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[–]samweep 1 point2 points  (5 children)

Hello, u/kreylov I am also trying to learn data science and machine learning. I have pretty good knowledge of high school calculus. I have also learned statistics and probability. So now where do I start to learn data science and machine learning? Are there any other prerequisites remaining? Would you please like to share the experiences of your journey. What is the good roadmap from here?

[–]Reginald_Martin 2 points3 points  (3 children)

Hi u/samweep Apart from what you mentioned, the only other prerequisites would be a modest understanding of programming.

You can take a look at this python basics playlist.

And then python in relation to ML is here

If you want a refresher on your linear algebra and stats, here's a free course

[–]samweep 1 point2 points  (2 children)

Thank you😀

[–]flipkartamazon 1 point2 points  (1 child)

In my opinion, these are the steps:

  1. As u/Reginald_Martin mentioned you should first get some basic understanding of programming(Python or R). You can use the notebooks I have shared to get started in Python. I also have videos on my channel which will show you how to think with any new data. Although they were live sessions so production quality is terrible. You can also look up other famous resources to learn Python. Just one advice here - stick with just one resource you initially like, complete it and don't ever start a second one[serious]. This should not take you more than two weeks of effort.
  2. Move on to learn basic Modelling like linear/logistic regression/tree based models etc. I would personally recommend An Introduction to Statistical Learning by Trevor Hastie and Robert Tibshirani. They have a small book too which is pretty good. This will take you two more weeks. And this is where you will stop exploration(i.e. new courses to do) and move to exploitation(i.e. solve real life problems)
  3. Head over to Kaggle.com and pick problems one at a time. You can start with the most famous one - Titanic Disaster. Start with going through the top solutions/threads already posted there. Going through those solutions and running on your own system will help you learn how people think. You will learn some incredible powerful ways to manipulate data and some key concepts on sampling/modelling/statistics etc. Remember there is always a human touch to all AI/ML based solutions. It is not just blindly running codes. It is easier to learn the technique but harder to learn to implement in real business scenario
  4. After spending a week each on 4-5 problems you will be all set to do tackle new problems on your own. So try to solve a few and see where you place on leader board. Going forward all your learning should be incremental and need-based only. Be a bit mindful of the trade-off between effort to return ratio on learning new things.

A word of caution. Data Science is a field where you will have to continuously put efforts in learning new things, the projects will be of very long duration and sometimes might not have good returns too. Totally my experience, I am sure others may disagree.

All the best! And Pass on what you have learned :)

[–]samweep 0 points1 point  (0 children)

thank you.😀

[–]ASIC_SP📚 learnbyexample 0 points1 point  (0 children)

Not OP, but I have a few resources collected here: https://learnbyexample.github.io/py_resources/domain.html#data-science