R. The fourth chapter discusses the importance of factors in data analysis. In the last two, students learn to work with data structures such as data frames and lists.

If you’re considering a career in data science, then R is an excellent language to master. It’s also part of data analysis, data science, and the DataCamp R programming skill tracks.

Instructor: Jonathan Cornelissen | Duration: 4 hours | Videos: 0 | Exercises: 62
Pricing: Standard Plan for $25/month. Premium: $35/month
Info: Visit website. Get a discount on all plans. Free trial.

3. Data Science for Everyone

When a data science course jumps right into coding, it’s natural to be alarmed. If that happened to you, then Data Science for Everyone (visit website) is a great choice. This DataCamp course introduces DS to an absolute beginner, with no coding involved.

The course begins with an introduction to data science. This covers the workflow in data science, how data science is implemented in real-world problems and various roles in the data science field. It will also talk about data collection and storage.

The following modules cover the preparation, exploration, and visualization of data. It’s the most important part of data analysis and most data scientists spend 80% of the time cleaning and manipulating data, while only 20% of time analyzing it.

This is one of the best DataCamp courses to get started with DataScience. It includes a chapter on experimentation and prediction and covers A/B testing and series forecasting.

Instructor: Sara Billen | Duration: 4 hours | Videos: 15 | Exercises: 48
Pricing: Standard Plan for $25/month. Premium: $35/month
Info: Visit website. Get a discount on all plans. Free trial.

4. Introduction to SQL

If you’re considering a career as a DBA (database administrator) or data scientist, then SQL is the basic requirement. The structured query language (SQL) is used to communicate with the database. This Datacamp SQL course (visit website) will push you in the right direction.

You will start on how to start working with a relational database. That includes database structure, lingo, and beginning data analysis with simple commands like Select.

The second chapter talks about filtering rows using comparison operators and matching patterns in text. Aggregate functions to summarize data for insights are discussed in the next chapter and arithmetics and aliases in SQL. This DataCamp course concludes with a chapter on sorting and grouping results in an RDB.

Instructor: Nick Carchedi | Duration: 4 hours | Videos: 1 | Exercises: 41
Pricing: Standard $25/month. Premium $35/month
Info: Visit website. Get a discount on all plans. Free trial.

5. Data Engineering for Everyone

Data scientists are pretty common, but data engineers are not! This DataCamp course (visit website) explores the difference between a data scientist and a data engineer and builds a foundation to begin your data engineer journey.

The course is pretty short and consists of only three chapters covered within two hours. The first chapter gives an introduction to data engineering and introduces learners to their first data pipeline. The second chapter explores data storage and how data engineers manage data lakes and data warehouses.

The last lesson is about data movements and processing. It explains various techniques used by data engineers and an introduction to parallel computing and cloud computing.

Instructor: Hadrien Lacroix | Duration: 2 hours | Videos: 11 | Exercises: 32
Pricing: Standard $25/month. Premium $35/month
Info: Visit website. Get a discount and free trial.

6. Data Science for Business

Data science is important for every organization, but the question is how and for what. This is one of a couple of Datacamp courses that explore that question and teach you how to use data science for business (visit website).

At first, there is a brief introduction to data science which proceeds to data collection and storage in the following lessons. Building upon this, you will learn about the analysis and visualization of data through dashboards, A/B testing, and Ad hoc data requests.

The last module covers machine learning, the buzziest topic in data science. It covers supervised and unsupervised learning and clustering and concludes a chapter with topics like time series prediction, NLP, deep learning, and explainable AI.

Instructor: Mari Nazary | Duration: 4 hours | Videos: 14 | Exercises: 51
Pricing: Standard $25/month. Premium $35/month
Info: Visit website. Get a discount and free trial.

7. Introduction to Tidyverse

Introduction to Tidyverse (visit website) is one of the best DataCamp courses for anyone who has a basic understanding of R. Tidyverse is a powerful collection of data science tools within R. This class is also part of selected skill and career tracks.

Start the course by exploring data-wrangling including filtering a table for a particular observation, arrange observations in a particular order, add, change, or mutate a column.

This will prepare students to then gain essential data visualization skills using ggplot2 packages. Grouping and summarizing data is covered in another lesson as well as various visualization types including line plots, bar plots, histograms, and boxplots. 

For data scientists working with R, this is one of the best DataCamp courses to get familiar with Tidyverse and provides an excellent overview of R packages for data science.

Instructor: David Robinson | Duration: 4 hours | Videos: 16 | Exercises: 50
Pricing: Standard Plan for $25/month. Premium: $35/month
Info: Visit website. Get a discount on all plans. Free trial.

8. Data Analysis in Excel

Microsoft Excel is a very powerful tool that we use every day and fail to leverage its full potential. This course (visit website) digs deeper into the MS Excel world and teaches 35 new Excel functions including AVERAGE(S), VLOOKUPS, and CONCATENATIVE.

The short course consists of three chapters. The first one explains the data analysis process, a framework to transform raw data into valuable information. In the second chapter, students learn how to clean data using a variety of functions.

The last lesson is all about analyzing data. It introduces an assortment of functions to analyze data and draw a conclusion based on it. Excel knowledge is great for data scientists and others.

Instructor: Jen Bricker | Duration: 4 hours | Videos: 12 | Exercises: 48
Pricing: Standard $25/month/annually. Premium $35/month/annually
Info: Visit website. Get a discount and free trial.

Tip: Wanna dive deeper into specific topics? Here are our curated lists of data science courses, business analytics courses, Python courses, and R courses.

DataCamp Skilltracks

9. R Programming

The DataCamp R programming skill track (visit website) covers beginner to advanced topics on the subject. It includes four parts of 4 and 6 hours, taught by various instructors. Each part consists of multiple lessons covering different topics.

The first course is an introduction to R, where students learn the basics of data analysis. It explains data structures like vectors, matrices, and frames. The next module expands to topics like loops, conditional statements, and vector functions in R.

Once you have completed the essential DataCamp courses, it’s time to focus on writing efficient R code, benchmarking, and profiling. You will also learn the principles of parallel programming in R, which is part of the fourth course along with parallel computing tools.

Info: Visit website. Get a discount on all plans. Free trial.
Duration: 18 hours | DataCamp Courses: 4 | Skills: R Language
Pricing: Standard Plan – $25/month/annually. Premium – $35/month/annually

10. Data Visualization with R

Data is invaluable, but only if you accurately analyze and visualize it. This learning path teaches the skills required to communicate insights drawn from data to non-technical stakeholders. The DataCamp Data Visualization with R (visit website) skill track consists of three 4-hour long courses, each taught by a new instructor.

The first two sections focus on data visualization with ggplot2 and discuss the aesthetics, geometrics, facets, coordinates, and statistics in ggplot2. Visualization best practices in R will complete your skillset. Learn how to best convey your data analytics with an overview of charts, alternative visualization types, and perception-driven style enhancements.

Info: Visit website. Get a discount on all plans. Free trial.
Duration: 12 hours | DataCamp Courses: 3 | Skills: R Language
Pricing: Standard Plan – $25/month/annually. Premium $35/month/annually

11. Data Visualisation with Python

If you’re familiar with Python, then Data Visualization in Python (visit website) might be the more suitable option, and it is a great way to enhance your existing skills. The skill track consists of five DataCamp courses, and you should bring Python basics to start this class.

This path teaches data visualization with three different libraries including Matplotlib, Bokeh, and Seaborn. Each library is introduced and taught in a separate course. Students learn how to create, customize, and share data visualization using a specific library.

There’s also a course on improving data visualization skills in Python. It elaborates on how to construct visualizations to effectively communicate results. The skill track concludes with a DataCamp course on how to visualize geospatial data in Python.

Info: Visit website. Get a discount on all plans. Free trial.
Duration: 20 hours | DataCamp Courses: 5 | Skills: Python
Pricing: Standard $25/month/annually. Premium $35/month/annually

12. Finance Fundamentals in R

Finance Fundamentals in R (visit website) explore how to make data-driven financial decisions. It’s longer than other skill tracks and consists of six courses. The first course teaches data structures in R and how to apply that knowledge to financial examples. Dates are discussed in the second chapter along with if statements, loops, and functions.

Xts and Zoo packages are introduced in the third course where students learn to manipulate ordered observations. The next module explains how to get financial data from local files and internet sources. 

The last two DataCamp courses are more advanced as they explore portfolio analysis in R. Students learn to apply their financial knowledge and R skills to backtest, analyze, and optimize financial portfolios.

Info: Visit website. Get a discount on all plans. Free trial.
Duration: 28 hours | DataCamp Courses: 5 | Skills: R
Pricing: Standard $25/month/annually. Premium $35/month/annually

13. Big Data with R

In the Big Data with R skill track (visit website), students will learn how to handle big data, parallel programming, interfacing with Spark, and data visualization. It includes 5 DataCamp courses that can be taken separately too.

The track begins with a course on writing efficient R code along with parallel programming, benchmarking, and profiling. Big data visualization packages like ggplot2 and trelliscopejs are introduced in the second chapter. Data processing packages like bigmemory and iotools are discussed in chapter three.

Apache begins in the fourth chapter, and students learn how to analyze large datasets with Spark and R using sparklyr. Parallel programming is the last concept discussed in the track. It covers parallel programming in depth and details the R tools used here.

Info: Visit website. Get a discount on all plans. Free trial.
Instructors: Colin Gillespie, Ryan Hafen, Michael Kane, Simon Urbanek
Duration: 20 hours | DataCamp Courses: 5 | Pricing: from $25/month/annually

14. Machine Learning Fundamentals with Python

Machine Learning Fundamentals with Python (visit website) is a great place to begin your ML journey. The skill track is about 20 hours long and consists of five online DataCamp courses. To begin, you must have a  background in Python and its libraries. 

The path begins with two DataCamp courses on supervised learning with Scikit-learn, and then unsupervised learning with Scikit-learn, and Scipy. Students learn about building and tuning predictive models and evaluating them. Instructors also discuss clustering, transformation, visualization, and extracting insights from unlabeled data. These topics are followed up by linear classifiers in Python.

A case study is covered in the fourth chapter where students build a model to automatically classify items in a school budget. Last but not least, this popular DataCamp skill track concludes with an introduction to deep learning in Python with Keras 2.0.

Info: Visit website. Get a discount on all plans. Free trial.
Instructors: Hugo Bowne-Anderson, Benjamin Wilson, Mike Gelbart, Peter Bull
Duration: 20 hours | DataCamp Courses: 5 | Pricing: from $25/month/annually

15. Deep Learning in Python

Deep learning is a subfield of ML (machine learning) that’s rapidly gaining popularity. It’s an AI function that imitates the human brain’s functioning to process data and find patterns to help decision-making. This DataCamp skill track (visit website) covers essential DL concepts and various platforms to create deep learning models.

Starting smoothly, the track first provides an overview of Deep Learning in Python and how to build deep learning models with Keras 2.0. Leveling up, you will learn about neural networks and build deep learning models using Tensorflow. In the third module, explore the PyTorch library to create deep learning models.

The last two online DataCamp courses focus more on Keras. It starts with creating models in Keras and moving on to building multiple-input and multiple-output models.

Info: Visit website. Get a discount on all plans. Free trial.
Instructors: Dan Becker, Isaiah Hull, Ismail Elezi, Miguel Esteban
Time: 20 hours | Courses: 5 | Pricing: from $25/month/annually

DataCamp alternatives: If you look for suitable DataCamp alternatives to learn programming or data analysis here is a list of the best Udacity nanodegrees. Alternatively, you may take a look into Pluralsight courses or Coursera courses.

DataCamp Courses – Pros and Cons

For beginners, DataCamp is a great place. They provide short video tutorials, coding examples, and tests that can help new coders grasp programming concepts. 

The DataCamp Python and R courses have a great reputation. The DataCamp courses about data science are not only for people pursuing a career in this field but also for managers and executives. It’s a diverse platform focused on building data skills. 

You can access all DataCamp courses with the subscription and receive a statement of accomplishment after completing a skill track. DataCamp also offers discounts on a yearly subscription, which comes in handy when you’re pursuing a career in data science.

Keep in mind that DataCamp but also other online learning platforms require taking action and researching solutions for problems. DataCamp offers additional tutorials to learn about each skill in more detail. However, their classes do not cover everything in detail, and their exercises require a student’s full attention as a lot of new knowledge can be gained here.

Best DataCamp Courses 2024 – Verdict 

Here it is, our round-up of the best DataCamp courses online in 2024. DataCamp is a great place to learn data skills whether you are new or advanced in data science. You can begin and try out any class for free and then continue the learning process with a monthly or yearly subscription starting from $25/month.

If you know what you want to do and need access to projects, assessments and challenges over a longer period of time, an annual subscription for the Standard or Premium plan is the more efficient and economical choice.

Overall, DataCamp is suitable and recommended for data science students who wish to land a job in technology but also for freelancers and entrepreneurs who wish to gain skills for their endeavors. To test DataCamp, remember you can always access the first class or module of all DataCamp courses for free.

The learning process is interactive and helpful. It includes video tutorials, exercises, case studies, and projects. Students can choose a course, begin learning and move on to more advanced topics. Keep in mind, that while everything is being done to facilitate your learning experience, you need to invest extra time to do research, reading and practicing.

What are the best DataCamp courses and SkillTracks? Let us know your learning experience below.

Resources: Python – 1 | Numpy – 2 | R-Programming – Wikipedia | Explainable AI – Wikipedia | TidyVerse – 5 | Matplotlib – 6 | Bokeh – 7 | Seaborn – 8 | Xts – 9 | Zoo –10 | Spark – 11 | PyTorch – 12

Disclosure: This site contains affiliate links to some providers of online DataCamp courses. courselounge may receive a commission for purchases made through these links. It does not add any extra costs. All reviews, opinions, descriptions and comparisons expressed here are our own.