Last updated: 24 October 2026. Written by Josh Hutcheson, OnlineCourseing editor. Every course and track below was opened on datacamp.com on 24 October 2026 to confirm it is live and to record its level, length, learner rating and last-updated date. See our review methodology and our full DataCamp review.
Quick picks: best DataCamp courses (2026)
Best for absolute beginners: Introduction to Python: four hours, no experience needed, first chapter free.
Best for analysts: Data Analyst in Python: a 36-hour, nine-course track in the right order.
Best for aspiring data scientists: Associate Data Scientist in Python (formerly Data Scientist with Python): 90 hours across 23 courses. See our review of the track.
Best for machine learning: Machine Learning Scientist in Python: 85 hours, from scikit-learn to deep learning with PyTorch.
Best free starting point: Introduction to SQL: the most-reviewed course on DataCamp, with a free first chapter.
DataCamp is an interactive platform built only for data and AI skills: more than 800 courses across Python, R, SQL, Power BI, Tableau, statistics, machine learning and AI tools, at $14 a month billed annually ($168 a year). The hard part is not deciding whether to subscribe; it is choosing which courses to take, in which order.
Below are 25 courses for every stage, from first-day introductions to case studies that look like real analyst work, plus the career tracks worth committing to, what certification involves, what it all costs, and cheaper alternatives when DataCamp is not the right fit.
How We Picked These 25 Courses
Before you sign up for another data science course, read this.
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We started from DataCamp’s own catalog and the courses its career tracks are built from, then opened every course page on 24 October 2026. A course stayed on the list only if it was live under the name we use, rated at least 4.7, and still useful for someone building job skills. We favored courses with large numbers of reviews and recent updates, and we flag the two that have not been updated since 2024 or earlier.
We did not complete all 25 courses for this article, and we do not claim to have. What we can vouch for is what each course page shows today, cross-checked against learner reviews and the tracks DataCamp builds them into.
All 25 Courses at a Glance
| # | Course | Level | Length | Rating | Updated |
|---|---|---|---|---|---|
| 1 | Introduction to R | Beginner | 4 hours | 4.8 (2,757) | Feb 2026 |
| 2 | Introduction to Python | Beginner | 4 hours | 4.8 (10,442) | Feb 2026 |
| 3 | Introduction to SQL | Beginner | About 2 hours (30 to 60 minutes in the AI-tutor format) | 4.8 (65,803) | Oct 2026 |
| 4 | Introduction to Power BI | Beginner | 3 to 4 hours | 4.8 (23,205) | Oct 2026 |
| 5 | Understanding Data Science | Beginner | 2 hours | 4.8 (8,046) | Jul 2026 |
| 6 | Data Analysis in Google Sheets | Beginner | 3 hours | 4.8 (1,333) | Sep 2024 |
| 7 | Analyzing Data in Tableau | Beginner | 8 hours | 4.8 (1,892) | Dec 2025 |
| 8 | Data Processing in Shell | Intermediate | 4 hours | 4.8 (569) | Jul 2026 |
| 9 | Data Analysis in Excel | Beginner | 3 hours | 4.8 (5,733) | Jul 2026 |
| 10 | Introduction to Git | Beginner | 2 hours | 4.8 (13,643) | Jan 2026 |
| 11 | Introduction to Scala | Intermediate | 3 hours | 4.8 (154) | Nov 2024 |
| 12 | Introduction to Statistics in Python | Intermediate | 4 hours | 4.7 (9,143) | Jul 2026 |
| 13 | Understanding Machine Learning | Beginner | 2 hours | 4.8 (12,120) | Jun 2026 |
| 14 | Data Manipulation with pandas | Beginner | 4 to 6 hours | 4.7 (16,401) | Sep 2026 |
| 15 | Introduction to the Tidyverse | Beginner | 4 hours | 4.8 (1,299) | Jul 2026 |
| 16 | Introduction to Data Visualization with Matplotlib | Beginner | 4 hours | 4.8 (1,274) | Jun 2025 |
| 17 | Intermediate Python for Finance | Intermediate | 4 hours | 4.7 (1,073) | Jun 2022 |
| 18 | Analyzing Marketing Campaigns with pandas | Beginner | 4 hours | 4.8 (449) | Apr 2026 |
| 19 | Cleaning Data in Python | Intermediate | 4 hours | 4.7 (5,533) | Dec 2025 |
| 20 | Understanding Data Engineering | Beginner | 2 hours | 4.8 (12,623) | Apr 2026 |
| 21 | Case Study: Exploratory Data Analysis in R | Beginner | 4 hours | 4.9 (51) | Sep 2024 |
| 22 | Case Study: Analyzing Customer Churn in Power BI | Beginner | 3 hours | 4.8 (7,815) | Oct 2026 |
| 23 | Case Study: Analyzing Customer Churn in Tableau | Beginner | 3 hours | 4.8 (1,097) | Jun 2024 |
| 24 | Data-Driven Decision Making for Business | Beginner | 2 hours | 4.8 (1,075) | Nov 2024 |
| 25 | Understanding Cloud Computing | Beginner | 2 hours | 4.8 (11,634) | Jul 2026 |
Level, length, rating and update date as shown on each DataCamp course page, 24 October 2026. DataCamp labels its entry level “Basic”; we call it Beginner.
1. Introduction to R
R is the language of statisticians, epidemiologists and many academic researchers, and DataCamp’s R catalog runs from this course to full career tracks. This is where it starts.
You work through vectors, factors, lists, matrices and data frames, the building blocks every later R course assumes. It needs no prior coding, and its first chapter is free.
Best for: anyone choosing R for statistics, research or academic work. Level: Beginner · Length: 4 hours · Rating: 4.8 from 2,757 reviews · Updated: Feb 2026.
Start Introduction to R on DataCamp (first chapter free). Take next: The tidyverse, which is how most modern R is written. Related guide: Python vs R and other data science languages.
2. Introduction to Python
DataCamp designed this for people with no Python experience, and it is the first course in most of its Python tracks. It covers variables, lists, functions and packages, then introduces NumPy, so you finish ready for data work rather than general programming.
If you are unsure where to start on DataCamp, start here. Its first chapter is free.
Best for: absolute beginners who want the language with the widest data job market. Level: Beginner · Length: 4 hours · Rating: 4.8 from 10,442 reviews · Updated: Feb 2026.
Start Introduction to Python on DataCamp (first chapter free). Take next: Pandas, the library Python data jobs test most. Related guide: best Python courses.
3. Introduction to SQL
The most-reviewed course on this list: 65,803 ratings and over 1.6 million learners. It covers how relational databases are organized, then your first queries: selecting columns, filtering rows and summarizing with aggregate functions.
DataCamp now offers it in a classic format of about two hours and an AI-tutor format it lists at 30 minutes to an hour. Either way it is the fastest useful skill on the platform.
Best for: anyone who will touch a company database, which is every analyst. Level: Beginner · Length: About 2 hours (30 to 60 minutes in the AI-tutor format) · Rating: 4.8 from 65,803 reviews · Updated: Oct 2026.
Start Introduction to SQL on DataCamp (first chapter free). Take next: The seven-course SQL Fundamentals track. Related guide: best SQL courses.
4. Introduction to Power BI
A thorough first look at Power BI: loading data, building visuals with drag and drop, and designing a report people can use. It is the first course in DataCamp’s Data Analyst in Power BI track, which was co-created with Microsoft.
Power BI is the BI tool most job postings name alongside Excel, which makes this one of the best-value hours here.
Best for: business analysts and anyone heading toward Microsoft’s PL-300 exam. Level: Beginner · Length: 3 to 4 hours · Rating: 4.8 from 23,205 reviews · Updated: Oct 2026.
Start Introduction to Power BI on DataCamp (first chapter free). Take next: The Data Analyst in Power BI track for PL-300. Related guide: best Power BI courses.
5. Understanding Data Science
A non-technical course with no code at all. It explains the different data roles, the stages of a data project and where machine learning fits, through short exercises.
Take it before paying for a career track if you are not sure which track you want.
Best for: managers, career explorers and anyone deciding whether data science is for them. Level: Beginner · Length: 2 hours · Rating: 4.8 from 8,046 reviews · Updated: Jul 2026.
Start Understanding Data Science on DataCamp (first chapter free). Take next: Introduction to Python, to start doing it. Related guide: data science tools.
6. Data Analysis in Google Sheets
Formerly called Data Analysis in Spreadsheets. It covers cleaning data, summary statistics, sorting and filtering, and combining tables with VLOOKUP, in Google Sheets.
It is a good bridge for spreadsheet users before Python or SQL. Note that it has not been updated since September 2024.
Best for: people whose data lives in spreadsheets today. Level: Beginner · Length: 3 hours · Rating: 4.8 from 1,333 reviews · Updated: Sep 2024.
Start Data Analysis in Google Sheets on DataCamp (first chapter free). Take next: Data Analysis in Excel, if your company runs Microsoft. Related guide: best Google Sheets courses.
7. Analyzing Data in Tableau
Despite the Beginner label, this is a second Tableau course: maps, date and time trends, calculated fields, bins, filters, table calculations, and dynamic sets and groups, with a customer analytics case study.
DataCamp positions it as a step toward the Tableau Desktop Specialist certification. Take Introduction to Tableau first if you have never opened the tool.
Best for: Tableau users ready for the next step after the introductory course. Level: Beginner · Length: 8 hours · Rating: 4.8 from 1,892 reviews · Updated: Dec 2025.
Start Analyzing Data in Tableau on DataCamp (first chapter free). Take next: The Tableau churn case study. Related guide: best Tableau courses.
8. Data Processing in Shell
Downloading, processing and transforming data from the command line, including running Python and scheduling jobs. DataCamp lists Introduction to Shell, Intermediate Python and Intermediate SQL as prerequisites.
Not a first course, but a strong one once you are writing scripts regularly.
Best for: data scientists and engineers who want to work faster on the command line. Level: Intermediate · Length: 4 hours · Rating: 4.8 from 569 reviews · Updated: Jul 2026.
Start Data Processing in Shell on DataCamp (first chapter free). Take next: The Data Engineer in Python track. Related guide: best Bash and shell courses.
9. Data Analysis in Excel
PivotTables, intermediate logical functions for customer segmentation, What-If analysis for scenarios, and forecasting with moving averages and trendlines.
Excel remains the most common analysis tool in most companies, and this course teaches its analytical side in three hours.
Best for: Excel users who want analysis skills rather than formatting skills. Level: Beginner · Length: 3 hours · Rating: 4.8 from 5,733 reviews · Updated: Jul 2026.
Start Data Analysis in Excel on DataCamp (first chapter free). Take next: Introduction to Power BI, the next tool most Excel analysts need. Related guide: best Excel courses.
10. Introduction to Git
Version control for data projects: creating repositories, tracking files, how Git stores data in blobs, trees and commits, and undoing changes.
Many hiring managers look at GitHub when you share a portfolio. Two hours here make every later project easier to share.
Best for: anyone who writes code that others will read or that should be versioned. Level: Beginner · Length: 2 hours · Rating: 4.8 from 13,643 reviews · Updated: Jan 2026.
Start Introduction to Git on DataCamp (first chapter free). Take next: Data Processing in Shell, once you live in the terminal. Related guide: best Git courses.
11. Introduction to Scala
The basics of Scala syntax and style, learned by building a small program, with context on why companies use it for data engineering infrastructure. DataCamp lists Intermediate Python as the prerequisite.
A niche pick: valuable for Spark-heavy engineering roles, unnecessary for analysts. It was last updated in November 2024.
Best for: data engineers heading toward Spark and large-scale pipelines. Level: Intermediate · Length: 3 hours · Rating: 4.8 from 154 reviews · Updated: Nov 2024.
Start Introduction to Scala on DataCamp (first chapter free). Take next: The Data Engineer in Python track. Related guide: best Scala courses.
12. Introduction to Statistics in Python
Summary statistics, probability, distributions and correlation, with questions such as how likely a customer is to buy or how many calls a support team will receive.
Statistics is what separates an analyst from a report builder, and this is DataCamp’s cleanest entry to it.
Best for: Python learners whose next gap is statistics. Level: Intermediate · Length: 4 hours · Rating: 4.7 from 9,143 reviews · Updated: Jul 2026.
Start Introduction to Statistics in Python on DataCamp (first chapter free). Take next: The Associate Data Scientist in Python track. Related guide: best statistics courses.
13. Understanding Machine Learning
A no-code introduction to supervised and unsupervised learning, model evaluation and the limits of the technology.
Good for managers and product people; if you want to build models, take the Machine Learning Scientist in Python track below.
Best for: non-coders who need to understand what machine learning can and cannot do. Level: Beginner · Length: 2 hours · Rating: 4.8 from 12,120 reviews · Updated: Jun 2026.
Start Understanding Machine Learning on DataCamp (first chapter free). Take next: The Machine Learning Scientist in Python track. Related guide: best machine learning courses.
14. Data Manipulation with pandas
Filtering, sorting, grouping and transforming DataFrames on real datasets, including Walmart sales, then visualizing the results. It sits in almost every DataCamp Python track.
pandas is the skill Python data jobs test most, so this is the course to take second.
Best for: anyone learning Python for data, right after Introduction to Python. Level: Beginner · Length: 4 to 6 hours · Rating: 4.7 from 16,401 reviews · Updated: Sep 2026.
Start Data Manipulation with pandas on DataCamp (first chapter free). Take next: Cleaning Data in Python. Related guide: best pandas courses.
15. Introduction to the Tidyverse
Data manipulation with dplyr and visualization with ggplot2, using a historical country dataset to answer exploratory questions.
The tidyverse is how most R is written today. This is the natural second R course.
Best for: R learners after Introduction to R. Level: Beginner · Length: 4 hours · Rating: 4.8 from 1,299 reviews · Updated: Jul 2026.
Start Introduction to the Tidyverse on DataCamp (first chapter free). Take next: The UN voting case study in R. Related guide: best data analysis courses.
16. Introduction to Data Visualization with Matplotlib
Building, customizing and sharing plots with Matplotlib, the library most other Python plotting tools sit on.
Pair it with pandas: the two together cover most of what an analyst does in Python day to day.
Best for: Python learners who need to present their findings. Level: Beginner · Length: 4 hours · Rating: 4.8 from 1,274 reviews · Updated: Jun 2025.
Start Introduction to Data Visualization with Matplotlib on DataCamp (first chapter free). Take next: Introduction to Statistics in Python. Related guide: best data visualization courses.
17. Intermediate Python for Finance
Datetimes, dictionaries, control flow and DataFrames applied to financial data. DataCamp lists Introduction to Python for Finance as the prerequisite.
A caution: it was last updated in June 2022, the oldest course on this list. The Python fundamentals still hold, but check DataCamp’s newer finance track before committing to it.
Best for: finance and business analysts automating their own work. Level: Intermediate · Length: 4 hours · Rating: 4.7 from 1,073 reviews · Updated: Jun 2022.
Start Intermediate Python for Finance on DataCamp (first chapter free). Take next: Introduction to Statistics in Python. Related guide: coding for finance.
18. Analyzing Marketing Campaigns with pandas
Real business questions on a subscription-business dataset: how a campaign performed, which channel brings the most subscribers, and why a channel underperforms. DataCamp lists Intermediate Python as the prerequisite.
It is the clearest example on DataCamp of how pandas skills turn into answers a manager asked for.
Best for: marketers learning Python, and analysts heading into marketing teams. Level: Beginner · Length: 4 hours · Rating: 4.8 from 449 reviews · Updated: Apr 2026.
Start Analyzing Marketing Campaigns with pandas on DataCamp (first chapter free). Take next: Cleaning Data in Python. Related guide: data analytics project ideas.
19. Cleaning Data in Python
Diagnosing and fixing data problems: wrong data types, out-of-range values, duplicates, missing data and record linkage between two restaurant datasets using string similarity.
Cleaning is most of an analyst’s real workload, and most beginner courses skip it.
Best for: anyone about to analyze real, messy data. Level: Intermediate · Length: 4 hours · Rating: 4.7 from 5,533 reviews · Updated: Dec 2025.
Start Cleaning Data in Python on DataCamp (first chapter free). Take next: The rest of the Data Analyst in Python track. Related guide: best Coursera data analytics certifications.
20. Understanding Data Engineering
A no-code tour of what data engineers do and how data flows through a company, following a fictional streaming service as it collects, cleans and catalogs data.
Take it before the 40-hour Data Engineer in Python track to see whether the role suits you.
Best for: anyone curious about data engineering, or working alongside engineers. Level: Beginner · Length: 2 hours · Rating: 4.8 from 12,623 reviews · Updated: Apr 2026.
Start Understanding Data Engineering on DataCamp (first chapter free). Take next: The Data Engineer in Python track. Related guide: best data engineering courses.
21. Case Study: Exploratory Data Analysis in R
A start-to-finish analysis of United Nations General Assembly voting history, comparing countries, years and issues, with the broom package for tidying model output. DataCamp lists Introduction to Data Visualization with ggplot2 as the prerequisite.
The highest-rated course here (4.9), on a small number of reviews.
Best for: R learners ready to apply dplyr and ggplot2 to a real dataset. Level: Beginner · Length: 4 hours · Rating: 4.9 from 51 reviews · Updated: Sep 2024.
Start Case Study: Exploratory Data Analysis in R on DataCamp (first chapter free). Take next: The Data Scientist in R track. Related guide: best predictive analytics courses.
22. Case Study: Analyzing Customer Churn in Power BI
You analyze churn at a fictional telecom company, building DAX measures, calculated columns and report pages to explain why customers leave. Prerequisites: Introduction to DAX in Power BI and Data Visualization in Power BI.
A churn analysis is a classic interview case, which makes this one of the most practical courses on the list.
Best for: Power BI learners who want a portfolio-ready analysis. Level: Beginner · Length: 3 hours · Rating: 4.8 from 7,815 reviews · Updated: Oct 2026.
Start Case Study: Analyzing Customer Churn in Power BI on DataCamp (first chapter free). Take next: The Data Analyst certification. Related guide: best business analytics courses.
23. Case Study: Analyzing Customer Churn in Tableau
The same telecom churn dataset, built in Tableau with calculated fields, dual-axis charts, scatter plots, filters, parameters and a story. Prerequisites: Introduction to Tableau, Analyzing Data in Tableau and Creating Dashboards in Tableau.
Last updated June 2024; the Power BI version above is fresher if you can choose either tool.
Best for: Tableau learners who want the same churn case. Level: Beginner · Length: 3 hours · Rating: 4.8 from 1,097 reviews · Updated: Jun 2024.
Start Case Study: Analyzing Customer Churn in Tableau on DataCamp (first chapter free). Take next: The Data Analyst certification. Related guide: data analytics project ideas.
24. Data-Driven Decision Making for Business
A no-code course on reading data and applying a decision-making framework to business questions.
Useful for team leads who brief analysts. DataCamp lists Machine Learning for Business as a prerequisite.
Best for: managers who need data literacy, not coding. Level: Beginner · Length: 2 hours · Rating: 4.8 from 1,075 reviews · Updated: Nov 2024.
Start Data-Driven Decision Making for Business on DataCamp (first chapter free). Take next: Understanding Machine Learning. Related guide: best business analytics courses.
25. Understanding Cloud Computing
A non-coding introduction to what the cloud is, terms such as scalability and latency, and the main service models and providers.
A short primer before DataCamp’s AWS Cloud Practitioner or Azure AZ-900 certification prep.
Best for: complete novices to the cloud. Level: Beginner · Length: 2 hours · Rating: 4.8 from 11,634 reviews · Updated: Jul 2026.
Start Understanding Cloud Computing on DataCamp (first chapter free). Take next: Understanding Data Engineering. Related guide: best cloud computing courses.
Four Learning Paths Built From These Courses
If you would rather not assemble your own sequence, these paths use only the courses above and take most people one to three months at five hours a week.
- Python analyst: Introduction to Python → Data Manipulation with pandas → Cleaning Data in Python → Matplotlib → Statistics in Python → Introduction to SQL. About 25 hours.
- Business analyst on Microsoft tools: Data Analysis in Excel → Introduction to SQL → Introduction to Power BI → the Power BI churn case study (after the DAX and visualization courses it requires). About 15 hours, then the PL-300 track if you want the certification.
- R for research and statistics: Introduction to R → Introduction to the Tidyverse → ggplot2 → the UN voting case study. About 15 hours.
- Data literacy for managers (no code): Understanding Data Science → Understanding Machine Learning → Understanding Data Engineering → Understanding Cloud Computing. About 8 hours.
Hours are the sum of DataCamp’s listed course lengths; expect to spend longer if you repeat exercises, which is where most of the learning happens.
Best DataCamp Career and Skill Tracks
Single courses are good for filling one gap. If you want a job-ready set of skills, a track sequences the courses for you and ends with projects and, for career tracks, a certification option.
| Track | Length | Courses | Rating | Best for |
|---|---|---|---|---|
| Data Analyst in Python | 36 hours | 9 | 4.6 (109) | First analyst job, Python route |
| Associate Data Scientist in Python | 90 hours | 23 | 4.7 (97) | Data science foundations through machine learning |
| Machine Learning Scientist in Python | 85 hours | 21 | 4.9 (16) | Supervised, unsupervised and deep learning |
| Data Engineer in Python | 40 hours | 14 | 4.3 (52) | Pipelines, ingestion and scheduling |
| Data Analyst in Power BI | 50 hours | 17 | 4.7 (222) | PL-300 exam prep, co-created with Microsoft |
| SQL Fundamentals | 26 hours | 7 | 4.7 (115) | SQL from zero |
| Data Scientist in R | 27 hours | 9 | Not shown | R learners after Associate Data Scientist in R (88 hours, 22 courses) |
From each track page on datacamp.com, 24 October 2026.
The most common criticism of DataCamp on Reddit is that it “only teaches the basics.” Users in r/DataCamp largely agree about the introductory courses and point to the later courses in the career tracks, where the material gets harder. If depth matters to you, judge DataCamp by a track, not by its first course.
DataCamp Certifications
Certifications are separate from course completion. For the Data Analyst certification, you register and then have 30 days to pass two timed exams (two hours and two attempts each) and a practical exam. Associate-level practical exams are graded automatically; higher levels are reviewed by a person. They are included in Premium. DataCamp also offers certifications in SQL, Power BI, Tableau, AI fundamentals and AI engineering, and prep for partner exams such as Microsoft PL-300, Azure AZ-900 and AWS Cloud Practitioner.
They are a real test, not a participation badge, but they are timed rather than proctored and employers know the name less well than Google’s or Microsoft’s. Use one alongside two or three portfolio projects.
How Much DataCamp Costs
| Plan | Price (24 Oct 2026) | What you get |
|---|---|---|
| Basic | Free | First chapter of every course, professional profile, assessments |
| Premium, annual | $14 a month billed annually ($168 a year); DataCamp shows a $28 list | All 800+ courses, tracks, projects and certifications |
| Premium, monthly | $35 a month | The same, and the account can be paused |
| Teams | $14 per user a month billed annually | Premium plus admin dashboard, license management and reports |
Source: datacamp.com/pricing, yearly and monthly views, read 24 October 2026.
DataCamp also runs dated sales; its Halloween page showed Premium at $165 for the first year against $330 on 24 October. The box below shows the live offer and disappears when it ends.
Live sale
DataCamp Premium 50% off. $165 for a year instead of $330 · 790+ data and AI courses. ends Oct 31. Verified 6 Oct 2026 on DataCamp's sale page (terms: Oct 5 to Oct 31, 2026); 28 Oct 2026 datacamp.com/pricing: Premium $28 -> $14/month billed annually, Premium monthly $35 (not discounted), Teams $28 -> $14/user/month billed annually.
See the DataCamp deal →Two things to know before you pay. A monthly plan can be paused; a yearly plan cannot. And the most common one-star complaint in DataCamp’s Trustpilot reviews is an annual renewal charged without notice and not refunded, so note your renewal date. College students can ask about DataCamp’s Premium Student Plan, which its pricing FAQ describes as over 50% off. Our DataCamp pricing guide and DataCamp Black Friday guide cover the timing in detail.
Are DataCamp Courses Free?
Partly. The free Basic plan opens the first chapter of every course, with no card and no time limit, plus cheat sheets, tutorials, skill assessments and a professional profile. Full courses, tracks and certificates need Premium. That is enough to try Introduction to Python, SQL and R before paying anything.
There is no legitimate free download of DataCamp courses. They run in the browser and in DataCamp’s mobile app, and sites offering downloads are distributing pirated copies.
Is DataCamp Good for Beginners?
Yes. Most courses on this list are labeled Basic, need no coding background, and check every exercise as you go. The AI tutor answers questions inside the lesson, which recent Trustpilot reviewers single out. Beginners should start with Introduction to Python or Introduction to SQL, then follow a career track rather than picking courses at random. DataCamp rates 4.6 from 984 reviews on Trustpilot.
Cheaper DataCamp Alternatives
DataCamp at $168 a year is already one of the cheaper ways to learn data skills. These options cost less, or nothing:
- Kaggle Learn (free): short, browser-based courses in Python, pandas, SQL and machine learning. Less structure and no recognized certificate, but zero cost.
- Microsoft Learn (free): the official PL-300 learning path for Power BI, the free alternative to DataCamp’s Power BI track.
- Coursera with financial aid: most programs accept aid applications; see our Coursera financial aid guide and DataCamp vs Coursera.
- Udemy single courses: one course, bought once, often on sale, for one skill you need. See our best Udemy Python courses and DataCamp vs Udemy.
- Dataquest: text-based lessons with larger projects; see DataCamp vs Dataquest.
- 365 Data Science: video-first career tracks; see our eight DataCamp alternatives for prices.
What Learners Say
Recent Trustpilot reviews praise the format most: short lessons with in-browser coding, practice files that carry on after the course, and the AI tutor. One instructor uses DataCamp to supplement community college computer science classes; another reviewer credits the platform with helping them through a master’s in data analytics.
The critical voices are consistent too. On Reddit, a recent “is DataCamp still worth it in 2026?” thread split between subscribers who learned Python, Git and generative AI there and others who found the material surface level and the certifications of limited use for hiring. Our reading: DataCamp is very good at building fluency and weak at proving it, so pair it with projects.
Conclusion
DataCamp is one of the best platforms for learning data analysis, data science and the tools around them, and its size is the main obstacle. If you are starting out, take Introduction to Python or Introduction to SQL, then commit to one career track: Data Analyst in Python for analytics, Associate Data Scientist in Python for data science, or Data Analyst in Power BI if your company runs Microsoft. If you already have the basics, the case studies on churn in Power BI and Tableau are the closest thing on DataCamp to a real analyst assignment.
Frequently Asked Questions
Are DataCamp courses worth it for beginners?
Yes. The introductory courses in Python, SQL, R and Power BI assume no coding experience and check every exercise as you go, and the first chapter of each is free. Follow a career track after your first course rather than picking at random.
Which DataCamp course should I take first?
Introduction to Python if you are undecided, because Python has the widest data job market and underpins most DataCamp tracks. Introduction to SQL if you want the fastest useful skill. Introduction to R if you will work in statistics or research.
How long does a DataCamp course take?
Most courses are two to five hours. Introduction to SQL takes about two hours, Data Manipulation with pandas four to six. Career tracks run 36 to 90 hours, which most people finish in two to four months at five to ten hours a week.
What is the difference between DataCamp courses, skill tracks and career tracks?
A course covers one topic in a few hours. A skill track groups several courses around one skill, such as SQL Fundamentals (7 courses). A career track stacks many courses and projects toward a role, such as Associate Data Scientist in Python (23 courses, 90 hours), and offers a certification at the end.
Does DataCamp give certificates?
Yes. Completing a course or track gives a statement of accomplishment you can add to LinkedIn. Separate certifications, such as Data Analyst, require two timed exams and a practical exam within 30 days and are included in Premium.
Do DataCamp certificates help you get a job?
They help as supporting evidence but will not get you hired on their own. The certifications with timed and practical exams carry more weight than course completions. Pair either with two to four portfolio projects on GitHub.
Are DataCamp courses free?
The first chapter of every course is free on the Basic plan, with no card required. Full courses, tracks and certificates need Premium, which is $14 a month billed annually ($168 a year) or $35 month to month.
Can you download DataCamp courses?
No. DataCamp courses run in the browser and in its mobile app. Sites offering free downloads are distributing pirated copies.
Which DataCamp course is best for Python?
Introduction to Python, then Data Manipulation with pandas, then Introduction to Statistics in Python. For a full path, the Data Analyst in Python or Associate Data Scientist in Python track.
Which DataCamp course is best for SQL?
Start with Introduction to SQL, the most-reviewed course on the platform, then the seven-course SQL Fundamentals track.
Which DataCamp course is best for machine learning?
Understanding Machine Learning for a no-code overview. To build models, the Machine Learning Scientist in Python track covers supervised and unsupervised learning, gradient boosting and deep learning with PyTorch in 85 hours.
Is DataCamp better than Coursera for these topics?
For hands-on coding practice, yes: you write code throughout every course. For a credential employers recognize, Coursera’s Google and IBM certificates carry more weight. Many learners use both.
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