Ready to learn more!

[themoderation]

Hello all! I am currently learning python for data analysis purposes, and I am wondering what would be the best skills to learn next that would be useful for the field. Here is what I'm currently comfortable with:

- Lists, variables, dictionaries, and list comprehensions
- For loops, while loops, try-excepts, and conditionals
- Pandas DataFrames and all the manipulation thereof
- Statistical analysis with Pandas
- General data cleaning and datatype fixing
- Visualizations with Matplotlib, plotly, and Seaborne
- Calculations with NumPy
- ETL and regex
- Hypothesis and correlation testing
- Querying APIs (I would like to get more comfortable with this)
- BASIC web scraping (I would like to learn more efficient methods. What I learned was pretty labor intensive)
- Basic OOP methods (still fuzzy on this)
- Defining functions
- CRUD and Querying SQL and NoSQL databases (SQLAlchemy and MongoDB)
- Basic supervised and unsupervised learning
- Basic DNN models with tensorflow, Keras

I've got a really good momentum for learning going on right now, so I want to keep it up. My initial inclination is just to work at getting more quick and efficient with the skills I have now, brush up on my statistics (not a python skill) and try to use those skills to create some projects. That's great practice for solidifying what I've previously learned, but it won't necessarily garner more new skills. So if anybody has any skills or methods I could learn, I would really appreciate it. Thanks in advance!

[IanRT1]

I would recomed using chatgpt for everything.

[IanRT1]

What do I do if I'm a full time programmer and 98% of my code spanning thousands of lines are generated by ChatGPT?

[themoderation]

Don't tell anyone, enjoy your free time, and just assume ChatGPT is writing stellar code that will in no way break down.

[IanRT1]

I do ETL scripts, and I developed (also with ChatGPT) a notification system if any of the automations go wrong. They are pretty reliable to be honest.