Hi all, looking for some advice. Ex big4 auditor now a Snr Analyst in Corporate FP&A in the Bay Area (somewhat intelligent although wasn't a fan of maths and programming classes in high school/college - never destined for the IB big$s) Now at the point where learning some data science skills would be beneficial for my development and overall skillset.
Are there any recommendations for particular courses out there that anyone has done for learning Python (and/or SQL) from having zero background/experience in the subject matter (for context I would say my excel skills are moderate, can obviously model, although don't really use VBA or Macros in my day to day).
Any suggestions would be most appreciated!
I'm also a CPA who has picked up Python and has utilized it a decent amount at my clients. My answer is not going to be what you're hoping for, because it's not an elegant solution, but the way that I learned Python was by thinking through manual processes at my clients, breaking down the process into smaller steps (i.e. first I load the data table from file X, then I need to run an INDEX(MATCH) to combine the information with file Y, etc.), and then googling/youtubing to figure out what Python function could help me do that.
Unfortunately, there's no Leila Gharani for Python for CPAs/Finance Professionals, so it was a painstaking process that took a long time for me to pick up because I had 0 CS background or anyone to help me (thank god for pandemic lockdown boredom, I guess), but after you do create a few scripts, you'll realize that it's basically like financial analysis in Excel on steroids in that there's a few functions you use over and over again. The Python language is so much faster and efficient, however, that it makes your life a breeze once you write the script. There's still work to do after you write the program, because you'll encounter errors/changes in data that you need to clean in subsequent months, but that's typically easier to handle than writing everything from scratch.
Here's the steps I would take:
1. Learn the basics of Python (i.e. what loops are, how variables work, how to run your code, the basic syntax, etc.). There's countless free video courses on Youtube that will help you do this
2. Some hardcore CS people might disagree with me here, but learn how Jupyter Notebook works. Similar to what I mentioned about breaking things down into smaller, subtasks to get to your end goal, I found the GUI of Jupyter Notebook much less intimidating than other IDEs for writing/testing my code, and also documenting what my goal was/how it fits into the rest of the script.
3. This is where you'll spend the most time: learn how to use Pandas and Numpy extensively. I know there are some really cool packages that do stats/machine learning, but I have yet to see much use for them thus far in corp fin/accounting work. Typically what I'm doing is automating tedious/time-consuming month-end close report creation so I can send the final analysis to my Manager that only knows Excel. If you know how to ETL data really well into Pandas dataframes and then can use Numpy to do your calculations/analysis, you'll be able to cut down literally hours of manual calculating and consolidating every month.
4. Practice. Just watching youtube videos and whatnot won't help you learn a whole lot. Again, take a repetitive process you do every month that takes a long time, break it into steps, and see if you can write a program that will replicate a prior period's results to see if your code works correctly. You'll run into roadblocks, but googling for whatever hurdle you're facing will likely bring up a stackoverflow question with someone asking the same thing. I can't tell you how much code I've copy-pasted from stackoverflow, with some minor edits for my needs, to solve my problems.
Quick question for you, but I noticed you're in FP&A. What all is your company using Python for? Typically, I see people asking for SQL, so I'm always curious to see what FP&A groups want Python knowledge for so I can build my skill-set accordingly and beyond just process improvement.
Leetcode. Plenty of people have gone through zero coding experience to software engineer/data scientist through it. I guess in terms of data science skills there’s a bit more statistics involved so maybe learn some basic probability/stats but in terms of coding, definitely leetcode
Thanks Lester, Rentmoney!
Lester, in response to your qu (my time to say sorry for the vagueness), but it’s more me trying to upskill/future proof myself rather than there being specific company/team initiatives at play - apart from a desire at the top to be more “data driven” (I have a hard time believing those at the top really know what that means/is supposed to look like). I think there’s some low hanging fruit with generic recurring task automation but beyond that it will be more experimentation once I have the skills
https://www.wallstreetoasis.com/machine-learning-package-overview
The corporate finance institute python course was helpful for me but for more advance I would try datacamp
Currently moving from FP&A/strategic finance at one start-up to another, previously came from IB, at current job we only use excel (and a separate team handles data analysis) but learning SQL for the next job as we use jedox tables and SQL instead of excel - expect to mostly learn on the job but am doing some prep courses on sqlzoo
I used hackerrank.com a lot when I was starting out. Once you get the basics, just let your projects guide you. Also, learn pandas, it's a game changer, and will make it so you can automate a teams work with a single script.
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