15 Best Data Science Courses Datacamp You Need to Know in 2025

Are you looking for Best Data Science Courses at DataCamp?… If yes, then this article is for you. DataCamp is an online learning platform specially dedicated to data science.

It is based on self-paced learning and has interactive courses, projects, and practice assignments in various programming languages such as Python, R, Sheets, SQL, and Shell.

 DataCamp is best for beginners and Intermediate Data Science learners. Because DataCamp has 344 interactive courses, 51 skill tracks, 14 career tracks, projects, and practice assignments.

I have collected and listed 15 Best Data Science Courses Datacamp in this article. Now, without any further ado, let’s see these 15 Best Data Science Courses at Datacamp-

Best Data Science Courses Datacamp

1. Data Science for Everyone

Time to Complete- 4 hours

Type- Course

This is a beginner-friendly course, where you will learn about the basics of data science like Introduction to Data Science, data science workflow, Data preparation, and experimentation and prediction. If you are a beginner, then this is the best course to begin your data science journey.

There are total 4 chapters in this course-

1. Introduction to Data Science
2. Data Collection and Storage
3. Preparation, Exploration, and Visualization
4. Experimentation and Prediction

Who Should Enroll?

• Beginner in data science.

Interested to Enroll?

If yes, then check out the course details here- Data Science for Everyone.

2. Data Scientist with Python

Time to Complete- 88 hours

Type- Career Track

This is a career track with 29 courses. If you are looking for a course that will provide all data science information in one place, then this the best pick for you. This career track begins with Python Programming. You will learn Python from scratch.

After learning Python, you will learn Data Manipulation with pandas, data visualization with matplotlib and Seaborn, statistical thinking in Python, machine learning, and much more. Throughout these courses, you will work on real-world problems.

Who Should Enroll?

• Those who are a complete beginner in data science, and looking for step by step career track for data science.

Interested to Enroll?

If yes, then check out the details here- Data Scientist with Python

3. Data Scientist with R

Time to Complete- 88 hours

Type- Career Track

This is a Career Track offered by Datacamp. In this career track, there are 22 courses. At the beginning of this career track, you will learn R programming basic and advanced concepts such as factors, lists, and data frames, etc. Then you will learn tidyverse, a powerful and popular collection of data science tools within R.

You will also learn Data Manipulation and Data joining with dplyr, data visualization using ggplot2, how to import data in R, Data cleaning in R, exploratory analysis in R, Statistics and Regression in R, etc.

Who Should Enroll?

• Those who are a beginner and want to learn data science with R from scratch.

Interested to Enroll?

If yes, then check out the details here- Data Scientist with R

4. Statistician with R

Time to Complete- 108 hours

Type- Career Track

This is a Career Track offered by Datacamp. In this career track, there are 27 courses. This career track will help you to gain essential skills to land a job as a statistician. In this career track, you will learn basic to advanced level concepts of statistics.

At the beginning of the career track, you will learn how to collect, analyze, and draw accurate conclusions from data, concepts of random variables, distributions, and conditioning, using the example of coin flips, how to fit simple linear and logistic regressions, how to fit model binomial data with logistic regression and count data with Poisson regression, etc.

Then you will learn Sampling, Hypothesis testing, basic experimental design, A/B testing, how to deal with missing data, survey design, survival analysis, Bayesian data analysis, Factor Analysis, and much more.

Who Should Enroll?

• Those who have previous knowledge in R programming.

Interested to Enroll?

If yes, then check out all details here- Statistician with R

5. Linear Algebra for Data Science in R

Time to Complete- 4 hours

Type- Course

In this course, you will learn Linear Algebra basics such as vectors and matrices, eigenvalue and eigenvector analyses, etc. You will also learn how to perform dimension reduction on real-world datasets by using principal component analysis.

This course uses the R programming language for performing all analyses. There are 4 chapters in this course-

1. Introduction to Linear Algebra
2. Matrix-Vector Equations
3. Eigenvalues and Eigenvectors
4. Principal Component Analysis

Who Should Enroll?

• Those who know the R programming language.

Interested to Enroll?

If yes, then check out the course details here- Linear Algebra for Data Science in R

6. Data Visualization with Python

Time to Complete- 20 hours

Type- Skill Track

This is a skill track offered by DataCamp. In this skill track, there are 5 courses. These courses will teach you data visualization with Python and its most popular libraries Matplotlib, Seaborn, Bokeh, etc.

In the first course, you will learn how to visualize data using Matplotlib in plots and figures exposes the underlying patterns in the data and provides insights. 

The second course provides an introduction to Seaborn and teaches you how to visualize your data using plots such as scatter plots, box plots, and bar plots.

In the third course, you will learn how to construct compelling and attractive visualizations that help you communicate the results of your analyses efficiently and effectively. 

The fourth course teaches Bokeh, an interactive data visualization library for Python. In the last course, you will learn how to make attractive visualizations of geospatial data with the GeoPandas package.

Who Should Enroll?

• Those who have some prior knowledge in Python and want to learn Data Visualization with Python.

Interested to Enroll?

If yes, then check out the course details here- Data Visualization with Python

7. Interactive Data Visualization in R

Time to Complete- 20 hours

Type- Skill Track

This is another skill track offered by Datacamp. In this skill track, there are 5 courses. These courses will teach you how to create Interactive Data Visualization in R.

In the first course, you will learn how to create maps using the IPEDS dataset, which contains data on U.S. colleges and universities.

The second course teaches how to create and customize interactive graphics in plotly using the R programming language. You will also review data visualization best practices.

In the third course, you will extend your understanding of plotly to create animated and linked interactive graphics, which will enable you to communicate multivariate stories quickly and effectively.

The fourth course teaches how to visualize big data in R using ggplot2 and trelliscopejs. In the last course, you will learn rbokeh: a visualization library for interactive web-based plots. 

Who Should Enroll?

• Those who have some prior knowledge in R and want to learn Data Visualization with R programming.

Interested to Enroll?

If yes, then check out the course details here- Interactive Data Visualization in R

8. Data Analyst with Python

Time to Complete- 62 hours

Type- Career Track

In this career track, there are 16 courses in a step-by-step manner, where you will learn how to import, clean, manipulate, and visualize data.

The best part of this career track is that you will get hands-on with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, and many more.

You will also work with real-world datasets, including data from the Titanic and Twitter’s streaming API.

Who Should Enroll?

• Those who are complete beginners and want to learn data analytics with Python.

Interested to Enroll?

If yes, then check out the course details here- Data Analyst with Python

9. Machine Learning for Everyone

Time to Complete- 4 hours

Type- Course

This Datacamp course is best for you if you are an absolute beginner in machine learning. In this course, you will learn all the basics of machine learning such as What is machine learning, machine learning models, and how does machine learning work.

There are 3 chapters in this course-

1. What is Machine Learning?
2. Machine Learning Models
3. Deep Learning

Who Should Enroll?

• Those who are absolute beginners in machine learning.

Interested to Enroll?

If yes, then check out the course details here- Machine Learning for Everyone

10. Introduction to Deep Learning with PyTorch

Time to Complete- 4 hours

Type– Course

This course will teach how you can use PyTorch to learn deep learning basics, then you will build your first neural network to predict digits from the MNIST dataset. After this, you will learn about convolutional neural networks. This course will also teach you how to use CNN to build more powerful models that give more accurate results. 

The first chapter of this course is free so that you can check the quality and content of the course. There are total 4 chapters in this course-

1. Introduction to PyTorch (FREE)
2. Artificial Neural Networks
3. Convolutional Neural Networks (CNNs)
4. Using Convolutional Neural Networks

Who Should Enroll?

• Those who know Python programming and familiar with supervised learning.

Interested to Enroll?

If yes, then check out the course details here- Introduction to Deep Learning with PyTorch

11. SQL Fundamentals

Time to Complete- 21 hours

Type- Skill Track

In this skill track, you will learn about relational databases, their structure, how to begin an analysis using simple SQL commands to select and summarize columns from database tables, how to use basic comparison operators, combine multiple criteria, match patterns in text.

You will also learn how to use aggregate functions to summarize data and gain useful insights and how to sort and group your results. In this skill track, you will learn intermediate SQL such as several key functions necessary to wrangle, filter, and categorize information in a relational database.

You will get to know how to create queries for analytics and data engineering with window functions by using flight data. You will also get an understanding of how to use built-in PostgreSQL functions in your SQL queries to manipulate different types of data including strings, characters, numeric, and date/time. 

Who Should Enroll?

• Those who want to enhance their SQL skills for data science.

Interested to Enroll?

If yes, then check out the course details here- SQL Fundamentals

12. Tableau Fundamentals

Time to Complete- 22 hours

Type– Skill Track

This is a skill track offered by Datacamp. In this skill track, you will learn how to use Tableau. And through hands-on exercises, you’ll learn how to organize and analyze data, create presentation-ready visualizations, build insightful dashboards, and apply analytics to worksheets.

After completing this skill track, you will be prepared to pass Tableau’s Desktop Specialist certification. There is a total of 4 courses in this Tableau skill track. Now let’s see the details of the courses-

Courses Details-

1. Introduction to Tableau
2. Analyzing Data in Tableau
3. Creating Dashboards in Tableau
4. Connecting Data in Tableau

Who Should Enroll?

• Those who are beginners and want to learn the fundamentals of Tableau.

Interested to Enroll?

If yes, then check out all details here- Tableau Fundamentals

13. Data Engineer with Python

Time to Complete- 95 hours

Type- Career Track

In this career track, you will learn how to build an effective data architecture, streamline data processing, and maintain large-scale data systems. 

Along with Python, you will also work with Shell, SQL, and Scala, to create data engineering pipelines, automate common file system tasks, and build a high-performance database.

In this career track, there is a total of 25 courses and after completing all courses, you will have mastered the critical database, scripting, and process skills you need to progress your career.

Who Should Enroll?

• Those who have some previous fundamental knowledge of Python and SQL.

Interested to Enroll?

If yes, then check out the course details here- Data Engineer with Python

14. Importing & Cleaning Data with Python

Time to Complete- 17 hours

Type- Skill Track

This skill track is all about importing and data cleaning with Python. In this skill track, you will learn the many ways to import data into Python: from flat files, from files native to other software, from relational databases, from the web, and Application Programming Interfaces.

Then you will learn how to identify, diagnose, and treat a variety of data cleaning problems in Python, ranging from simple to advanced. After that, you will learn how to build pipelines to import data kept in common storage formats.

At the end of this skill track, you will learn to navigate and parse Html code and build tools to crawl websites automatically. There are 5 courses on this skill track-

1. Introduction to Importing Data in Python
2. Intermediate Importing Data in Python
3. Cleaning Data in Python
4. Streamlined Data Ingestion with pandas
5. Web Scraping in Python

Who Should Enroll?

• Those who have intermediate-level Python knowledge.

Interested to Enroll?

If yes, then check out the course details here- Importing & Cleaning Data with Python

15. Data Manipulation with Python

Time to Complete- 16 hours

Type- Skill Track

In this skill track, you will learn everything about data manipulation with Python. There are 4 courses on this skill track. In the first course, you will learn how to manipulate DataFrames, as you extract, filter, and transform real-world datasets for analysis.

Then you will learn how to join data with pandas. You will also work with datasets from the World Bank and the City Of Chicago. After learning pandas fundamentals, you will apply that knowledge by answering interesting questions about a real Stanford Open Policing Project dataset.

At the end of this skill track, you will learn the basics of relational databases using SQL with Python.

Courses Details-

1. Data Manipulation with pandas
2. Joining Data with pandas
3. Analyzing Police Activity with pandas
4. Introduction to Databases in Python

Who Should Enroll?

• Those who have intermediate-level Python knowledge.

Interested to Enroll?

If yes, then check out all details here- Data Manipulation with Python

And here the list ends. I hope these 15 Best Data Science Courses Datacamp will help you to learn data science concepts. I would suggest you bookmark this article for future referrals. Now it’s time to wrap up.

Conclusion

In this article, I tried to cover the 15 Best Data Science Courses Datacamp. If you have any doubts or questions, feel free to ask me in the comment section.

And if you know of any Best Data Science Courses at DataCamp, let me know in the comment section.

All the Best!

Enjoy Learning!

Thank YOU!

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Though of the Day…

‘ It’s what you learn after you know it all that counts.’

– John Wooden