I am planning to learn data analytics and i got overwhelmed by all the information at the internet so I am asking here how much statistics do you need and what are those you actually have to master to become a data analyst? Also need some advice or mentorship if any want to help.

Say I have a very large dataset of signals that I’m attempting to perform some downstream task on (classification, for instance). My datastream is huge and can’t possibly be held or computed on in memory, so I want to train a model that compresses my data and then performs the downstream task on the compressed data. I would like to compress as much as possible while still maintaining respectable task accuracy. How should I go about this? If inference on compressed data is a well studied topic, could you please point me to some relevant resources? Thanks!

I’ve been job hunting since graduating last year with no luck. I’m self-supporting and nearly out of funds, even after selling personal items. I’m now exploring freelancing to earn whatever I can to cover essentials until I land a full-time role. I’ve applied to some freelance gigs, but many were scams or required strong software engineering skills, which isn’t my background.

My core skills are in Python and SQL, and I have project work to show. Here’s a quick snapshot of my skill set:

Tools: AWS, Outlook, Excel, Visio, Access, Tableau, Jupyter Notebook, SAP ERP, Colab
SQL: Queries, DB design, triggers, procedures, transactions, locks, indexing, CTEs, window functions
Python: APIs, testing, ML, OOP, analytics, ETL, stats, visualization
Java: OOP, JavaFX GUI, file I/O

Open to any opportunities, freelance or part-time that can help me get by.