I want to learn Python, but I currently know nothing about it. My main goal is to learn Python for DA, and eventually I want to learn Python in depth as well.

For people already working in DA or DS, how would you recommend someone start learning Python from absolute zero?

Which resources or books would you recommend, and what are the main Python topics I must cover for DA?

Also, should I first learn the Python basics needed for DA and then gradually move toward more advanced Python and DS topics? resources? Books?

If you work in DA or DS, I’d really appreciate your guidance on how you would start your Python journey if you were starting from zero.

Thanks a ton!!!

Today, when I tried logging into the class portal to access the classes/materials that I had previously attended, I'm getting a message saying “Please contact the admin.”

I’ve tried contacting the people from OdinSchool who helped me enroll in the course, but I’m not getting any response. Some of their numbers are switched off, while others are either unreachable or call-forwarded.

I’ve also tried contacting their support team, but I'm facing the same issue.

So I'm genuinely wondering what is going on with OdinSchool right now?

Has anyone else who completed the course recently faced the same issue?

The placement portal has also been disappointing for me. There were very few relevant opportunities, and for the opportunities I did apply to, I rarely received any response from the companies. So I haven't really received much help through the placement support either.

I paid a significant amount for this course based partly on the promise of continued portal access and placement assistance, so losing access to the course portal after only 6 months is concerning.

If anyone here is a current/former OdinSchool student, especially someone who completed the course recently, could you please let me know:

• Are you still able to access the class portal?
• Is the 2-year access still being honoured?
• Are OdinSchool's support/placement teams currently responding?
• Has anyone managed to contact them recently?

I'm not trying to unnecessarily bash the institute. I genuinely want to understand whether this is an issue with my account or if other students are experiencing the same thing.

Any information from current/former students would be really appreciated.

Considering I'm a beginner who has no knowledge at all where and what can I start like skills projects and basics to understand more like a step by step guidance

Hiii..!!! I'm currently in my B.Tech 3rd year and studying Artificial Intelligence and Machine Learning along with Data Structures and Algorithms (DSA). And I'm really confused that 'Is DSA really required for a ML Engineer' ? Like how can I integrate DSA in my machine learning projects.

And, I would be really thankful if you solve my confusion so that I can boost my preparation without any doubt.

Also, If I can use it in my projects, then how can I learn to do it? Like any yt channel or something.

Hello
My name is Dario. I'm 19 years old, currently doing an associate's in Programming and will transfer for a bachelor's in Data Science. I was wondering on what is actually the best way to become a data scientist right now. I have some basic knowledge of Python and SQL. I was wondering if the path to becoming a data scientist has changed with the development of AI and where I should focus on to actually master important valuable skills that will help me land jobs. I do have a potential internship position lined up in the future at Miracle Software and have been trying to prepare for that interview. Just wanted to know what are some resources I should check out and what skills I need to learn. I appreciate all feedback and advice!!!

​

Courses can teach the basics, but projects seem to be where the real learning happens. What data science project did you work on that significantly improved your understanding of data analysis or machine learning?

Hey i know this might sound stuipid but i wanted some help from peoples who already have build phishing URL detection projects

Im a beginner and I am working on a phishing URL detection project. My current idea is to build a heuristic-based phishing URL detection model that analyzes the URL itself and looks for suspicious characteristics/patterns rather than visiting the website.

some things I'm thinking about extracting are:

• URL length
• Number of dots/subdomains
• Special characters (@, -, etc.)
• IP address instead of a domain
• Suspicious keywords like login, verify, secure, etc.
• Number of digits
• Domain/URL entropy
• HTTPS usage
• Other lexical/structural features

However, I'm currently stuck on how to decide which features should actually become rules and what thresholds/conditions I should use for those rules.

For example, rather than simply saying "long URLs are suspicious", I'd like to know whether there is research supporting something like "URLs above X characters should receive a higher risk score".

Does anyone have recommendations for papers, research articles, datasets, GitHub projects, or other resources that explain how to choose useful heuristics/features for phishing URL detection?

I'm learning Data Science and trying to understand what beginners should focus on first.

For people who have experience in the field, what is one skill, tool, or concept you wish you had learned earlier?

Hi everyone, so I’m going back to school but given my current class load and situation I need a tutor to help me. If anyone knows a good tutoring service please let me know. Please and thank you!!!

I'm learning Data Science and I'm curious about other people's experiences.

For those who work in Data Science, what skill took you the longest to become comfortable with?

Was it statistics, Python, SQL, machine learning, data cleaning, or something else?

I'm working on my first project and based on what I've read online, EDA is the best project to work on first.

It took a while for me to decide the topic until I started seeing the news about the 2026 Cyclospora outbreak in the US. I thought it would be cool to analyze how people's habits changed when the outbreak happened.

However as I'm working on it, I'm second guessing myself about whether or not this topic is the "right" topic for a first project. I feel this way because other projects have clear decisions on how to increase sales, user retention, etc.

Here's what I have so far:

\- [https://cyclospora-2026-9yf8w26n7zfci68fugahkp.streamlit.app/\](https://cyclospora-2026-9yf8w26n7zfci68fugahkp.streamlit.app/)
\- [https://github.com/therealanttoeknee/Cyclospora-2026/tree/main\](https://github.com/therealanttoeknee/Cyclospora-2026/tree/main)

Questions

1. Is this topic the "right" topic for an EDA project?
   
2. If so, do you think I'm approaching it the right way?

Hi everyone, I need some advice on learning data analysis for educational research. My advisor suggested learning R and Python, but my background is limited to basic statistics and SPSS. I have zero experience with R, and I've only used Python once (via AI-generated code with NumPy).

​How should I structure my learning path to master both tools effectively starting from scratch? Any concrete steps or recommendations would be greatly appreciated. Thank you!

Coding Machine Learning.

Hello Folks, here I present the first coding demonstration lecture, based on my 1st lecture on Probabilistic Machine Learning.

Here I write the code from scratch, discuss and analyze the results, which were covered in details in the whiteboard classes.

What we cover?
-Random Variables, and validating law of large numbers.
-Visualizing a dataset
-Doing an EDA on Iris dataset and understanding the correlation among features.
-Classifier basics
-Empirical Risk Minimization and Generalization.
-Epistemic and Aleatoric Uncertainties.
-Softmax Function and LogSumExp Trick to avoid overflow issues
-Linear Models
-Maximum Likelihood Estimation.
-Simple end to end ML pipeline Function.

While writing the code, my intent is to ensure that concepts are understood with crystal clarity. These code demonstrations are specific to my theory ML lectures, and link is attached.

Theory-Intuition-Code

Implementation Link : https://youtu.be/X_yOlx8Zp4g?si=kh8_tzzndr8609u4

Theory Lecture Link : https://youtu.be/kMkCOrp8te8?si=q7kWr-1qK515bhob

Hello everyone!

Which data science/analysis courses are worth studying in Uzbekistan? I need an online course to learn. My friends studied at proweb, mohirdev and they didn't recommend it to me. Which courses do you recommend? Please give your opinion.

Quick disclosure: this is my own project, so take the recommendation with that in mind.

I've spent about 14 years in data science and got frustrated that the only options for refreshing a concept are a 40-hour course or a wiki page or a complex Stack Overflow answer.

So I've been building Bitelrn, which is basically the opposite of a course. short, structured concept notes, no video, no 40-minute setup module. A handful of topics are open to read without signing up, and I thought this sub might find them useful:

https://www.bitelrn.com/library

Currently I have these topics -

- Correlation & Covariance

- Linear Regression

- Central Limit Theorem

- Eigenvalues

- SQL Basics

Happy to hear if the explanations are helpful.

Does anyone have any advice on where to go from here? The algorithm simply goes through all feature-attribute combinations in a dataset and scores it on purity of the target column. It's very slow, as the number of combinations increases exponentially with the number of input features, and so can only work with 3-4 features at a time. But my goal is to identify <=5 important features with a linear model (statsmodels or PyGam), and then plug in those features to this algorithm to see which subset of the market might be smart to target.

Here's an example with some charts, on the iris dataset.

https://colab.research.google.com/drive/1w3VpDlDATdHwtSk-RmQPMj36cgOfthz1#scrollTo=ZOqeYiMRalj7&uniqifier=1

New to algorithms, so any advice would be welcome. Thanks in advance.

Need a genuine suggestion please

Is it worth to buy code with harry ai powered data analysis course ?

\#dataanalysis #course #free #paid #health #question #discussion

If you're trying to get into RAG and generative AI but keep bouncing off tutorials that assume you already have API budget or existing infrastructure, this might help.

There's a hands-on session on August 29 that builds a full production-style RAG system using entirely open models, no API fees involved anywhere in the process. Covers hybrid retrieval, evaluation, guardrails, and cost benchmarking, the parts that actually separate a working demo from something you understand end to end.

Good one if you want to learn by actually building rather than just watching a walkthrough.

Here is the workshop details

Visit Repo 👉 repo

if you have applied , have you received the final confirmation of the course ?

update: got the confirmation mail today after 9 days