The Python language has become one of the most sought after skills of the 21st century, as its usage in data science and artificial intelligence emerged. In fact, Python is one of the most popular programming languages today.
Learning Python creates opportunities for you to obtain a higher income. According to Indeed, Python developers could earn as much as $111,806 a year on average in the United States. The trend is moving upward, as well.
One amazing thing about Python is that you can master it online. You could start from the beginner level and become an adept coder at the end.
Currently, there are thousands of Python courses available. In this fast-paced world, you may not have enough time to sort out the best Python courses.
Thus, I decided to do the heavy lifting for you. I select the most practical and useful Python 3 online courses and break down each of them in an insightful way. You will only be left with a list of 12 courses.
This new list is now manageable; now, it is much easier to find the best Python course that meets your needs. This would certainly save you time and money.
Things You Should Know
First of all, I have separated the list into groups. I understand that visitors have different skill levels in Python and Programming, so users would find it more convenient to select the right courses.
The groups are
- Python Basics/Core Python
- Advanced Python
- Python for Data Science
- Free Python Courses
As these courses serve different purposes, they have distinct prerequisites. I will state them clearly when I discuss each course below.
Another thing you need to understand is that each Python course is not the same. This is mostly because instructors taught in different ways (mainly theoretical or project-based).
For this part, it’s totally subjective. However, I personally prefer project-based courses, as the course “forces” me to code on my own, which is very important in programming.
I will also include “my reviews” in the courses that I have already taken. This review will show the strengths and weaknesses of the courses or issues that I have faced.
Finally, I would like to disclose that this article contains affiliate links. Victory Tale partners with online learning platforms such as Udemy, Coursera, and Datacamp. This means that I will receive a small commission from these providers if you purchase through my links.
Python Basics/Core Python Courses
Courses in this group will teach you the basics of the Python programming language. For example, you will learn the syntax and understand it by heart.
To complete beginners in Python or programming, I suggest selecting 1-2 courses from this group before proceeding to specialty courses.
1. 100 Days of Code – The Complete Python Pro Bootcamp for 2021
100 Days of Code is unarguably one of the best Python 3 courses offered by Udemy. The creator is Angela Yu, lead instructor of App Brewery, one of London’s finest programming Bootcamp.
The course is project-based. The instructor mentions that it will simulate the real Bootcamp experience. You will spend the majority of your time coding on your own. Please be prepared!
- Variables and Data Types
- Conditionals and Loops
- Lists and Dictionaries
- Object-Oriented Programming (OOP)
- Files, Directories, Paths and Working with CSV Data
- Building a GUI Application and an API (Using Tkinter)
- Web Development in Python – You will build and deploy your first web application in this part. Noted that you will learn a crash course on HTML and CSS here, so you don’t need to learn them beforehand.
- and many more
The instructor hoped you could complete all of these in 100 days.
Based on my experience, completing the course in 100 days is extremely difficult. This is because each lesson is filled with numerous real-world projects, quizzes, and coding challenges. I ended up spending 2-4 extra hours for every 1 hour of video lessons.
Below are summaries of the strengths and weaknesses I have found.
- The instructor is great at explaining theory and projects alike. Her accent is clear and understandable.
- The instructor uses many interactive tools to help you understand the materials.
- She is responsive to the problems and issues you have had.
- You don’t need to install anything at the beginning to code. Thus, you will start coding very early in the course.
- Most of the course content is interesting and fun, especially the basic concepts.
- Projects are suitable for both absolute beginners and experienced developers. Beginners will receive more hints.
- Every Python exercise and hands-on in the course is practical and useful.
- Great downloadable resources overall
- You will use Pycharm after Day 15. This could be very slow and annoying if you have low-quality hardware.
- As you progress, the instructor will explain in less detail to simulate what a Python developer is doing in real life. This is intentional, but I’m not too fond of it.
- I fell asleep when I learned the GUI part.
- This course has a “data science part,” but you have to learn on your own because there is no video. If you really want to learn Python for Data Science, you may want to find other courses instead.
Overall, this is a good choice for those who want to learn Python online, especially learners who have no prior programming experience.
Course Length: 60 Hours
2. The Modern Python 3 Bootcamp
For anyone looking for a great theoretical Python 3 course, it is worth checking The Modern Python 3 Bootcamp by Colt Steele, a Bootcamp instructor at Galvanize.
Colt explains Python basics in great detail. Below are what you will learn from this course.
- Command-Line Fundamentals (MAC/LINUX/WINDOWS)
- Python Setup for MAC and Windows
- Variables, Strings, Integers
- Conditionals (If, elif, else) and Loops (For, while)
- Lists and Dictionaries
- Tuples and Sets
- Functions and Lambda Functions
- Debugging and Error Handling
- Object-Oriented Programming (OOP)
- HTTP Requests with Python + API Project
- Web Scraping Project
- SQL Basics
- and many more
Overall, the course captures the essence of basic-medium Python programming. The total length of this on-demand video course is 29.5 hours. Additionally, there are 200 quizzes and coding exercises and a few projects for learners to complete.
- The instructor is highly knowledgeable and has strong teaching skills. Everything he explains is effortless to understand. I also like his humor.
- The course is well-structured. The material is progressing from basic to advanced as it should be.
- Everything is explained in great detail.
- Video lectures are accompanied by slides, which you can use to review later.
- Useful real-world projects at the end.
- Generally a great python introductory course.
- The boring stuff is at the beginning and a bit lengthy. Thus, it will take you a while before you can start Python coding.
- There are too few coding exercises to help you master Python. You will need another project-based course.
Course Length: 29.5 Hours
3. 2021 Complete Python Bootcamp From Zero to Hero in Python
This is the most popular Python course on Udemy by a wide margin. With almost 1.2 million students, this course was created by Jose Portilla, Head of Data Science at Pierian Data Inc.
Jose’s course is concise compared to the first 2 courses I recommend. If you want a fast Python tutorial, this course is for you.
- How to use Jupyter Notebooks and create .py files
- Objects and Data Structure Basics (from Strings to Dictionaries and Tuples)
- Conditionals and Loops
- Functions and Methods (Lambda Functions Included)
- Object-Oriented Programming
- Python Decorators and Generators
- Web Scraping and Sending Emails with Python
Apart from video lectures, you will also receive a notebook for review and practice exercises and quizzes.
I see this course as a shortened version of Colt’s course. I also think that some parts, such as OOP, are too concise for new programmers like me. That’s why I chose Colt’s course instead.
However, as I have taken other courses from Jose, I am certain this course is worth considering for learners who desire a solid foundation in Python.
Course Length: 21 Hours
4. Complete Python Developer in 2021: Zero to Mastery
For everyone who loves to learn by doing, you also want to check this course by Andrei Neagoie, an experienced software developer.
This course teaches you how to build 12+ real-world Python applications from scratch. However, the course is not purely project-based. You will learn the basic features as well.
Course content has two main parts, core concepts and practical aspects like below:
- Basics of Programming, Python Interpreter, Difference between Python 2 and 3
- Summary of Data Types
- Conditionals, Loops, Functions + How to write a clean code
- Introduction to prominent developer environments: Pycharm, Jupyter Notebooks, VS Code and Sublime Text
- Object Oriented Programming and Functional Programming
- Decorators, Generators and Error Handling
- Modules: Debugging and Testing in Python
- Scripting in Python (Image Processing, Sending Emails, Creating a Password Checker, Building a Twitter Bot)
- Build a Web Scraper (Using BeautifulSoup Python Library)
- Web Development with Python (Using Flask)
- Automated Testing using Selenium
- Build Basic Machine Learning Models
Andrei’s course is a great introduction for everyone who wants to become a Python developer. Both essential basics and Python key features and usages are included adequately in this single course.
After completing this course, you are more than ready to take on Python’s advanced concepts and applications.
Course Length: 30.5 Hours
5. The Complete Python Course | Learn Python by Doing
If you want an online Python course that teaches you how to use Python like a professional, this course is among the best you could have. The creator of this course is Rob Percival, a Cambridge-graduate web developer.
Rob will teach you the basics. Below is what you will learn from the course.
- Introduction to Python (Numbers, Strings, Boolean, Lists, Dictionaries, Tuples, and Sets)
- If Statements, For/While Loops, Functions, Arguments and Parameters
- OOP in Python
- Dealing with Errors and Files
- Database in Python (Using SQLite)
- Asynchronous Python Development
- Web Scraping with Python + Browser Automation (Using Selenium)
- Python Web Development (Using Flask)
- GUI Development with Tkinter
- Data Structure and Algorithms in Python (Big O, Binary Trees, Nodes)
- and many more
This online Python class is a great blend of concepts and hands-on training. Every lesson is full of coding practices that help improve your understanding of the content.
Moreover, there are milestone projects to showcase how well you learn in the course and improve your skills to use Python in real life.
For example, you will build a currency exchange program by interacting with the REST API and create a scraping app.
Rob also guides how to avoid common pitfalls and develop good habits for you to become a better Python developer. If you want to become one, this course is a must-buy.
Course Length: 35 Hours
6. Python for Everybody Specialization
Python for Everybody Specialization is a course created by the University of Michigan that teaches Python to complete novices. Therefore, a programming background is not necessary at all.
Interestingly, this specialization is based on a book with a same name and comprises 5 courses:
1. Getting Started with Python: This course introduces you to the world of programming. You will understand why we need to program in real-life.
Subsequently, you will learn about Python basics such as variables, integers, strings, conditionals, functions, and loops.
2. Python Data Structures: This course will discuss strings, lists, dictionaries, sets, and tuples.
3. Using Python to Access Web Data: In this course, you will completely understand how to manage and retrieve various web data types. Furthermore, you will work with different data formats (HTML, XML, and JSON) in Python.
4. Using Databases with Python: This course will teach SQL basics, how to build web crawlers, and usage of D3.js to visualize your data.
5. Capstone: The end of your learning journey in this specialization. This is a project course that tests your skills acquired throughout the four courses above. You will retrieve, process, and visualize assigned data using Python.
Overall, this course is a flawless first course for anyone who wants to pursue data science career tracks, especially those who want to learn in a university-style environment.
The instructor noted that you should spend 3 hours a week for 8 months to complete this specialization. If you a fast learner like me, this is going to be tedious. Hence, it would help if you consider enrolling in a Udemy course over this specialization.
Similar to other Coursera courses, you can audit this course entirely free, but your assignment will not be graded, and you will not receive a certificate.
I don’t care much about the certificate (unless you want to show them on your resume), but I believe it is worth getting your homework graded by experts to be confident that you are on the right track.
Feeling convinced? Coursera allows you to take this course for free for 7 days. If you are happy about the learning experience, the monthly membership will cost you $49/month.
Advanced Python Courses
I recommend taking these advanced Python courses if you are a learner who has a strong interest in Computer Science or wants to know more about Python inner mechanics.
After finishing these courses, which is not easy to do, your Python skills would skyrocket to an expert level.
7. Python 3 Deep Dive (4 Courses)
If you are really serious about learning Python and want to understand every complicated aspect of this programming language, this series of courses by Fred Baptiste on Udemy is a must-buy.
Unlike other courses that only touch the surface, these 4 courses delivered an in-depth view of the Python language. You will understand how each component works (like an engineer!)
However, these courses are not for one with no programming skills. You will need a moderate background in Python to start taking them.
Let’s see what these 4 courses will teach you:
Part I (Functional)
This part discusses the inner mechanics of variables, numeric types, functions, scopes, decorators, tuples, and many more. You will also understand how to optimize the code efficiently.
The instructor will switch back and forth between the lecture and coding. This enables learners to experience both concepts and practicals.
Content Length: 44.5 Hours Ratings: 4.8/5.0 Students: 25,800+
Part II (Iteration, Generators)
Part II will focus on how sequences, iterables, context managers, and generators work in Python and the relationships between each one.
Unlike Part I, Part II is project-intensive. Each part of the course has its own project for learners to complete. In total, you will have 6 high-quality projects to improve your skills strongly.
Content Length: 34.5 Hours Ratings: 4.8/5.0 Students: 17,100+
Part III (Hash Maps)
This part is devoted to explaining Python dictionaries, sets, and related data structures. The instructor also discusses serialization and deserialization of dictionaries to JSON and specialized dictionaries such as DefaultDict and OrderedDict.
These are complex concepts that you could find no other courses to teach.
The course format is similar to Part I. However, you will have more coding practices with solutions to help you understand these sophisticated materials.
Content Length: 20.5 Hours Ratings: 4.9/5.0 (I have never seen this high.) Students: 12,300+
Part IV (OOP)
The last course in the series focuses solely on Object-Oriented programming. Suppose you are always confused about the Python class. This course is your first choice to take.
However, Fred doesn’t stop at Python classes. He will introduce you to the OOP concepts of Polymorphism, Single Inheritance, Descriptors, Enumerations, and conclude the course with Metaprogramming.
You will also have 6 projects to finish as in Part II, along with many opportunities to write python code on your own.
Content Length: 35 Hours Ratings: 4.8/5.0 Students: 11,200+
To conclude, Python 3 Deep Drive is probably the most comprehensive and advanced online Python course I have ever seen. If you manage to finish all materials, I am certain you are more than ready to apply for a Python programmer position.
Best Python for Data Science Courses
What I will discuss next is the best Python for Data Science courses. You will learn Python to be used in data science tasks, such as data analysis and data visualizations.
These courses will not focus on the core of Python Programming language. In other words, the instructor would teach you only python basic concepts (variables, strings, conditionals, etc.), skip OOP and other advanced computer science stuff, then move to NumPy, Pandas, and other data-science-related Python libraries.
Many courses in this category had no prerequisites, but I suggest otherwise. If you are an absolute beginner, you might want to take a core 1 Python course (numbered 1-6 in this list) before taking any “Python for data science courses.”
This is because Python fundamentals taught in almost all “Python for data science courses” are too brief to help you possess sufficient Python skills to tackle data science.
For instance, a newbie might confuse the increasingly complex syntax in NumPy or Pandas and utterly get lost in the sea of code.
On the other hand, if you are a polyglot programmer or have tons of programming experience, you take these courses with ease right now.
8. Python for Data Science and Machine Learning Bootcamp
This course by Jose Portilla teaches you how to use Python in data science and machine learning. You will start with Python language basics and end with Spark and deep learning with various Python libraries in between.
The video content can be separated into 4 parts with 25 hours in total length.
Part I: Basics
- Set Up Jupyter Notebook
- Python Basics (This part is 84 minutes long, obviously inadequate for a novice. However, Jose already mentioned that this course is not for an absolute beginner. Thus, you will need to take at least one Python online course beforehand.
Part II: Python for Data Analysis
- NumPy: Arrays, Indexing, Operations
- Pandas (A major Python library for data analysis): DataFrames, Merge, Join, Concatenate, Groupby, Dealing with missing data
Part III: Python for Data Visualization
- Seaborn – Distribution Plots, Categorical Plots, Matrix Plots, Regression Plots
- Plotly/Cufflinks/Geographical Plotting
Part IV: Machine Learning
- Linear/Logistic Regression
- K-Nearest Neighbors, Decision Trees, Random Forests, SVM Theory, K Mean Clustering
- Build Recommender Systems (A system that provides recommendations to visitors)
- Natural Language Processing with Python
- Deep Learning (You will use Tensorflow and Keras)
- Big Data and PySpark
I have taken this course myself. These are the key points that I have found.
- Jose is a great organizer. His course is well-structured. Everything is in perfect order. His accent is highly comprehensible.
- The lecture is concise and covers a huge number of topics.
- I am very new to Python, data science, and ML, but I could say the exercises are way too easy. They are not challenging enough.
- This is more or less a Python tutorial. Many topics included in the course are very shallow. I am certain you cannot create complex ML models by completing this course alone.
In my opinion, if you want a general overview of every useful Python library and machine learning algorithm, you should consider this course.
In contrast, if you want to deep dive on each topic such as Pandas. This course is not for you. You should take other Pandas courses instead.
Ratings: 4.6/5.0 Students: 415,000
9. Data Science Fundamentals with Python and SQL Specialization
This IBM specialization will start your data science journey by explaining the basic concepts through Python and SQL. The instructors confirmed that you would develop hands-on experience with many tools in the course.
As the name suggests, this is not a “Python course” but more like a data science one. However, I found out that minor courses in this specialization are excellent “Python for Data Science” courses, so I recommend this specialization here.
Interesting minor courses:
1. Python for Data Science and AI: A beginner-friendly course that provides the python knowledge you need for studying data science and artificial intelligence.
When you complete the course, you will be comfortable performing real-world tasks with Python, such as creating a basic Python program.
2. Statistics for Data Science with Python: You will learn the fundamental principles of statistics in Python, used in data analysis. This includes hypothesis testing, ANOVA, Regression and correlation analysis, and many more.
There are also 2 other data science courses that comprise a specialization. These courses are significant for building a solid data science career as well. If you enroll in this specialization, you should also take them to get a certificate from IBM.
- Tools for Data Science – A quick introduction to data science tools
- Databases and SQL for Data Science – An overview of databases and SQL
The workload for this specialization is manageable. IBM suggests you spend 4 hours a week, and you will finish it in 5 months.
Learning Python from one of the largest tech companies rarely disappoints anyone. Why don’t you give it a try?
You can try the full course for 7 days. If you want to continue learning, the tuition is $39 per month.
10. Applied Data Science with Python Specialization
This specialization in Coursera was also created by the University of Michigan. Christopher Brooks and other faculty members will introduce you to data science through Python. You will use a wide variety of Python libraries to perform fascinating data-related tasks.
Since this is an intermediate-level course, make sure you have prior python training or completed Python fundamental courses before enrolling.
There are 5 minor courses in this specialization:
1. Introduction: The instructors will discuss basic Python concepts along with NumPy and Pandas. You will be able to manipulate, prepare, and clean the data by using functions.
2. Applied Plotting, Charting & Data Representation in Python: You will be introduced to data visualization (creating charts) in Python and Matplotlib. The instructors would also recommend best practices that fit each particular problem.
3. Applied Machine Learning in Python: You will learn the background of machine learning (ML) and its different approaches and start using Scikit-Learn. The instructor will focus on supervised learning methods, how to evaluate them, and their limitations.
4. Applied Text Mining in Python: You will discover how Python handles texts and be introduced to the NLTK framework that manipulates texts.
Subsequently, you will prepare your texts for ML processes and apply basic NLP methods to text. When the course ends, you will be able to perform text classification and topic modeling.
The learning material seems to be great. However, several reviewers mentioned that the grading system might be problematic at this point (January 2021)
5. Applied Social Network Analysis in Python: This is the final course that introduces you to the world of network analysis by using the NetworkX library. You will understand the importance of connectivity, network centralization, and many more.
The Instructors recommend that every student spend 7 hours a week on the specialization, and you will complete it in 5 months.
However, I believe the workload here is intense, especially if you have full-time employment. I suggest you check whether you are free enough to complete the course before enrolling.
You could audit these courses entirely free, but still, it’s much better if you pay for the specialization. Experts will evaluate your assignments and tests, and you will receive an Applied Data Science Python Certification.
Similar to Course 6, the full experience would cost you $49 a month.
11. Datacamp Python Courses
Datacamp is a platform that specializes in teaching data science. Unlike Udemy and Coursera, Datacamp does not teach by lecturing students.
Each chapter will have a very short video by experts to guide learners. Mainly, you will learn Python programming by completing numerous assignments on its interactive platform.
There are dozens of Python courses in Datacamp. Each of them is grouped in skill tracks. You can choose which track you want to pursue. For instance, I can choose a Data Scientist Track if I want to become a data scientist.
However, please keep in mind that courses in each track overlap. This means in total there is far less content than it seems.
Secondly, Datacamp courses teach Python for data science, not for computer science. If you want a comprehensive course for the Python language, you should find better choices elsewhere.
Datacamp uses a subscription model. There is a standard plan ($12.42 per month) and a Premium Plan ($33.25 per month).
For learners who are interested only in Python for Data Science, subscribing to the standard plan is more than enough, as you will gain access to the majority of courses in the platform (335+ of them.)
However, if you are interested in premium content, including Tableau, Oracle, Power BI, and would like to complete real-world projects, a Premium plan is a definite choice.
Datacamp lets you try the first chapter of each course for free without providing credit card details.
My Reviews on Datacamp
I never subscribed to Datacamp, but I accessed the Premium content for weeks when Datacamp had a special campaign.
- Extremely beginner-friendly. Every Python course is designed to make users feel comfortable learning.
- You can learn anytime and anywhere. This is because you code everything on its interactive platform. Datacamp has a great app as well. Thus, you can learn on smartphones.
- I really like its gamey interface. It’s much harder to get bored or distracted.
- The curriculum covers various topics. This is more than adequate for anyone interested in learning Python for data science.
- The developers are actively updating the platform, so it’s getting better over time.
- I believe some assignments are oversimplified, as some codes are already written. In other words, someone has done the heavy lifting for you. This is not a real Python programmer experience, as it claims.
- You will have less experience working in professional development environments such as Pycharm, VS Code, and Jupyter Notebooks, as you will code mostly on the Datacamp platform.
Free Python Courses
Below are the Python courses that do not fit into any group, but I feel they are worth noting here.
Freecodecamp is a website built by computer science experts to provide free programming education to everyone. You can certainly find a free Python course here!
The website has two curriculums for Python:
- Scientific Computing with Python Certification – Despite its name, you will learn basic Python here. This includes networking, web services, and relational databases in Python as well. In the end, you will tackle scientific computing projects such as building a Polygon Area Calculator.
- Data Analysis with Python Certification – You will learn to use Python and its libraries (NumPy and Pandas) to perform data analysis and use knowledge to do the projects. Interestingly, you will build an analyzer to predict the sea level.
Instructors on Freecodecamp teach by using lectures. Though their content is shallower than paid courses, it’s free to access. If you are very new to Python or programming, experimenting here is a great option.