The Best Python Courses to Take in 2026: A Comprehensive Guide

I have spent the last few weeks researching Python courses, and my honest finding is that this market has split in two.

There is a body of free university material that has been quietly improving for a decade, and there is a set of paid interactive platforms that get you writing code inside 5 minutes.

Which one suits you comes down to a question almost no course listing asks: do you want to understand Python, or do you want to use it?

In this article, I'll cover the best Python courses across 8 categories, looking at beginner routes, free options, certifications, general programming, data science, AI, and the much thinner market at intermediate and advanced levels.

You can also see our guides to the best Python certifications and the best data science courses.

Course ratings, review counts and learner numbers last verified 15 September 2026.

In a Nutshell

If you read no further, here is where I landed.

• Best overall for most people: DataCamp's Introduction to Python, because it runs in the browser and you are writing code within minutes.
• Best free course: Harvard's CS50P, free to audit in full. 
• Best for a credential: the Python Institute's PCAP exam for something vendor-neutral, or DataCamp's Associate Python Developer track if you want the teaching and the certification together.
• Best for data science: DataCamp's Data Scientist in Python track, which has the largest review base of anything in this article.

Best Python Courses Comparison Table

Every DataCamp course we cover is listed below, with its live rating and learner count. Competitor courses are covered in the sections themselves.

Best Python Courses For Beginners

The best Python course for a complete beginner is one that removes setup entirely, because installing Python is where most people quit before writing a single line of code. Beginners also split into 2 groups that most listings treat as one: people who have never programmed, and people who already write JavaScript, R or SQL and just need the Python syntax. The second group does not need the first group's course.

1. Introduction to Python - DataCamp

This is our flagship beginner course and the one I recommend most often. It runs entirely in the browser, so there is nothing to install before you start.

• Level: Beginner, no experience needed
• Time: 4 hours
• Cost: Chapter 1 free, full access from $14/month billed annually
• Best for: Anyone who has never programmed and wants results in an afternoon

The course covers variables and types, lists, NumPy arrays, and basic plotting, taught by Hugo Bowne-Anderson and Filip Schouwenaars. Exercises run against a real interpreter and check your output, so you cannot pass by reading.

The learner count is the reason it leads this list. At that volume, every confusing exercise has been found and rewritten many times over, which is something a newer course cannot offer, no matter how good its syllabus looks.

2. Introduction to Python for Developers - DataCamp

The same language, taught for people who already program.

It skips the explanations of what a loop is and gets to what Python does differently.

• Level: Beginner in Python, not in programming
• Time: 3 hours
• Cost: Chapter 1 free, full access from $14/month billed annually
• Best for: Developers coming from JavaScript, Java, R or C

It moves faster than our standard introduction and spends its time on the things that actually trip up experienced developers in Python: mutability, truthiness, comprehensions, and the import system.

If you already code, start here instead of the course above. Sitting through an explanation of what a variable is when you have written 5 years of Java is a waste of an afternoon.

3. CS50's Introduction to Programming With Python - Harvard University

The strongest free beginner course available anywhere, taught by David Malan and Brian Yu to the same standard as the on-campus Harvard course.

• Level: Beginner, but demanding
• Time: Roughly 9 weeks at a few hours per week
• Cost: Free to audit, optional paid certificate
• Best for: People who want to understand programming, not just ship a script

It teaches functions, exceptions, regular expressions, object-oriented programming, and unit testing, with problem sets that are genuinely hard. You install Python yourself and use a real editor, which is more friction at the start and better preparation for everything after.

The trade-off is pace and support. There is no adaptive feedback, and nobody checks in on you, so completion depends entirely on your own discipline. Plenty of people start CS50P and stop at week 3.

4. Python for Everybody - University of Michigan, Coursera

Probably the most-taken Python course in the world, built by Charles Severance around his own free textbook.

• Level: Beginner
• Time: Several months as a full specialization
• Cost: Free to audit individual courses, subscription for the certificate
• Best for: Learners who want a gentle pace and a university name attached

The teaching is patient and clear, and the specialization carries you from first principles through to working with databases and web data. Severance is a good lecturer, and the accompanying book is free.

It is also showing its age in places, particularly around tooling and Python versions, and the pace will frustrate anyone who already programs.

5. Learn Python 3 - Codecademy

The closest competitor to DataCamp's format: browser-based, interactive, no setup required.

• Level: Beginner
• Time: Around 25 hours
• Cost: Partly free, full course on a paid plan
• Best for: People who bounce off video lectures and want to type

It is quite well built, and the interactive model works.

Where it differs from ours is focus: Codecademy teaches Python as a general language, while our beginner track is aimed at data work from the first exercise.

Our pick: Start with our Introduction to Python if you have never programmed, or Introduction to Python for Developers if you already do. If you would rather have depth than convenience, take CS50P instead.

Best Free Python Course

The best free Python course is Harvard's CS50P, and I would rather say that plainly than build an argument for one of ours. It is free to audit in full, taught to university standard, and more rigorous than anything else at that price.

There is a second question hiding in this category, though, and it has a different answer.

Asking which single free course is best is not the same as asking how to keep learning Python for free over a year, where breadth beats any one course.

1. CS50's introduction to programming with Python - Harvard University

Our pick for this category, for the reasons in the beginner section above: real rigour, real problem sets, no paywall on the material itself.

• Level: Beginner, demanding
• Time: Roughly 9 weeks
• Cost: Free to audit
• Best for: Self-directed learners who want the strongest free option

The only thing you pay for is the certificate, and the certificate is the least valuable part. If you finish the problem sets you will have code to show, which is worth more.

2. Python Programming MOOC - University of Helsinki

A full university Python curriculum, free, with automated grading and no enrollment cap.

• Level: Beginner to intermediate
• Time: 14 parts, several months
• Cost: Free
• Best for: Anyone who wants university depth and structure at no cost

It goes considerably further than most free courses, into object-oriented programming and larger projects, and the automated grader gives you immediate feedback.

Finishing all 14 parts is a real achievement, and very few people do.

3. Learn Python - Scrimba

Short, fully interactive, and the best free option if you want to be typing rather than watching.

• Level: Beginner
• Time: Around 6 hours
• Cost: Free
• Best for: A fast, low-commitment first look at the language

Scrimba's format lets you pause a video and edit the code inside it, which suits people who learn by fiddling.

It covers the fundamentals through to file handling and a project, and it will not take you to job-ready level on its own.

4. Google's Python Class - Google

Free written material, lecture videos, and exercises, aimed squarely at people who already program.

• Level: Beginner in Python, experienced elsewhere
• Time: A couple of days of focused work
• Cost: Free
• Best for: Working developers who want the fastest possible Python primer

It is dense, unglamorous, and effective, with strong sections on strings, lists, dictionaries, and file handling.

It is also old, so treat the tooling advice with caution while trusting the language fundamentals.

5. Introduction to Python, Chapter 1 - DataCamp

Every course on our platform has its first chapter free, including this one, with no card required.

• Level: Beginner
• Time: About 1 hour for chapter 1
• Cost: Free
• Best for: Finding out whether interactive learning suits you before paying

Being precise about this, because it matters: the free plan gives you the first chapter of every course, not whole courses.

What it does give you in full is all of our tutorials and cheat sheets, our live code-alongs, skill assessments, and competitions. Across more than 300 Python tutorials and 20 Python cheat sheets, that is a lot of free material, and it is a different proposition from one free course.

Our pick: Take CS50P. If you already program and want to move fast, Google's Python Class will get you productive in days rather than weeks.

Best Online Python Courses With Certification

A Python certification earns its cost when you need to get past a resume screen without a portfolio, and earns very little once you have one. Before choosing, separate the 3 things that all get called certification: a completion certificate, which says you finished a course; a proctored exam, which says you passed an independent test; and a university credential, which says an institution vouches for you.

1. Associate Python Developer - DataCamp

DataCamp's answer to the teaching gap the Python Institute leaves: a track that takes you from fundamentals to a certification in one sequence.

• Level: Beginner to associate
• Time: 28 hours
• Cost: Included with a subscription, from $14/month billed annually
• Best for: People who want the skills and the credential together

The certification at the end involves timed assessments and a practical exercise rather than a completion badge, which is the part worth caring about.

Some people feel that a vendor-neutral exam carries more weight with an employer who has never heard of DataCamp, though with the skills that you learn, you'll be more than ready to show them everything you can learn with DataCamp! 

2. Associate Data Scientist in Python - DataCamp

The analytical counterpart, and a much larger commitment.

• Level: Beginner to associate
• Time: 90 hours
• Cost: Included with a subscription
• Best for: People targeting an analyst or junior data scientist role

At 23 courses, this is not something to start casually.

It covers Python, statistics, machine learning, and the reporting work that actually fills the job, and it takes most people a few months.

3. PCEP and PCAP - Python Institute

The only widely recognized vendor-neutral Python qualifications, meaning the only ones that test Python itself rather than a platform's own curriculum.

• Level: PCEP entry, PCAP associate
• Time: Exam only, study time is up to you
• Cost: Paid exam, check current pricing before booking
• Best for: Career changers who need a credential an employer will recognise

Worth clearing up, because several other roundups currently say otherwise: PCAP has not been retired. The Python Institute's own PCAP page lists PCAP-31-03 as the active version with no retirement date, shows PCAP-31-04 as in development for release in Q3 2026, and states that the update "does not affect the five-year validity of credentials already earned".

If you see a claim that these exams expired on 31 August 2026, check it at the source before you act on it.

The exams test you but do not teach you, which is the gap most people need to fill. That is what the two DataCamp tracks are for.

4. PCAD, certified associate data analyst with Python - Python Institute

The other thing rival articles have missed is how far this family now extends beyond PCEP and PCAP.

• Level: Associate
• Time: Exam only
• Cost: Paid exam
• Best for: Analysts who want a credential matched to analysis rather than general programming

Alongside PCEP and PCAP there is now PCED and PCAD for data analysis, PCET and PCAT for testing, and PCES, PCEA and PCEI for security, automation and AI.

If you want a qualification aimed at the work you actually do, the two-exam ladder everyone else describes is out of date.

5. Scientific Computing with Python - freeCodeCamp

A free certification, which makes it the honest recommendation for anyone who cannot pay.

• Level: Beginner to intermediate
• Time: Varies, 5 projects to complete
• Cost: Free
• Best for: Learners who need something to show and have no budget

It carries less weight than a proctored exam, and the projects are real work that produces code you can point at. A free certificate (though not an accredited Certification) plus a public repository beats an empty resume. Cisco Networking Academy also runs free Python Essentials courses that prepare you for PCEP.

We go deeper on all of this, including current exam costs, in our guide to the best Python certifications.

Our pick: Take our Associate Python Developer track if you need the teaching as well as the certification. Take PCAP if you want a credential that travels.

Best Python Programming Course

A Python programming course teaches the language as a general-purpose tool, which is a genuinely different subject from Python for data analysis, even though the first 10 hours look identical.

Choose this route if you are heading towards backend work, automation, or scripting rather than notebooks and dataframes.

I should be upfront: DataCamp is primarily a data-skills platform. For pure software engineering, there are options below that go deeper on recursion, memory, and data structures than we do.

1. Python Programming - DataCamp

Our track for people who want Python as a language rather than as a data tool, covering the software-engineering side we are less known for.

• Level: Beginner to intermediate
• Time: 19 hours
• Cost: Included with a subscription, from $14/month billed annually
• Best for: Developers who want structured Python without the statistics

It runs through functions, object-oriented programming, and writing code other people can maintain.

Shorter than our data tracks, and deliberately so.

2. Software Engineering Principles in Python - DataCamp

The course I point people to when their scripts work, but nobody else can run them.

• Level: Intermediate
• Time: 4 hours
• Cost: Included with a subscription
• Best for: Analysts whose code needs to become software

It covers modularity, documentation, packaging, and testing: the difference between a notebook and something you can hand over.

This is perhaps the single most undervalued course in our Python catalog.

3. Object-Oriented Programming in Python - DataCamp

Classes, inheritance, and the object model, taught with the kind of examples you actually meet in a codebase.

• Level: Intermediate
• Time: 4 hours
• Cost: Included with a subscription
• Best for: Anyone who has read a class definition and bluffed

Most Python learners avoid OOP for years and then hit a library that assumes it.

Four hours here removes that problem permanently.

4. Learn to Code in Python - Boot.dev

A strong pure-programming alternative, and more computer-science heavy than anything we offer.

• Level: Beginner to intermediate
• Time: Months, as a full path
• Cost: Subscription
• Best for: People aiming at backend engineering rather than analysis

It is gamified, which sounds gimmicky and works better than it should for keeping people going.

The content covers algorithms and data structures properly rather than gesturing at them.

5. Python Crash Course - Eric Matthes

Not technically a course at all, but still the book I recommend most often to self-teachers.

• Level: Beginner to intermediate
• Time: Self-paced
• Cost: One-off book purchase
• Best for: People who read faster than they watch

The second half is 3 substantial projects, including a game and a web application, which is more finished work than most video courses produce.

If you learn from text, this can beat a subscription.

Our pick: Our Python Programming track for a structured route, plus Software Engineering Principles in Python. If your goal is backend engineering specifically, Boot.dev is a good shout.

Best Python Data Science Course

The best Python data science course is our Data Scientist in Python track, and this is the category where I think DataCamp is straightforwardly the strongest option, rather than a strong competitor. It also has the largest review base behind any of the courses in this article.

Sequence matters more here than anywhere else. Learning pandas before you can write a function produces people who can copy a notebook and not much else.

1. Data Scientist in Python - DataCamp

The full career path, from Python fundamentals through statistics and machine learning to communicating results.

• Level: Beginner to job-ready
• Time: 26 hours
• Cost: Included with a subscription, from $14/month billed annually
• Best for: Anyone targeting a data science role from a standing start

The ordering is the value here.

It teaches you to write functions before it teaches you to manipulate dataframes, which sounds obvious and is the opposite of how most self-taught paths go.

Most people spread the 26 hours over 2 to 3 months and build their own projects alongside it. Doing it in a fortnight is possible, though I would recommend taking more time over it.

2. Introduction to Data Science in Python - DataCamp

The shortest honest route from nothing to a finished analysis.

• Level: Beginner
• Time: 4 hours
• Cost: Chapter 1 free, then a subscription
• Best for: Testing whether data work interests you at all

It carries the highest rating of any course in this article. Four hours is enough to find out whether you enjoy this before committing to a 26-hour track.

3. Data Manipulation with pandas - DataCamp

If you only take one course in this section, this is the one with the widest daily application.

• Level: Beginner to intermediate
• Time: 4 hours
• Cost: Included with a subscription
• Best for: Anyone who works with tabular data, in any role

Subsetting, grouping, aggregating and joining, which is most of what a working analyst does most days. Analysts who never learn this properly spend years writing loops where a groupby would do. It's also one of the courses on this list that uses DataCamp's AI Tutor, which provides adaptive, personalized learning. 

4. IBM Data Science Professional Certificate - IBM, Coursera

One of the most popular data programs online, with over 470,000 enrolled learners across its 12 courses.

• Level: Beginner
• Time: Several months
• Cost: Subscription
• Best for: Learners who want a recognizable employer brand on the certificate

The breadth is real with this course. The common criticism, which I think is fair, is that 12 courses covering everything ends up shallow in each, and the capstone is where most of the actual learning happens.

5. Data Analysis with Python - freeCodeCamp

Free, certified, and it teaches the exact libraries that job descriptions list.

• Level: Beginner to intermediate
• Time: Self-paced, 5 projects
• Cost: Free
• Best for: Analysts on no budget

NumPy, pandas, Matplotlib, and Seaborn on real datasets, with no paywall at any point. Kaggle Learn is worth adding alongside it for practice data.

Our pick: Our Data Scientist in Python track if you want one structured path, or Data Manipulation with pandas on its own if you already code and just need the tools.

Best Python AI Course

Python AI courses are split into 2 jobs that get confused constantly: building features on top of existing models, and building the models themselves.

The first needs API design, retrieval, and evaluation; the second needs linear algebra and PyTorch. Pick wrong, and you will spend 30 hours learning something you never use.

Recency matters more in this category than in any other. A 2024 AI course is teaching an API that has since changed, which is why I have put the content refresh date in the course strips below.

1. Associate AI Engineer for Developers - DataCamp

Our track for shipping AI features, aimed at developers rather than researchers.

• Level: Intermediate
• Time: 29 hours
• Cost: Included with a subscription, from $14/month billed annually
• Best for: Developers adding AI to an existing product

It covers working with APIs, embeddings, retrieval-augmented generation, and evaluating output, which is the actual job of most people with "AI" in their title now. No model training.

2. Introduction to LLMs in Python - DataCamp

The course for understanding what is happening inside the model, rather than just calling it.

• Level: Intermediate
• Time: 3 hours
• Cost: Included with a subscription
• Best for: Engineers who want the mechanics, not just the API

Transformers, tokenization, attention, and fine-tuning, in Python, in 3 hours. It assumes you can already write Python comfortably.

3. Developing AI Systems with the OpenAI API - DataCamp

The production-patterns course: what to do once the prototype works and real traffic arrives.

• Level: Intermediate
• Time: 3 hours
• Cost: Included with a subscription
• Best for: Anyone whose AI prototype needs to survive contact with users

Error handling, rate limits, moderation, function calling, and cost control. Unglamorous, and the difference between a demo and a product.

4. Introduction to Deep Learning with PyTorch - DataCamp

For the other route: building models rather than consuming them.

• Level: Intermediate
• Time: 4 hours
• Cost: Included with a subscription
• Best for: People heading towards research or ML engineering

Tensors, autograd, training loops, and evaluation. You will want comfort with NumPy and some linear algebra before starting.

5. Practical Deep Learning for Coders - fast.ai

Free, and the most distinctive teaching approach in machine learning.

• Level: Intermediate
• Time: 8 lessons, substantial
• Cost: Free
• Best for: Coders who want a working model before the theory

Jeremy Howard teaches top-down: you train a working image classifier in lesson 1 and learn why it works afterward. It suits some people enormously and frustrates others, and since it is free, the cost of finding out is an evening.

Andrew Ng's Deep Learning Specialization from DeepLearning.AI remains the canonical bottom-up alternative if you would rather have theory first, and Hugging Face's free LLM course is the closest thing to our own LLM material.

Our pick: Our Associate AI Engineer for Developers track if you are shipping AI features, or Introduction to Deep Learning with PyTorch if you want to build the models. fast.ai is a good free option.

Best Intermediate Python Course

You are ready for an intermediate Python course when you can write a script that works, but cannot explain why it breaks on someone else's machine.

That is a more useful test than any syllabus, and it is the gap this category closes.

This is also where most self-taught learners stall. Beginner material is abundant, and intermediate material asks you to care about things that are not immediately fun.

1. Intermediate Python - DataCamp

The canonical step 2, and by some distance the most-taken course in this section.

• Level: Intermediate
• Time: 4 hours
• Cost: Included with a subscription, from $14/month billed annually
• Best for: Anyone who finished a beginner course and stalled

Matplotlib, dictionaries, pandas, logic and control flow, and looping patterns. It is the direct sequel to our Introduction to Python, and the two together are the most common route people take with us.

2. Python Toolbox - DataCamp

The course that makes your code look like Python rather than translated Java.

• Level: Intermediate
• Time: 4 hours
• Cost: Included with a subscription
• Best for: People whose Python works but reads badly

Iterators, generators, comprehensions, and lambda functions. Generators, in particular, are the point where memory stops being something you can ignore.

3. Writing Functions in Python - DataCamp

Decorators, scope and context managers: the things that separate scripting from engineering.

• Level: Intermediate
• Time: 4 hours
• Cost: Included with a subscription
• Best for: Anyone who has copied a decorator without understanding it

Decorators are the concept most Python developers use daily and could not implement from scratch. This fixes that in an afternoon.

4. Real Python membership - Real Python

A subscription library rather than a course, and some really good written Python material.

• Level: Intermediate to advanced
• Time: Ongoing
• Cost: Subscription, much of the site free
• Best for: People who prefer reading to video and want depth on demand

The tutorials are unusually careful and go deeper than most paid video courses. It is a reference library rather than a path, so it suits people who already know what they need to learn.

5. Talk Python Training - Talk Python

Video courses from Michael Kennedy, who also runs the podcast.

• Level: Intermediate to advanced
• Time: Varies by course
• Cost: Per course or bundled
• Best for: Web and API developers working in Python

The catalog covers ground many places do not, particularly web frameworks, async, and deployment. Dan Bader's Python Tricks is worth adding if you want idiomatic Python in book form.

Our pick: Take Intermediate Python then Writing Functions in Python. Add a Real Python membership if you learn better by reading.

Best Advanced Python Course

Genuinely advanced Python material is rare, and most courses labeled "advanced" are intermediate courses with a confident title. Real advanced content covers the interpreter, concurrency, profiling, and the data model, and there is far less of it than the market implies.

Our own numbers show the drop-off plainly. Intermediate Python has 1.4 million learners; Intermediate Object-Oriented Programming has 9,594. Almost nobody goes past the middle, which is exactly why going past it is worth so much.

1. Writing Efficient Python Code - DataCamp

Profiling and optimisation, which is where advanced Python actually starts.

• Level: Intermediate to advanced
• Time: 4 hours
• Cost: Included with a subscription, from $14/month billed annually
• Best for: Anyone whose code is correct but slow

It teaches you to measure before you optimize, using timing and memory profiling rather than guesswork. Most performance work people do by instinct is aimed at the wrong line.

2. Intermediate Object-Oriented Programming in Python - DataCamp

Inheritance, polymorphism, and designing class hierarchies, you will not regret.

• Level: Advanced
• Time: 4 hours
• Cost: Included with a subscription
• Best for: Developers designing libraries rather than using them

The lowest learner count of anything in this article, and one of the most useful courses in it. Take that as a recommendation rather than a warning.

3. Introduction to Testing in Python - DataCamp

pytest, fixtures, and test design. Testing is the clearest line between people who write scripts and people who write software.

• Level: Advanced
• Time: 4 hours
• Cost: Included with a subscription
• Best for: Anyone whose code other people depend on

It covers what to test rather than only how, which is the harder half. Tests that assert the wrong things are worse than no tests.

4. Machine Learning Scientist with Python - DataCamp

The longest and most demanding path we publish.

• Level: Advanced
• Time: 85 hours
• Cost: Included with a subscription
• Best for: People moving from analysis into machine learning engineering

21 courses covering supervised and unsupervised learning, deep learning, and model deployment.

A months-long commitment, and the only thing in this article I would call genuinely hard.

5. Fluent Python - Luciano Ramalho, O'Reilly

A book, and the standard recommendation for advanced Python, for good reason.

• Level: Advanced
• Time: Months, realistically
• Cost: One-off book purchase
• Best for: Developers who want to understand the data model properly

It explains why Python behaves as it does, covering the data model, protocols, metaprogramming and concurrency at a depth no video course reaches. If you read one advanced Python thing, read this.

For video, ArjanCodes covers design patterns and architecture well, and Anthony Shaw's CPython Internals is the book to read if you want to know how the interpreter itself works.

Our pick: Start with Writing Efficient Python Code and Introduction to Testing in Python, then read Fluent Python. No video course substitutes for that book.

How We Chose These Courses

Ratings, review counts, and learner numbers come from live course data pulled on the date in the freshness stamp near the top of this article, not from a spreadsheet filled in once. Where a track is listed, its rating is a review-weighted average across the courses inside it, because a track page on its own carries too few reviews to mean much.

We included free and competitor courses wherever they beat ours, and said so in the sections where that happens. We excluded courses with no content update in the last 18 months, which removed several well-known options still being recommended elsewhere.

Final Thoughts

For most people starting out, our Introduction to Python is where I would begin, largely because it removes the setup step that stops so many people in week 1.

If you want a good amount of depth and do not mind installing things yourself, CS50P is a good alternative. 

What struck me most putting this together is how thin the advanced end of this market is. There are hundreds of beginner Python courses and perhaps a dozen serious advanced ones. If you can get past intermediate, the competition drops away fast, and almost nobody does.

If you want to start today and commit to a learning path, I recommend the Python Data Fundamentals track, which covers the whole beginner section above in one sequence.