Professional data scientist and GenAI builder here. Code writing, data analytics, machine learning, prompt engineering, artificial intelligence, chatbots, etc. Degrees in engineering and statistics also.
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Use free (YouTube, Google) or cheap sites (Udemy, Code Camp) and start with highly rated intro/crash courses (day to week) before you invest too much time then move to longer courses (weeks to months).
Learn some SQL, Python, and either Tableau, Looker, or Excel (for visualization). That triple combo of databases, code, and visualization is a gateway to analytics internships and careers. The courses often have exercises and datasets.
To step up to data science, I would start first with the Google developer crash course on ML which is less intensive and has great illustrations. It starts to drive home concepts. Machine Learning | Google for Developers. But it’s just for play. The training on Kaggle is excellent also and they have many public datasets to work with Learn Python, Data Viz, Pandas & More | Tutorials | Kaggle
when you are farther along…there are longer boot camp courses that mix all of this plus statistics, and have you code-along hands-on to build things (Udemy 2024 Data Science Bootcamp or equivalent). These will give enough confidence and examples to let someone tackle some simple personal projects which is key. Another option for something more advanced would be the excellent machine learning specialization course from Stanford which is again beginner friendly.
As soon as you are comfortable, begin with small personal projects. This the best way to learn both how to code and do analytics. And learn GitHub which is a version control system but also allows you to share and display your projects with potential schools/employers.
I’ll have to look at Gen AI more for easy intro courses
In high school, any CS courses or statistics will help. It will show interest and aptitude for colleges. (However, I would not take stats in place of precalc or calc. Only in addition)
But, if you have a few years, learning on the side and completing personal projects will be things that can get you internships and also show colleges what you can do.