I was in the same boat a while back, trying to figure out the best way to learn Python and Data Science. After trying a bunch of different courses, here’s what worked best for me: I started with Automate the Boring Stuff with Python, which was great for getting comfortable with Python basics. Then, I took Jose Portilla’s Python for Data Science & ML Bootcamp on Udemy, which helped bridge the gap between Python and real-world Data Science applications.For more structured learning, I joined the Logicmojo Data Science classes and it really helped me get hands-on experience with real-world projects, SQL, and ML models. Alongside that, I also followed Andrew Ng’s Machine Learning course on Coursera, which is a must for understanding ML fundamentals. Once I had the basics down, I started practicing on Kaggle that’s where I really learned how to apply my knowledge with real datasets. If you r serious about Data Science, I’d highly recommend focusing on hands on projects and working with real-world datasets rather than just watching tutorials. These projects actually add value to your resume. I have created my GitHub also with projects I learned. Interviewer can directly see your Github, it creates a good impression about your work experience in data science. In short : Start with Python basics (Automate the Boring Stuff), take a solid Data Science course and get your hands dirty with Kaggle. Learning by doing makes all the difference. Answer from vinit__singh on reddit.com
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Reddit
reddit.com › r/learnpython › what's the best course for learning python and data science?
r/learnpython on Reddit: What's the best course for learning Python and Data Science?
December 30, 2021 -

Hi everyone, I was wondering if I could get any recommendations or suggestions on the best online course I can take to learn Python and Data Science? I've been a data analyst for 3 years now, dabbling into a little bit of machine learning on past projects but certainly not the bulk of my work. I worked with SAS for 2 years, and the past year I've been using SQL (although during my SAS time I used SQL through SAS).

I want to learn python, focused mostly on data analytics/science, so I'm looking for a course to take. I know there are plenty of free sources out there, but I need some structure to stay focused when I'm starting out. I took two intro Python courses about a year ago and have used it sparsely here and there, so I'm not a complete beginner but fairly new to it. I've looked at these two so far.

100 Days of Code: The Complete Python Pro Bootcamp for 2022. Looks good for learning Python, but it looks like there's a lot of web-development content.

Python for Data Science and Machine Learning Bootcamp. Looks like it covers a lot of the data science aspect, but maybe not as good for someone with only a little bit of Python experience.

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https://automatetheboringstuff.com/ https://ehmatthes.github.io/pcc/ Do those 2 courses in that order, then come back here for data science recommendations
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I was in the same boat a while back, trying to figure out the best way to learn Python and Data Science. After trying a bunch of different courses, here’s what worked best for me: I started with Automate the Boring Stuff with Python, which was great for getting comfortable with Python basics. Then, I took Jose Portilla’s Python for Data Science & ML Bootcamp on Udemy, which helped bridge the gap between Python and real-world Data Science applications.For more structured learning, I joined the Logicmojo Data Science classes and it really helped me get hands-on experience with real-world projects, SQL, and ML models. Alongside that, I also followed Andrew Ng’s Machine Learning course on Coursera, which is a must for understanding ML fundamentals. Once I had the basics down, I started practicing on Kaggle that’s where I really learned how to apply my knowledge with real datasets. If you r serious about Data Science, I’d highly recommend focusing on hands on projects and working with real-world datasets rather than just watching tutorials. These projects actually add value to your resume. I have created my GitHub also with projects I learned. Interviewer can directly see your Github, it creates a good impression about your work experience in data science. In short : Start with Python basics (Automate the Boring Stuff), take a solid Data Science course and get your hands dirty with Kaggle. Learning by doing makes all the difference.
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Reddit
reddit.com › r/learnpython › where to learn data science with python??
r/learnpython on Reddit: Where to learn data science with python??
July 2, 2023 -

Hello guys, you may think what a stupid question I am asking but will you please help me from where to study or learn data science at best. Novice here!! Please also share links or study materials I would be thankful to you Also appreciate you help 🙏🙏

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These might help: Open Source Society — Path to a free self-taught education in Data Science Python Data Science Handbook — learn to use Python libraries such as NumPy, Pandas, Matplotlib, Scikit-Learn, and related tools to effectively store, manipulate, and gain insight from data Python for Data Analysis — nuts and bolts of manipulating, processing, cleaning, and crunching data in Python Data Analysis with Python — online course offered by University of Helsinki, data analysis pipeline using Python and its data analysis ecosystem
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I'm going through codecademy right now. It's just at the threshold of good. I don't think any employers care about the cert, but it has gotten me up and started enough to do my own projects and implement major libraries/work with data/SQL/etc. I can't saying I'm enjoying it, but it is giving me all the info in one place.
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Reddit
reddit.com › r/learnpython › best way to learn python if my goal is data science?
r/learnpython on Reddit: Best way to learn Python if my goal is data science?
August 25, 2025 -

I’ve been meaning to pick up Python for a while, mainly because I want to get into data science and analytics. The problem is most beginner resources just focus on syntax but don’t connect it to real projects.For those who learned Python specifically for data-related careers, what path worked best for you? Did you just follow free tutorials, or did you go for a proper structured course?

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My advice to all beginners is to start working on your own projects (those related to hobbies / interests / side-hustles / family obligations / work tasks) as early as possible, as the focus will then be on solving problems well understood by the beginner rather than on the lower level specific coding elements (which will be learned at need). So follow whatever initial learning path you prefer (good suggestions in the wiki for this subreddit) but put more emphasis on those related to file handling, data manipulation, and filtering. Start playing with pandas early. Visit kaggle.com for sample data sets and examples of work around them. You may also like to learn to use Jupyter Notebooks (which you can also use from within editors/IDEs such as VS Code, PyCharm and Spyder) as well as in a web browser.
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MOOC - university of Helsinki and my Python and Data Science course are great. Sorry for the self promo but check out my course content and reviews, etc. It might be what you're looking for.
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Reddit
reddit.com › r/learnpython › python for data analysis
r/learnpython on Reddit: Python for Data Analysis
April 4, 2023 -

Hey guys! So I work as a Data Analyst with SQL, Tableau and Excel but I would like to take the next step which is programming with python for Data Analysis.

Can anyone recommend a course or bootcamp for this? I have 0 programming experience btw. I dont want to learn things out of my scope like creating apps or scraping the web.

I want to learn something useful for my job. For example I would like to be able to predict when a user will churn, how to predict the customer lifetime value, how to do machine learning in ways that will help the company and make me more valuable. I believe I need to learn pandas,numpy, seaborn, pyspark, tensorflow, matplotlib etc.

Thanks for the help!

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There's literally a book called Python for Data Analysis by Wes McKinney who created Pandas. It is expensive to buy in physical form, but entirely free on his website https://wesmckinney.com/book/
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I recommend you take a look at freecodecamp's Data Analysis with Python curriculum. They also have in-depth course videos on Data Analysis with Python and Python for Data Science on youtube.
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Reddit
reddit.com › r/learnpython › what is the best website to learn python on as a student in data science who knows almost nothing about data science?
r/learnpython on Reddit: What is the best website to learn python on as a student in data science who knows almost nothing about data science?
December 11, 2024 -

I'm taking an intro to data science class next quarter in January. One of my friends who are already in this class told me that if I have zero python knowledge, it's best I try to learn it during Winter break because the class is taught as if you have some knowledge in the language.

He also told me to learn pandas, which I presume is a part of python. So, is there any online resource I can use to effectively learn some python in a few weeks as a data scientist?

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There's no "best" here. The best thing is to start anywhere and not get stuck in analysis paralysis. I personally like automatetheboringstuff.com a lot. Or if you like video tutorials better: https://youtube.com/playlist?list=PL-osiE80TeTskrapNbzXhwoFUiLCjGgY7&si=TfatTzTq77OqWmrp If these don't click with you, this sub has a sidebar with tons of resources.
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Automate The Boring Stuff by Al Sweigart is a good start.
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Reddit
reddit.com › r/learnpython › how should i go about learning python for data science?
r/learnpython on Reddit: How should I go about learning Python for data science?
September 12, 2019 -

Not really interested in development but I want to work with data in the future (in a business analyst type of role). What would be the most effective way to learn Python for this specific purpose?

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Pick up a book like "Hands on Machine Learning with Scikit Learn & Tensorflow".

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You’ll more than likely need a decent sense of development with python in order to utilize its tools for data manipulation. I’d start with learning the ins and outs of numpy, matplotlib and pandas packages. Once you’re comfortable with that go on to scikit and ML. Jupyter labs are awesome for DS as well. Simply creating some data frames and throwing them on a line graph is one thing. But scraping and cleaning your own data is another. Sentdex on YouTube has great videos

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Reddit
reddit.com › r/learnpython › tips for learning python for data science
r/learnpython on Reddit: Tips for learning python for data science
August 6, 2025 -

Hey guys , I am a 3rd year CSE student who wants to get into data science . Just got done with SQL and now want to learn python , should I focus more on the basic python concepts like list, tuples ,data structures , OOPs or more on the numpy, pandas etc and plz suggest a course for me Thank you

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I started with numpy pandas and matplotlib, thats the most basic you can do for data processing and visualization
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I would learn the basics first and then move onto the key packages, as u/iehm suggested. Check this subreddit's wiki for lots of guidance on learning programming and learning Python, links to material, book list, suggested practice and project sources, and lots more. The FAQ section covering common errors is especially useful. Roundup on Research: The Myth of ‘Learning Styles’ Don't limit yourself to one format. Also, don't try to do too many different things at the same time. Above all else, you need to practice. Practice! Practice! Fail often, try again. Break stuff that works, and figure out how, why and where it broke. Don't just copy and use as is code from examples. Experiment. Work on your own small (initially) projects related to your hobbies / interests / side-hustles as soon as possible to apply each bit of learning. When you work on stuff you can be passionate about and where you know what problem you are solving and what good looks like, you are more focused on problem-solving and the coding becomes a means to an end and not an end in itself. You will learn faster this way.
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Reddit
reddit.com › r/learnpython › learning python for data analysis
r/learnpython on Reddit: Learning python for data analysis
February 17, 2025 -

Strange-ish scenario here but I just got hired as an Data Analyst for a company with no experience. The boss knows this and is fine with it, he is a close friend and wants to help me start a profession. He told me to throw some data sets in chat gpt to help me and slowly learn how to use python as I go. Anyone know some good textbooks or online programs I could check out to help expedite this process? I also have no background in python LOL.

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The fastest and most efficient way to learn is Wes McKinney’s Python for Data Analysis, 3rd edition . Just download the notebooks , and start playing with them while reading the book in parallel. It is an extremely good way to ramp up your knowledge at an accelerated pace in this field.
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If it's work from home can you let your boss know I'm also available lol
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Reddit
reddit.com › r/learnpython › need help in learning python for data science and ml
r/learnpython on Reddit: Need help in learning Python for data science and ML
May 27, 2025 -

Hey, can anyone please share best courses and study groups to learn python from scratch. I am looking to move to a career in AI, so need guidance and mentoring. Please help.

Need a mentor.

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The best way to start is by setting clear learning goals instead of picking random courses. Begin with Python basics, then move to data handling (NumPy, pandas), data visualization, and core stats/math. Once that’s solid, get into ML with scikit-learn, then go deeper into model tuning and deep learning (TensorFlow or PyTorch). Choose courses that help you hit these steps one by one, it keeps things focused and way less overwhelming.
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IBM course is there for Python for data science
Find elsewhere
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Reddit
reddit.com › r/learnpython › learning python for data science versus general
r/learnpython on Reddit: Learning Python for Data Science versus General
February 23, 2025 -

For context, I'm currently a senior Psychological Sciences student looking to pursue my MS in Data Science. For my last semester I'm taking Introduction to Computing for Engineers and our homework/labs are through zyBooks. Learning different concepts is enjoyable, but actually being given a lab with little to no guidance on what principles to apply is difficult. I'm not anticipating using it in my Masters is any easier but as I understand it from my friend (who is a CS major), python (along with other languages) can be used for web development, building computer applications etc.

I know learning python is a tricky because it all depends on what you're trying to do, so I ask:

How should I approach continuing to learn python given that I intend on using it for data science/analytics and research? Resources/Book recommendations are appreciated :)

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Hey there! I'm in a similar boat as you: I earned my BS in Psychology and will be pursuing a MS in Data Science in the fall. I've been learning python for little over a year now (mainly for fun and general use) but I have utilized the following sources to help learn how to use python for Data Science: DataQuest : It's similar to codecademy, if you've ever used them, but IMO DataQuest does a good job of teaching you basic and intermediate python from the data science/analyst perspective. An Introduction to Statistical Learning with Applications in Python : I purchased this highly recommended book, but it's also available for free on their website. There's a free complementary course on edX which basically follows the book. The book's main purpose is to teach essential tools and methods in statistical modeling and data science. The python version has some datasets and labs for you to practice with. 100 Days of Code: The Complete Python Pro Bootcamp : This is the course I used to start learning the basics of python. I'm not sure how much python you know, but this might not be a bad starting point if you have no experience with it. IMO it does a good job of forcing you to apply what you learn, but you will start off making a lot of games and random stuff. Personally, I completed all of the beginner courses, some of the intermediate courses, and then just skipped to the Data Science section. If you're in the US, you can get access to Udemy courses for free through your public library via Gale or maybe even through your university. Best of luck to you on your journey! EDIT: My only other tip is to put a little bit of time each day into learning python. An hour or two a day will go a long way over time.
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Good morning, First of all, I don't work in psychology. You will need to bring your critical thinking and experience to the answers that follow. Start with the basics, such as Automate boring stuff with Python. If you are working with data you will need to manipulate it, you might need pandas (manipulate data) and matplotlib (visualize data). Ideally, use a Jupyter Notebook to visualize your results. It can be interesting to have interactive graphs with Plotly. Then come the statistics/ML modules: statistics, SciPy or even Scikit-learn At the same time, try to find cases close to yours since there may be libraries more suited to your field of study. Good luck
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Reddit
reddit.com › r/learnpython › python for data science - recommendation for a beginner
r/learnpython on Reddit: python for data science - recommendation for a beginner
January 14, 2024 -

Hello everyone!

I am an Economics student on his way to complete his MSc and I’d like to learn Python applying it to data science (and economics ofc, but in general I’d say data science, hence data management and analysis).

Where do you think I should start? Do you have any advice about which book to rely on/ courses to attend online?

I think I can study Python for like a couple of hours per day more or less.

Thanks!

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I usually find that the most engaging approach to learn is to build something you are excited about. Start with something small so that you complete it and have a sense of achievement. There are useful datasets on Kaggle (although you likely won't be doing something novel if you just take an existing dataset). Alternatively you could just do some practice exercises. I built https://bytearena.dev for my girlfriend when she was preparing for Python Data Science interviews. I find exercises better than courses as they actually force you to do something and practice rather than just sitting there passively absorbing some content.
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Hey! My two cents, start with basics - DataCamp or Codecademy got Python for Data Science, pretty solid. Then Python Crash Course by Eric Matthes, good stuff, breaks it down nice. After, consider pandas, numpy, scikit-learn, get a good grip on em. Kaggle for real-life challenges, ain't better way to learn. Happy coding!
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Reddit
reddit.com › r/learnpython › how can i break into data science with just python skills and no formal experience?
r/learnpython on Reddit: How Can I Break into Data Science with Just Python Skills and No Formal Experience?
October 10, 2024 -

Hey all,
I’ve been learning Python and am really interested in breaking into data science, but I don’t have any formal experience in the field. What steps should I take to start a career in data science with just Python skills? Any advice on building a portfolio, getting hands-on experience, or transitioning into a data science role would be super helpful.

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do you know statistics ? linear algebra ? calculus ? do you have at least a bachelors degree ? if the answer to any of those questions is no, then you can not break into data science learn sql, learn statistics, learn excel, learn tableau or power bi and maybe, just may be you can break into data analytics
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When I started getting comfortable with python and programming overall, I took an interest in data science. I backed out fairly quickly after I realised data science is programmed/automated statistics. You need to know advanced statistics and be at home with math. I was not and weren't going to spend time on that so I let it go. Either that or let gpt tell you what you need to do. But you won't learn much using this with "just get to the goal" attitude (not saying you have it but working with AI is a slippery slope) To summarise, you can't do with just python here
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Reddit
reddit.com › r/pythontips › any good resources to learn python for data analytics/science
r/pythontips on Reddit: Any good resources to learn python for data analytics/science
December 26, 2024 -

Hello, im currently a senior at my college as an applied math major. i know tons of programming languages but at the basic level. I've honed my SQL and Excel skills. I know a little pandas but not to the point where i can remember things. any good resources/interactive courses online where i can learn this without having to pay too much money?

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YT is full of wonderful resources for learning Python and R for Data Science. Many videos have a git repo link in the description that you can follow to view code. I recommend using Google Colab for setting up your environment and then playing with the code.
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You can try Python Basic and pyspark on databricks academy. It is data oriented. Not lot of learning materiał but solid foundation.
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Reddit
reddit.com › r/dataanalysis › python for beginner
r/dataanalysis on Reddit: Python for beginner
October 20, 2024 -

Hello everyone

I want to learn the fundamentals of Python as a complete beginner, so I can use it and improve it in Data Analytics. Is there any Udemy course I should get? Would you recommend me anything else?

Thanks everyone in advance

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For general Python https://programming-24.mooc.fi/ For Data Analysis with Python in particular https://dap-21.mooc.fi/ I didn’t do either of them because i came across the courses too late. But i did a lot of other mooc.fi courses and they have consistently been free, high quality up to date courses with exercises, and university grade certification (if you want that).
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Look up 100 days of code ! Super helpful
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Reddit
reddit.com › r/learnpython › i want to get better at python for data science. any advice?
r/learnpython on Reddit: i want to get better at Python for data science. any advice?
January 13, 2025 -

im okay at python, but i want to learn more about pandas without waiting for a sale on Udemy. if anyone can give me any resources or even online courses specifically for pandas that would be amazing

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Putting two youtube resources you may try... https://youtu.be/DkjCaAMBGWM?si=TJieMMKAOYsSJWv9 https://youtube.com/playlist?list=PLeo1K3hjS3uuASpe-1LjfG5f14Bnozjwy&si=mC_vlUIUOPXFL-Cd
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I recently started working through Intro to Statistical Learning in Python and they use pandas heavily. There's a book , labs , video lectures and problem sets with solutions .
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Reddit
reddit.com › r/datascience › best way to become an expert in python for data science?
r/datascience on Reddit: Best way to become an expert in Python for Data Science?
August 31, 2022 -

or How should a beginner study python?

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Use it. A lot..... and use it well........to do data science. Mastering takes dedication and experience.
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Unpopular opinion but you don't actually need to be an 'expert' in Python if you are gonna work in Data Science. An intermediate level of understanding plus some fluidity working with lists, dictionaries, exception handling and functional programming will be enough to keep you covered. Hate to say it and this is coming from someone who loves coding: Focus on being an expert in statistics, business understanding and visualization skills, instead.
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Reddit
reddit.com › r/python › best way to learn data science?
r/Python on Reddit: Best way to learn data science?
December 12, 2014 -

I and a group of my friends want to learn data science and we would like to know the best resources.

I checked out Udacity's Data Science Course, watched the first 20 videos or so and it seemed helpful, working with pandas is great, pandas is useful. Looked at some reviews though and learned that the entire course scratches the surface and doesn't really teach much about real data science.

Checked out Coursera's Intro Data Science course and watched the first 10 videos or so, this was mostly just explaining the field and its subfields. Which is great, I just knew I wouldn't start coding until probably 20 videos in or so. Checked out the reviews for this one too, pretty much the same things were said of this course: scratches the surface, too complex to fast, bad instructor, would be better off learning each subject individually, etc. (one person even said this was the worst course on coursera!)

Reading ThinkStats at the moment and checked the reviews for this one too, they all seem to be good with a couple of bad ones talking about how it is an introduction to pandas rather than an introduction to statistics. Which is fine. ThinkBayes is on our reading list too.

I am wondering what would be the absolute best course of action to learn data science, so that we don't waste any more time.

Would really appreciate some quality advice

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While my official title is not "Data Scientist" (I'm a post doc at a US DOE national lab), about 75% of my day-to-day involves what I would consider data science using numpy,scipy,scikit-image, some pandas, matplotlib, etc... I would suggest finding something you are interested in and doing some "data science" on it. My personal opinion (which is worth what you have paid for it) is that it is best to learn by doing, rather than just reading. The reading and courses will help, but that is only a tiny fraction of it. Things you may be able to do: Analyze stock tick data Find out some information about sports players and their statistics Look at currency market data (there is a lot of historical data for bitcoin readily available for various exchanges) Analyze ebook data (for common words, sentence length, ...) Analyze twitter feeds/trends (similar stuff to ebooks, and you can throw in some info about geospatial location) Look at price data of a product/s as a function of time on something like amazon or newegg (you can learn some simple url scraping with this too) Learn something about your local region with weather data. I'm sure there are more options that others can think of too. Good Luck!
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Here's what I'd recommend. GETTING STARTED WITH DATA SCIENCE If you're interested in learning data science I'd suggest the following: Tools I’d recommend learning R before Python (although Python is an exceptional tool). Here are a few reasons. Many of the hot tech companies in SF, the Valley, and NYC like Google, Apple, FB, LinkedIn, and Twitter are using R for much of their data science (not all of it, but a lot). R is the most common programming language among data scientists. O’Reilly Media just released their 2014 Data Science Salary Survey . I’ll caveat though, that Python came in at a close second. Which leads me to the third reason: R has 2 packages that dramatically streamline the DS workflow: dplyr for data manipulation ggplot2 for data visualization Learning these has several benefits: they streamline your workflow. They speed up your learning process, since they are very easy to use. And perhaps most importantly, they really teach you how to think about analyzing data. GGplot2 has a deep underlying structure to the syntax, based on the Grammar of Graphics theoretical framework. I won’t go into that too much, but suffice it to say, when you learn the ggplot2 syntax, you’re actually learning how to think about data visualization in a very deep way. You’ll eventually understand how to create complex visualizations without much effort. Skill Areas My recommendations are: Learn basic data visualizations first. Start with the essential plots: the scatter plot the bar chart the line chart (But, again I recommend learning these in R’s ggplot2.) The reason I recommend these is The are, hands down, the most common plots. For entry level jobs, you’ll use these every day. They are “foundational” in the sense that when you learn about the underlying structure of these plots, it begins to open up the world of complex data visualizations. As with any discipline, you need to learn the foundations first; this will dramatically speed your progress in the intermediate to advanced stages. You’ll need these plots as “data exploration” tools. Whether you’re finding insights for your business partners or investigating the results of a sophisticated ML algorithm, you’ll likely be exploring your data visually. These plots are your best “data communication” tools. As noted elsewhere in this thread, C-level execs need you to translate your data-driven insights into simple language that can be understood in a 1-hour meeting. Communicating visually with the basic plots will be your best method for communicating to a non-technical audience. Communicating to non-technical audiences is a critical (and rare) auxiliary skill, so if you can learn to do this you will be very highly valued by management. I usually suggest learning these with dummy data (for simplicity) but if you have a simple .csv file, that should work to. Learn data management second (AKA, data wrangling, data munging) After you learn data visualization, I suggest that you “back into” data management. For this, you should find a dataset and learn to reshape it. The core data management skills: subsetting (filtering out rows) selecting columns sorting adding variables aggregating joining You can start learning these here . Again, I recommend learning these in R’s dplyr because dplyr makes these tasks very straight forward. It also teaches you how to think about data wrangling in terms of workflow: the “chaining operator” in dplyr helps you wire these commands together in a way that really matches the analytics workflow. dplyr makes it seamless. Learn machine learning last. ML is sort of like the “data science 301” course vs. the 102 and 103 levels of the data-vis and data manipulation stuff I outlined above. Here, I’ll just give book recos: An Introduction to Statistical Learning . This is a highly regarded introduction Machine Learning with R I’ve also heard that there is some foundational ML information in R in Action , though I haven’t read it myself. After you get these foundations, then you can move on to specialize in a particular area. OTHER RESOURCES: Data Visualization Nathan Yao of Flowing Data is great. His blog shows excellent data visualization examples. Also, I highly recommend his books. In particular, Data Points . Data Points will help you learn how to think about visualization. The book ggplot2 by Hadley Wickham. This is a great resource (though a little outdated, as Hadley has updated the ggplot package). I also really like Randal Olson’s work (AKA, /u/rhiever ). He creates some great data visualizations that can serve as inspiration as you start learning. TL;DR I'd recommend learning R for data science before Python. Learn data visualization first (with R's ggplot2), using simple data or dummy data. Then find a more complicated dataset. Learn data manipulation second (with R's dplyr), and practice data manipulation on your more complex data. Learn machine learning last.
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Reddit
reddit.com › r/learnpython › course recommendation for python for data science
r/learnpython on Reddit: Course recommendation for Python for Data Science
May 6, 2024 -

Hi,

I am a R user hoping to pick up Python, especially the data science relevant libraries such as NumPy, Pandas, Scikit-Learn, etc. I have a good background in statistics (and am comfortable using R for running models). I have in the past completed till day 35, the Udemy course by Angela Yu. I loved her teaching and the course, but felt it was focused way too much on front-end development (after the the great initial intro till day 30), so discontinued it. Is there any such course (paid or free) that you would recommend for the data science libraries in Python? I checked the course by Jose Portilla (https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/?couponCode=KEEPLEARNING), but the latest reviews all seem to say that it is outdated (it was last updated 4 years back). While I am open to theory based courses, I would prefer project based hands-on courses. Thanks!

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That course is severely outdated and uses a very old unstable (<1.x.y) of scikit-learn in the latter part of the course and therefore has a lot of depreciated code as scikit-learn went through a number of refinements in its API for version 1.0.0 which was released after this course. Jose Portilla has a newer course on Udemy which is essentially the same course but an updated version and uses a newer version of scikit-learn (>1.x.y) which has a more stable API: Python for Machine Learning and Data Science by Jose Portilla (Udemy) . I'm not sure why Udemy recommends the old version over the newer version. I recommend supplementing the course with the textbook Python and Data Analysis by Wes McKinney (Open Access) , the founder of the Pandas Library.
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since you're coming from R, I totally get the transition challenge! for learning python data science libs, i actually built preswald while teaching myself these tools and found project-based learning super helpful. here's what worked for me: start with pandas - its actually pretty similar to R's dataframes. the 10 minutes to pandas tutorial on their website is gold then numpy (its like the backbone of everything). dont need to go too deep, just basics for ML stuff scikit-learn has amazing documentation with practical examples instead of following courses, id recommend picking a small project you care about - maybe something you've done in R - and rebuild it in python. you'll learn way faster that way! if you want a quick way to experiment, you could try preswald (what i built) - its basically a way to write python/sql and instantly create data apps. might be nice for comparing your R and python implementations side by side but honestly whatever tool you use, just build stuff! courses are good but nothing beats actual projects for learning imo good luck! lmk if you need any other tips for the R -> python journey 🙂
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Reddit
reddit.com › r/learnpython › [deleted by user]
I want to learn python for data analysis
September 19, 2024 - A good structured way to get into it is a course like Intro to Python for Data Science, which covers the essentials and gives you hands-on experience. Once you're comfortable, learning matplotlib or seaborn for data visualization would be super useful too.
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Reddit
reddit.com › r/learnpython › how can i effectively learn python for data analysis as a complete beginner?
r/learnpython on Reddit: How can I effectively learn Python for data analysis as a complete beginner?
February 17, 2026 -

Hi everyone!

I’m completely new to Python and I'm particularly interested in using it for data analysis. I've read that Python is a powerful tool for this field, but I’m unsure where to start.

Could anyone recommend specific resources or beginner-friendly projects that focus on data analysis?
What libraries or frameworks should I prioritize learning first? I want to build a solid foundation, so any advice on how to structure my learning path would be greatly appreciated.

Thank you!

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First , start at the beginning. Download and install it. Then try print("Hello World") Then check out the wiki on the right.
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I've taught data analysis to thousands of beginners, so here's the path that works best: Start with pandas, not theory. Grab a CSV dataset you actually care about (your Spotify history, a Kaggle dataset about movies, whatever) and learn pandas by exploring it. df.head(), df.describe(), df.groupby() — these three will carry you surprisingly far. Learn visualization early. matplotlib and seaborn make your data tangible. Being able to see patterns keeps you motivated way more than reading documentation. Skip machine learning for now. Seriously. 80% of real-world data analysis is cleaning, filtering, and summarizing data — not building models. Get comfortable with pandas + basic stats first. A good free starting point: the "Python for Data Analysis" book by Wes McKinney (pandas creator). It's practical and skips the fluff. Once you can load a dataset and answer 3 questions about it on your own, you're ready for more advanced stuff.
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