Welcome to the entering & transitioning topic for this week! Any queries regarding beginning work in data science, studying, or making the switch should be directed in this thread. Subjects covered include:
Educational materials (such as books, guides, and videos)
Conventional education, such as colleges, degrees, and electives
alternative learning (such as boot camps and online courses)
Questions about career prospects, applications, resumes, and applying for jobs
Simple inquiries (such as where to begin and what comes next)
Check out our wiki’s FAQ and Resources sections while you wait for responses from the community. Additionally, you can look for solutions in previous weekly threads.
I’m in the process of selecting electives for my degree, and I’m torn between three different paths. I’ve done my research and understand the differences in focus and skill sets, but I’d love some real-world advice from those with experience in the industry. With the job market constantly evolving, I want to ensure I’m making the best choice for future opportunities.
Path 1:
Artificial Intelligence (AI Specialist)
Advanced Data Analysis
Managerial Economics and Corporate Finance and Investment
Path 2:
Production Engineering, Automation, and Robotics
Data Engineering
AI or Advanced Data Analysis (leaning towards AI but if you advice for the choice between these two would be much appreciated)
Path 3:
Artificial Intelligence (AI Specialist)
Advanced Data Analysis
Data Engineering
My goal is to build a strong career foundation that’s future-proof and aligned with emerging trends in tech.
Given your experience in the field, which path do you think offers the best balance of skills and career opportunities for the long term? Any insights on how these fields are evolving would be incredibly helpful.
I’m having a bit of a crisis over what MS degree to pursue (if any).
I have a BS in Applied Mathematics and over 5 years of experience in Analytics. There’s this MS DS program near me that has a good curriculum, but it’s not a top school. I also know that data science degrees aren’t always viewed the best, but I’m thinking it might be fine since I have a STEM undergrad degree and years of experience. I’ve also considered statistics/applied statistics programs, but I took multiple graduate-level statistics courses during my undergrad, so I really don’t feel like I’ll be gaining that much by studying statistics. My work experience tells me that advanced statistical knowledge really isn’t that applicable for day-to-day analytics/DS work. I’m more interested in ML/AI.
Don’t know what to do. I’m also considering not even getting a graduate degree at this point. I guess I’m mostly just freaked out by how the broader market perceives degrees in data science. Ugh.
Hey everyone! I’m thinking about applying to CS/ML PhDs
Here’s my background. I’m currently finishing my bachelor’s in Economics, where I focused on quantitative methods. In terms of relevant coursework, I’ve taken Calculus, ODEs, 5 Statistics and Econometrics courses, Intro to AI, Machine Learning, Fundamentals of Data Science, Deep Learning for NLP, and Operations Research. I’m also taking Real Analysis later this year.
I’ve done two undergraduate research projects: one in computational economics (numerical methods for finding general equilibria) and one in NLP applied to finance. I’m writing my thesis in quantitative finance. I have one publication in ML as a coauthor, thanks to my time as a research assistant in an ML lab at my university. I’ve also been working in finance for the last year as a data scientist.
I really enjoyed doing research in ML, especially in NLP, so I’ve been considering applying for a PhD in CS or Statistics, with the goal of working as a research scientist or engineer, and perhaps going into academia later on. I realize I have a few weaknesses, namely the lack of CS courses. I could also probably benefit from more math coursework.
Any tips on how I can maximize my chances of getting into a program? I’m open to spending a few months addressing gaps in my background by self-studying and/or taking one or two more classes at university.
Any advice for learning leetcode as a tech data scientist that writes code every day but never learned DSA techniques? Any good textbooks to cover what I should know? I can do some easy problems but oftentimes find myself struggling for a while on a problem only to find out that there’s a specific data structure or algorithm that I should have known about to solve it. Thanks!
I am thinking about transitioning into data science master from a bachelor physics degree.
A little background on my situation, I have finished my bachelors degree in Applied Physics, and I am thinking in continuing into a master in Data science. Reasons for this change is that I think it is an interesting field with a lot of opportunities, in addition I feel a bit burnt out from doing Physics and I don’t see myself doing this forever.
Are there people here with experience in a similar switch between these field, and what did you think of this switch? Was it a difficult transition? Is there a skill or some knowledge that you were lacking when you made this switch, compared to your peers? Did you also have some advantages?