u/Ok_Explanation2786

Currently a CS major at another UC. Got admitted to UC Berkeley for Applied Math and UCSD for CSE. Goal is a tech job right out of undergrad, not planning on grad school.

I want to go to Berkeley for the opportunities and Bay Area access, but the tradeoff is leaving CS. My plan would be to double major (or at least pivot heavily) into Data Science and stack CS-adjacent coursework to stay close to the field. Already locked in a research genomic ML internship at Berkeley the summer before I’d transfer, so I’d have a head start on the network and a relevant project on the resume.

Regarding what niche I want to do in tech, I am open to each side from ai/ml, data, to swe,cloud ,and hardware focused. I have currently focused on more of the AI/Ml projects with data science work and some autnomous driving related work but I am early enough in my career to pivot in any field of tech. Do not want to do front end or full stack.

I’ve spent time on the Berkeley campus and mapped out how the course plan would work. I’ve also talked to people at both schools, surprisingly, the UCSD students told me they’d pick Cal if they were in my position, even with the major mismatch.

So the question is, what do I choose a more ideal major or the more ideal school with way better connections.

Currently a CS major at another UC. Got admitted to UC Berkeley for Applied Math and UCSD for CSE. Goal is a tech job right out of undergrad, not planning on grad school.

I want to go to Berkeley for the opportunities and Bay Area access, but the tradeoff is leaving CS. My plan would be to double major (or at least pivot heavily) into Data Science and stack CS-adjacent coursework to stay close to the field. Already locked in a research genomic ML internship at Berkeley the summer before I’d transfer, so I’d have a head start on the network and a relevant project on the resume.

Regarding what niche I want to do in tech, I am open to each side from ai/ml, data, to swe,cloud ,and hardware focused. I have currently focused on more of the AI/Ml projects with data science work and some autnomous driving related work but I am early enough in my career to pivot in any field of tech. Do not want to do front end or full stack.

I’ve spent time on the Berkeley campus and mapped out how the course plan would work. I’ve also talked to people at both schools, surprisingly, the UCSD students told me they’d pick Cal if they were in my position, even with the major mismatch.

So the question is, what do I choose a more ideal major or the more ideal school with way better connections.

Currently a CS major at another UC. Got admitted to UC Berkeley for Applied Math and UCSD for Computer engineering. Goal is a tech job right out of undergrad, not planning on grad school.

I want to go to Berkeley for the opportunities and Bay Area access, but the tradeoff is leaving CS. My plan would be to double major (or at least pivot heavily) into Data Science and stack CS-adjacent coursework to stay close to the field. Already locked in a research genomic ML internship at Berkeley the summer before I’d transfer, so I’d have a head start on the network and a relevant project on the resume.

Regarding what niche I want to do in tech, I am open to each side from ai/ml, data, to swe,cloud ,and hardware focused. I have currently focused on more of the AI/Ml projects with data science work and some autnomous driving related work but I am early enough in my career to pivot in any field of tech. Do not want to do front end or full stack.

I’ve spent time on the Berkeley campus and mapped out how the course plan would work. I’ve also talked to people at both schools, surprisingly, the UCSD students told me they’d pick Cal if they were in my position, even with the major mismatch.

So the question is, what do I choose a more ideal major or the more ideal school with way better connections.

Currently a CS major at another UC. Got admitted to UC Berkeley for Applied Math and UCSD for CSE. Goal is a tech job right out of undergrad, not planning on grad school.

I want to go to Berkeley for the opportunities and Bay Area access, but the tradeoff is leaving CS. My plan would be to double major (or at least pivot heavily) into Data Science and stack CS-adjacent coursework to stay close to the field. Already locked in a research genomic ML internship at Berkeley the summer before I’d transfer, so I’d have a head start on the network and a relevant project on the resume.

Regarding what niche I want to do in tech, I am open to each side from ai/ml, data, to swe,cloud ,and hardware focused. I have currently focused on more of the AI/Ml projects with data science work and some autnomous driving related work but I am early enough in my career to pivot in any field of tech. Do not want to do front end or full stack.

I’ve spent time on the Berkeley campus and mapped out how the course plan would work. I’ve also talked to people at both schools, surprisingly, the UCSD students told me they’d pick Cal if they were in my position, even with the major mismatch.

So the question is, what do I choose a more ideal major or the more ideal school with way better connections.