u/Ok-Significance285

Hey everyone, I'm in a situation where I need to make my final university decision and I'm genuinely struggling. The deadline has already passed and I've accepted multiple schools but I need to commit to one. I've done a ton of research but I want real perspectives from people who've actually been in this situation before I make the most important decision of my life.

My situation:

I've been accepted to and already accepted offers at:

UCSB Statistics & Data Science (B.S.)

SFSU Computer Science (B.S.)

Cal State Fullerton CS + Cybersecurity Concentration

I'm a transfer student so only 2 years at whichever school I choose. All three are potentially fully funded including housing so cost is not a factor at all.

I also have waitlists at UCSD CS and UC Davis CS but I need to make my decision based on guaranteed acceptances.

I need to pick ONE and commit. That's where I need your help.

My background:

Currently in the Bay Area

Strong in math and analytical thinking

No strong preference yet for a specific career, still exploring

My career goals honest answer: I don't fully know yet

I'm being honest here, I'm in 2026 and the tech landscape is changing so fast that I want to keep my options open. I haven't locked into one specific career path yet and I plan to do more research over the next year to figure out what direction fits me best.

What I do know:

I want to work in tech in some capacity

I want a high salary and strong job security

I want to be working with AI in some way whether building it, analyzing it, or applying it

I am not very interested in traditional Software Engineering the reason being that AI is automating a significant portion of entry level coding jobs in 2026 and I've seen many fresh SWE graduates struggling to find work. It feels like a risky path for someone graduating in 2028

Beyond that I'm open to recommendations from people with real experience

Research I've already done:

I've gone through real job postings at OpenAI, Google, and Anthropic and found:

OpenAI's Applied AI Engineer role ($230K–$385K) requires strong Python, ML product experience, model evaluation, and prompt engineering does NOT specifically require a CS degree

OpenAI's Applied Data Scientist role ($290K–$441K) names Statistics as the first accepted degree before CS

OpenAI has 20+ Data Scientist and AI roles beyond pure engineering

Google's Student Researcher program explicitly names Statistics as a primary accepted degree alongside CS

For pure engineering roles SWE, AI Systems, Android infrastructure CS clearly has an advantage

For AI and data science roles specifically, Stats & DS is equally or more competitive than CS

What I'm torn between:

UCSB Stats & DS:

UC brand recognized by top tech companies and passes resume screening more easily

Statistics degree = deep math foundation, strong understanding of how AI models actually work at a mathematical level

Matches what OpenAI and Google data science and AI postings specifically ask for

Santa Barbara is 5 hours from Bay Area, slightly harder internship access

Need to self-study Python seriously since degree is math-heavy not coding-heavy

Fewer backup career options if primary path doesn't work out

SFSU CS:

San Francisco location Bay Area tech companies literally next door, easier internship access

Stronger coding foundation from day one

More flexible opens more career doors including cybersecurity, DevOps, data engineering

Weaker brand at top tech companies compared to UC schools

More generic degree competing against thousands of CS graduates every year

Weaker math and statistics foundation for AI and ML understanding specifically

Cal State Fullerton CS + Cybersecurity:

Cybersecurity concentration is genuinely in demand

Weakest brand of the three for top tech company hiring

Southern California location further from Bay Area tech scene

Good backup option but not my first choice

My specific questions for you:

Given that I'm genuinely unsure about my exact career path, which degree and school gives me the most flexibility and best long term options in tech in 2026?

For anyone working in tech right now, what careers do you think are most future-proof and in demand for someone graduating in 2028? I'm especially interested in roles that work WITH AI rather than getting replaced by it

Is the coding gap between Stats & DS and CS graduates actually significant when applying for tech jobs, or can it be closed through self-study and portfolio projects?

For anyone who has hired in tech, does the school brand (UC vs CSU) actually matter when screening resumes for AI, data science, or engineering roles?

For UCSB students specifically, how accessible are Bay Area internships from Santa Barbara? Is the 5 hour distance a real obstacle or manageable?

Did anyone here choose Stats & DS over CS or vice versa, do you regret it or feel it was the right call looking back?

Is my concern about traditional SWE being automated by AI valid or am I overthinking it? Should that even factor into my school decision?

Anyone in a similar situation, what do you wish you knew before choosing? What would you do differently?

What I'm currently leaning toward:

Based on my research I'm leaning toward UCSB Statistics & Data Science because the UC brand recognition, the deep math foundation for AI roles, and the degree matching what top companies specifically ask for seems to outweigh SFSU's location advantage. But I'm genuinely unsure and I want real honest perspectives before I make this final commitment.

Please be brutally honest, I'd rather hear something uncomfortable and make the right decision than hear what I want and regret it. Any advice, personal experience, or career recommendations are genuinely welcome. Thank you!

Hey everyone, I'm in a situation where I need to make my final university decision and I'm genuinely struggling. The deadline has already passed and I've accepted multiple schools but I need to commit to one. I've done a ton of research but I want real perspectives from people who've actually been in this situation before I make the most important decision of my life.

My situation:

I've been accepted to and already accepted offers at:

UCSB Statistics & Data Science (B.S.)

SFSU Computer Science (B.S.)

Cal State Fullerton CS + Cybersecurity Concentration

I'm a transfer student so only 2 years at whichever school I choose. All three are potentially fully funded including housing so cost is not a factor at all.

I also have waitlists at UCSD CS and UC Davis CS but I need to make my decision based on guaranteed acceptances.

I need to pick ONE and commit. That's where I need your help.

My background:

Currently in the Bay Area

Strong in math and analytical thinking

No strong preference yet for a specific career, still exploring

My career goals honest answer: I don't fully know yet

I'm being honest here, I'm in 2026 and the tech landscape is changing so fast that I want to keep my options open. I haven't locked into one specific career path yet and I plan to do more research over the next year to figure out what direction fits me best.

What I do know:

I want to work in tech in some capacity

I want a high salary and strong job security

I want to be working with AI in some way whether building it, analyzing it, or applying it

I am not very interested in traditional Software Engineering the reason being that AI is automating a significant portion of entry level coding jobs in 2026 and I've seen many fresh SWE graduates struggling to find work. It feels like a risky path for someone graduating in 2028

Beyond that I'm open to recommendations from people with real experience

Research I've already done:

I've gone through real job postings at OpenAI, Google, and Anthropic and found:

OpenAI's Applied AI Engineer role ($230K–$385K) requires strong Python, ML product experience, model evaluation, and prompt engineering does NOT specifically require a CS degree

OpenAI's Applied Data Scientist role ($290K–$441K) names Statistics as the first accepted degree before CS

OpenAI has 20+ Data Scientist and AI roles beyond pure engineering

Google's Student Researcher program explicitly names Statistics as a primary accepted degree alongside CS

For pure engineering roles SWE, AI Systems, Android infrastructure CS clearly has an advantage

For AI and data science roles specifically, Stats & DS is equally or more competitive than CS

What I'm torn between:

UCSB Stats & DS:

UC brand recognized by top tech companies and passes resume screening more easily

Statistics degree = deep math foundation, strong understanding of how AI models actually work at a mathematical level

Matches what OpenAI and Google data science and AI postings specifically ask for

Santa Barbara is 5 hours from Bay Area, slightly harder internship access

Need to self-study Python seriously since degree is math-heavy not coding-heavy

Fewer backup career options if primary path doesn't work out

SFSU CS:

San Francisco location Bay Area tech companies literally next door, easier internship access

Stronger coding foundation from day one

More flexible opens more career doors including cybersecurity, DevOps, data engineering

Weaker brand at top tech companies compared to UC schools

More generic degree competing against thousands of CS graduates every year

Weaker math and statistics foundation for AI and ML understanding specifically

Cal State Fullerton CS + Cybersecurity:

Cybersecurity concentration is genuinely in demand

Weakest brand of the three for top tech company hiring

Southern California location further from Bay Area tech scene

Good backup option but not my first choice

My specific questions for you:

Given that I'm genuinely unsure about my exact career path, which degree and school gives me the most flexibility and best long term options in tech in 2026?

For anyone working in tech right now, what careers do you think are most future-proof and in demand for someone graduating in 2028? I'm especially interested in roles that work WITH AI rather than getting replaced by it

Is the coding gap between Stats & DS and CS graduates actually significant when applying for tech jobs, or can it be closed through self-study and portfolio projects?

For anyone who has hired in tech, does the school brand (UC vs CSU) actually matter when screening resumes for AI, data science, or engineering roles?

For UCSB students specifically, how accessible are Bay Area internships from Santa Barbara? Is the 5 hour distance a real obstacle or manageable?

Did anyone here choose Stats & DS over CS or vice versa, do you regret it or feel it was the right call looking back?

Is my concern about traditional SWE being automated by AI valid or am I overthinking it? Should that even factor into my school decision?

Anyone in a similar situation, what do you wish you knew before choosing? What would you do differently?

What I'm currently leaning toward:

Based on my research I'm leaning toward UCSB Statistics & Data Science because the UC brand recognition, the deep math foundation for AI roles, and the degree matching what top companies specifically ask for seems to outweigh SFSU's location advantage. But I'm genuinely unsure and I want real honest perspectives before I make this final commitment.

Please be brutally honest, I'd rather hear something uncomfortable and make the right decision than hear what I want and regret it. Any advice, personal experience, or career recommendations are genuinely welcome. Thank you!

Hey everyone, I'm in a situation where I need to make my final university decision and I'm genuinely struggling. The deadline has already passed and I've accepted multiple schools but I need to commit to one. I've done a ton of research but I want real perspectives from people who've actually been in this situation before I make the most important decision of my life.

My situation:

I've been accepted to and already accepted offers at:

UCSB Statistics & Data Science (B.S.)

SFSU Computer Science (B.S.)

Cal State Fullerton CS + Cybersecurity Concentration

I'm a transfer student so only 2 years at whichever school I choose. All three are potentially fully funded including housing so cost is not a factor at all.

I also have waitlists at UCSD CS and UC Davis CS but I need to make my decision based on guaranteed acceptances.

I need to pick ONE and commit. That's where I need your help.

My background:

Currently in the Bay Area

Strong in math and analytical thinking

No strong preference yet for a specific career, still exploring

My career goals honest answer: I don't fully know yet

I'm being honest here, I'm in 2026 and the tech landscape is changing so fast that I want to keep my options open. I haven't locked into one specific career path yet and I plan to do more research over the next year to figure out what direction fits me best.

What I do know:

I want to work in tech in some capacity

I want a high salary and strong job security

I want to be working with AI in some way whether building it, analyzing it, or applying it

I am not very interested in traditional Software Engineering the reason being that AI is automating a significant portion of entry level coding jobs in 2026 and I've seen many fresh SWE graduates struggling to find work. It feels like a risky path for someone graduating in 2028

Beyond that I'm open to recommendations from people with real experience

Research I've already done:

I've gone through real job postings at OpenAI, Google, and Anthropic and found:

OpenAI's Applied AI Engineer role ($230K–$385K) requires strong Python, ML product experience, model evaluation, and prompt engineering does NOT specifically require a CS degree

OpenAI's Applied Data Scientist role ($290K–$441K) names Statistics as the first accepted degree before CS

OpenAI has 20+ Data Scientist and AI roles beyond pure engineering

Google's Student Researcher program explicitly names Statistics as a primary accepted degree alongside CS

For pure engineering roles SWE, AI Systems, Android infrastructure CS clearly has an advantage

For AI and data science roles specifically, Stats & DS is equally or more competitive than CS

What I'm torn between:

UCSB Stats & DS:

UC brand recognized by top tech companies and passes resume screening more easily

Statistics degree = deep math foundation, strong understanding of how AI models actually work at a mathematical level

Matches what OpenAI and Google data science and AI postings specifically ask for

Santa Barbara is 5 hours from Bay Area, slightly harder internship access

Need to self-study Python seriously since degree is math-heavy not coding-heavy

Fewer backup career options if primary path doesn't work out

SFSU CS:

San Francisco location Bay Area tech companies literally next door, easier internship access

Stronger coding foundation from day one

More flexible opens more career doors including cybersecurity, DevOps, data engineering

Weaker brand at top tech companies compared to UC schools

More generic degree competing against thousands of CS graduates every year

Weaker math and statistics foundation for AI and ML understanding specifically

Cal State Fullerton CS + Cybersecurity:

Cybersecurity concentration is genuinely in demand

Weakest brand of the three for top tech company hiring

Southern California location further from Bay Area tech scene

Good backup option but not my first choice

My specific questions for you:

Given that I'm genuinely unsure about my exact career path, which degree and school gives me the most flexibility and best long term options in tech in 2026?

For anyone working in tech right now, what careers do you think are most future-proof and in demand for someone graduating in 2028? I'm especially interested in roles that work WITH AI rather than getting replaced by it

Is the coding gap between Stats & DS and CS graduates actually significant when applying for tech jobs, or can it be closed through self-study and portfolio projects?

For anyone who has hired in tech, does the school brand (UC vs CSU) actually matter when screening resumes for AI, data science, or engineering roles?

For UCSB students specifically, how accessible are Bay Area internships from Santa Barbara? Is the 5 hour distance a real obstacle or manageable?

Did anyone here choose Stats & DS over CS or vice versa, do you regret it or feel it was the right call looking back?

Is my concern about traditional SWE being automated by AI valid or am I overthinking it? Should that even factor into my school decision?

Anyone in a similar situation, what do you wish you knew before choosing? What would you do differently?

What I'm currently leaning toward:

Based on my research I'm leaning toward UCSB Statistics & Data Science because the UC brand recognition, the deep math foundation for AI roles, and the degree matching what top companies specifically ask for seems to outweigh SFSU's location advantage. But I'm genuinely unsure and I want real honest perspectives before I make this final commitment.

Please be brutally honest, I'd rather hear something uncomfortable and make the right decision than hear what I want and regret it. Any advice, personal experience, or career recommendations are genuinely welcome. Thank you!

Hey everyone, I'm in a situation where I need to make my final university decision and I'm genuinely struggling. The deadline has already passed and I've accepted multiple schools but I need to commit to one. I've done a ton of research but I want real perspectives from people who've actually been in this situation before I make the most important decision of my life.

My situation:

I've been accepted to and already accepted offers at:

UCSB Statistics & Data Science (B.S.)

SFSU Computer Science (B.S.)

Cal State Fullerton CS + Cybersecurity Concentration

I'm a transfer student so only 2 years at whichever school I choose. All three are potentially fully funded including housing so cost is not a factor at all.

I also have waitlists at UCSD CS and UC Davis CS but I need to make my decision based on guaranteed acceptances.

I need to pick ONE and commit. That's where I need your help.

My background:

Currently in the Bay Area

Strong in math and analytical thinking

No strong preference yet for a specific career, still exploring

My career goals honest answer: I don't fully know yet

I'm being honest here, I'm in 2026 and the tech landscape is changing so fast that I want to keep my options open. I haven't locked into one specific career path yet and I plan to do more research over the next year to figure out what direction fits me best.

What I do know:

I want to work in tech in some capacity

I want a high salary and strong job security

I want to be working with AI in some way whether building it, analyzing it, or applying it

I am not very interested in traditional Software Engineering the reason being that AI is automating a significant portion of entry level coding jobs in 2026 and I've seen many fresh SWE graduates struggling to find work. It feels like a risky path for someone graduating in 2028

Beyond that I'm open to recommendations from people with real experience

Research I've already done:

I've gone through real job postings at OpenAI, Google, and Anthropic and found:

OpenAI's Applied AI Engineer role ($230K–$385K) requires strong Python, ML product experience, model evaluation, and prompt engineering does NOT specifically require a CS degree

OpenAI's Applied Data Scientist role ($290K–$441K) names Statistics as the first accepted degree before CS

OpenAI has 20+ Data Scientist and AI roles beyond pure engineering

Google's Student Researcher program explicitly names Statistics as a primary accepted degree alongside CS

For pure engineering roles SWE, AI Systems, Android infrastructure CS clearly has an advantage

For AI and data science roles specifically, Stats & DS is equally or more competitive than CS

What I'm torn between:

UCSB Stats & DS:

UC brand recognized by top tech companies and passes resume screening more easily

Statistics degree = deep math foundation, strong understanding of how AI models actually work at a mathematical level

Matches what OpenAI and Google data science and AI postings specifically ask for

Santa Barbara is 5 hours from Bay Area, slightly harder internship access

Need to self-study Python seriously since degree is math-heavy not coding-heavy

Fewer backup career options if primary path doesn't work out

SFSU CS:

San Francisco location Bay Area tech companies literally next door, easier internship access

Stronger coding foundation from day one

More flexible opens more career doors including cybersecurity, DevOps, data engineering

Weaker brand at top tech companies compared to UC schools

More generic degree competing against thousands of CS graduates every year

Weaker math and statistics foundation for AI and ML understanding specifically

Cal State Fullerton CS + Cybersecurity:

Cybersecurity concentration is genuinely in demand

Weakest brand of the three for top tech company hiring

Southern California location further from Bay Area tech scene

Good backup option but not my first choice

My specific questions for you:

Given that I'm genuinely unsure about my exact career path, which degree and school gives me the most flexibility and best long term options in tech in 2026?

For anyone working in tech right now, what careers do you think are most future-proof and in demand for someone graduating in 2028? I'm especially interested in roles that work WITH AI rather than getting replaced by it

Is the coding gap between Stats & DS and CS graduates actually significant when applying for tech jobs, or can it be closed through self-study and portfolio projects?

For anyone who has hired in tech, does the school brand (UC vs CSU) actually matter when screening resumes for AI, data science, or engineering roles?

For UCSB students specifically, how accessible are Bay Area internships from Santa Barbara? Is the 5 hour distance a real obstacle or manageable?

Did anyone here choose Stats & DS over CS or vice versa, do you regret it or feel it was the right call looking back?

Is my concern about traditional SWE being automated by AI valid or am I overthinking it? Should that even factor into my school decision?

Anyone in a similar situation, what do you wish you knew before choosing? What would you do differently?

What I'm currently leaning toward:

Based on my research I'm leaning toward UCSB Statistics & Data Science because the UC brand recognition, the deep math foundation for AI roles, and the degree matching what top companies specifically ask for seems to outweigh SFSU's location advantage. But I'm genuinely unsure and I want real honest perspectives before I make this final commitment.

Please be brutally honest, I'd rather hear something uncomfortable and make the right decision than hear what I want and regret it. Any advice, personal experience, or career recommendations are genuinely welcome. Thank you!

Hey everyone, I'm in a situation where I need to make my final university decision and I'm genuinely struggling. The deadline has already passed and I've accepted multiple schools but I need to commit to one. I've done a ton of research but I want real perspectives from people who've actually been in this situation before I make the most important decision of my life.

My situation:

I've been accepted to and already accepted offers at:

UCSB Statistics & Data Science (B.S.)

SFSU Computer Science (B.S.)

Cal State Fullerton CS + Cybersecurity Concentration

I'm a transfer student so only 2 years at whichever school I choose. All three are potentially fully funded including housing so cost is not a factor at all.

I also have waitlists at UCSD CS and UC Davis CS but I need to make my decision based on guaranteed acceptances.

I need to pick ONE and commit. That's where I need your help.

My background:

Currently in the Bay Area

Strong in math and analytical thinking

No strong preference yet for a specific career, still exploring

My career goals honest answer: I don't fully know yet

I'm being honest here, I'm in 2026 and the tech landscape is changing so fast that I want to keep my options open. I haven't locked into one specific career path yet and I plan to do more research over the next year to figure out what direction fits me best.

What I do know:

I want to work in tech in some capacity

I want a high salary and strong job security

I want to be working with AI in some way whether building it, analyzing it, or applying it

I am not very interested in traditional Software Engineering the reason being that AI is automating a significant portion of entry level coding jobs in 2026 and I've seen many fresh SWE graduates struggling to find work. It feels like a risky path for someone graduating in 2028

Beyond that I'm open to recommendations from people with real experience

Research I've already done:

I've gone through real job postings at OpenAI, Google, and Anthropic and found:

OpenAI's Applied AI Engineer role ($230K–$385K) requires strong Python, ML product experience, model evaluation, and prompt engineering does NOT specifically require a CS degree

OpenAI's Applied Data Scientist role ($290K–$441K) names Statistics as the first accepted degree before CS

OpenAI has 20+ Data Scientist and AI roles beyond pure engineering

Google's Student Researcher program explicitly names Statistics as a primary accepted degree alongside CS

For pure engineering roles SWE, AI Systems, Android infrastructure CS clearly has an advantage

For AI and data science roles specifically, Stats & DS is equally or more competitive than CS

What I'm torn between:

UCSB Stats & DS:

UC brand recognized by top tech companies and passes resume screening more easily

Statistics degree = deep math foundation, strong understanding of how AI models actually work at a mathematical level

Matches what OpenAI and Google data science and AI postings specifically ask for

Santa Barbara is 5 hours from Bay Area, slightly harder internship access

Need to self-study Python seriously since degree is math-heavy not coding-heavy

Fewer backup career options if primary path doesn't work out

SFSU CS:

San Francisco location Bay Area tech companies literally next door, easier internship access

Stronger coding foundation from day one

More flexible opens more career doors including cybersecurity, DevOps, data engineering

Weaker brand at top tech companies compared to UC schools

More generic degree competing against thousands of CS graduates every year

Weaker math and statistics foundation for AI and ML understanding specifically

Cal State Fullerton CS + Cybersecurity:

Cybersecurity concentration is genuinely in demand

Weakest brand of the three for top tech company hiring

Southern California location further from Bay Area tech scene

Good backup option but not my first choice

My specific questions for you:

Given that I'm genuinely unsure about my exact career path, which degree and school gives me the most flexibility and best long term options in tech in 2026?

For anyone working in tech right now, what careers do you think are most future-proof and in demand for someone graduating in 2028? I'm especially interested in roles that work WITH AI rather than getting replaced by it

Is the coding gap between Stats & DS and CS graduates actually significant when applying for tech jobs, or can it be closed through self-study and portfolio projects?

For anyone who has hired in tech, does the school brand (UC vs CSU) actually matter when screening resumes for AI, data science, or engineering roles?

For UCSB students specifically, how accessible are Bay Area internships from Santa Barbara? Is the 5 hour distance a real obstacle or manageable?

Did anyone here choose Stats & DS over CS or vice versa, do you regret it or feel it was the right call looking back?

Is my concern about traditional SWE being automated by AI valid or am I overthinking it? Should that even factor into my school decision?

Anyone in a similar situation, what do you wish you knew before choosing? What would you do differently?

What I'm currently leaning toward:

Based on my research I'm leaning toward UCSB Statistics & Data Science because the UC brand recognition, the deep math foundation for AI roles, and the degree matching what top companies specifically ask for seems to outweigh SFSU's location advantage. But I'm genuinely unsure and I want real honest perspectives before I make this final commitment.

Please be brutally honest, I'd rather hear something uncomfortable and make the right decision than hear what I want and regret it. Any advice, personal experience, or career recommendations are genuinely welcome. Thank you!

Hey everyone, I'm in a situation where I need to make my final university decision and I'm genuinely struggling. The deadline has already passed and I've accepted multiple schools but I need to commit to one. I've done a ton of research but I want real perspectives from people who've actually been in this situation before I make the most important decision of my life.

My situation:

I've been accepted to and already accepted offers at:

UCSB Statistics & Data Science (B.S.)

SFSU Computer Science (B.S.)

Cal State Fullerton CS + Cybersecurity Concentration

I'm a transfer student so only 2 years at whichever school I choose. All three are potentially fully funded including housing so cost is not a factor at all.

I also have waitlists at UCSD CS and UC Davis CS but I need to make my decision based on guaranteed acceptances.

I need to pick ONE and commit. That's where I need your help.

My background:

Currently in the Bay Area

Strong in math and analytical thinking

No strong preference yet for a specific career, still exploring

My career goals honest answer: I don't fully know yet

I'm being honest here, I'm in 2026 and the tech landscape is changing so fast that I want to keep my options open. I haven't locked into one specific career path yet and I plan to do more research over the next year to figure out what direction fits me best.

What I do know:

I want to work in tech in some capacity

I want a high salary and strong job security

I want to be working with AI in some way whether building it, analyzing it, or applying it

I am not very interested in traditional Software Engineering the reason being that AI is automating a significant portion of entry level coding jobs in 2026 and I've seen many fresh SWE graduates struggling to find work. It feels like a risky path for someone graduating in 2028

Beyond that I'm open to recommendations from people with real experience

Research I've already done:

I've gone through real job postings at OpenAI, Google, and Anthropic and found:

OpenAI's Applied AI Engineer role ($230K–$385K) requires strong Python, ML product experience, model evaluation, and prompt engineering does NOT specifically require a CS degree

OpenAI's Applied Data Scientist role ($290K–$441K) names Statistics as the first accepted degree before CS

OpenAI has 20+ Data Scientist and AI roles beyond pure engineering

Google's Student Researcher program explicitly names Statistics as a primary accepted degree alongside CS

For pure engineering roles SWE, AI Systems, Android infrastructure CS clearly has an advantage

For AI and data science roles specifically, Stats & DS is equally or more competitive than CS

What I'm torn between:

UCSB Stats & DS:

UC brand recognized by top tech companies and passes resume screening more easily

Statistics degree = deep math foundation, strong understanding of how AI models actually work at a mathematical level

Matches what OpenAI and Google data science and AI postings specifically ask for

Santa Barbara is 5 hours from Bay Area, slightly harder internship access

Need to self-study Python seriously since degree is math-heavy not coding-heavy

Fewer backup career options if primary path doesn't work out

SFSU CS:

San Francisco location Bay Area tech companies literally next door, easier internship access

Stronger coding foundation from day one

More flexible opens more career doors including cybersecurity, DevOps, data engineering

Weaker brand at top tech companies compared to UC schools

More generic degree competing against thousands of CS graduates every year

Weaker math and statistics foundation for AI and ML understanding specifically

Cal State Fullerton CS + Cybersecurity:

Cybersecurity concentration is genuinely in demand

Weakest brand of the three for top tech company hiring

Southern California location further from Bay Area tech scene

Good backup option but not my first choice

My specific questions for you:

Given that I'm genuinely unsure about my exact career path, which degree and school gives me the most flexibility and best long term options in tech in 2026?

For anyone working in tech right now, what careers do you think are most future-proof and in demand for someone graduating in 2028? I'm especially interested in roles that work WITH AI rather than getting replaced by it

Is the coding gap between Stats & DS and CS graduates actually significant when applying for tech jobs, or can it be closed through self-study and portfolio projects?

For anyone who has hired in tech, does the school brand (UC vs CSU) actually matter when screening resumes for AI, data science, or engineering roles?

For UCSB students specifically, how accessible are Bay Area internships from Santa Barbara? Is the 5 hour distance a real obstacle or manageable?

Did anyone here choose Stats & DS over CS or vice versa, do you regret it or feel it was the right call looking back?

Is my concern about traditional SWE being automated by AI valid or am I overthinking it? Should that even factor into my school decision?

Anyone in a similar situation, what do you wish you knew before choosing? What would you do differently?

What I'm currently leaning toward:

Based on my research I'm leaning toward UCSB Statistics & Data Science because the UC brand recognition, the deep math foundation for AI roles, and the degree matching what top companies specifically ask for seems to outweigh SFSU's location advantage. But I'm genuinely unsure and I want real honest perspectives before I make this final commitment.

Please be brutally honest, I'd rather hear something uncomfortable and make the right decision than hear what I want and regret it. Any advice, personal experience, or career recommendations are genuinely welcome. Thank you!

Hey everyone, I'm in a situation where I need to make my final university decision and I'm genuinely struggling. The deadline has already passed and I've accepted multiple schools but I need to commit to one. I've done a ton of research but I want real perspectives from people who've actually been in this situation before I make the most important decision of my life.

My situation:

I've been accepted to and already accepted offers at:

UCSB Statistics & Data Science (B.S.)

SFSU Computer Science (B.S.)

Cal State Fullerton CS + Cybersecurity Concentration

I'm a transfer student so only 2 years at whichever school I choose. All three are potentially fully funded including housing so cost is not a factor at all.

I also have waitlists at UCSD CS and UC Davis CS but I need to make my decision based on guaranteed acceptances.

I need to pick ONE and commit. That's where I need your help.

My background:

Currently in the Bay Area

Strong in math and analytical thinking

No strong preference yet for a specific career, still exploring

My career goals honest answer: I don't fully know yet

I'm being honest here, I'm in 2026 and the tech landscape is changing so fast that I want to keep my options open. I haven't locked into one specific career path yet and I plan to do more research over the next year to figure out what direction fits me best.

What I do know:

I want to work in tech in some capacity

I want a high salary and strong job security

I want to be working with AI in some way whether building it, analyzing it, or applying it

I am not very interested in traditional Software Engineering the reason being that AI is automating a significant portion of entry level coding jobs in 2026 and I've seen many fresh SWE graduates struggling to find work. It feels like a risky path for someone graduating in 2028

Beyond that I'm open to recommendations from people with real experience

Research I've already done:

I've gone through real job postings at OpenAI, Google, and Anthropic and found:

OpenAI's Applied AI Engineer role ($230K–$385K) requires strong Python, ML product experience, model evaluation, and prompt engineering does NOT specifically require a CS degree

OpenAI's Applied Data Scientist role ($290K–$441K) names Statistics as the first accepted degree before CS

OpenAI has 20+ Data Scientist and AI roles beyond pure engineering

Google's Student Researcher program explicitly names Statistics as a primary accepted degree alongside CS

For pure engineering roles SWE, AI Systems, Android infrastructure CS clearly has an advantage

For AI and data science roles specifically, Stats & DS is equally or more competitive than CS

What I'm torn between:

UCSB Stats & DS:

UC brand recognized by top tech companies and passes resume screening more easily

Statistics degree = deep math foundation, strong understanding of how AI models actually work at a mathematical level

Matches what OpenAI and Google data science and AI postings specifically ask for

Santa Barbara is 5 hours from Bay Area, slightly harder internship access

Need to self-study Python seriously since degree is math-heavy not coding-heavy

Fewer backup career options if primary path doesn't work out

SFSU CS:

San Francisco location Bay Area tech companies literally next door, easier internship access

Stronger coding foundation from day one

More flexible opens more career doors including cybersecurity, DevOps, data engineering

Weaker brand at top tech companies compared to UC schools

More generic degree competing against thousands of CS graduates every year

Weaker math and statistics foundation for AI and ML understanding specifically

Cal State Fullerton CS + Cybersecurity:

Cybersecurity concentration is genuinely in demand

Weakest brand of the three for top tech company hiring

Southern California location further from Bay Area tech scene

Good backup option but not my first choice

My specific questions for you:

Given that I'm genuinely unsure about my exact career path, which degree and school gives me the most flexibility and best long term options in tech in 2026?

For anyone working in tech right now, what careers do you think are most future-proof and in demand for someone graduating in 2028? I'm especially interested in roles that work WITH AI rather than getting replaced by it

Is the coding gap between Stats & DS and CS graduates actually significant when applying for tech jobs, or can it be closed through self-study and portfolio projects?

For anyone who has hired in tech, does the school brand (UC vs CSU) actually matter when screening resumes for AI, data science, or engineering roles?

For UCSB students specifically, how accessible are Bay Area internships from Santa Barbara? Is the 5 hour distance a real obstacle or manageable?

Did anyone here choose Stats & DS over CS or vice versa, do you regret it or feel it was the right call looking back?

Is my concern about traditional SWE being automated by AI valid or am I overthinking it? Should that even factor into my school decision?

Anyone in a similar situation, what do you wish you knew before choosing? What would you do differently?

What I'm currently leaning toward:

Based on my research I'm leaning toward UCSB Statistics & Data Science because the UC brand recognition, the deep math foundation for AI roles, and the degree matching what top companies specifically ask for seems to outweigh SFSU's location advantage. But I'm genuinely unsure and I want real honest perspectives before I make this final commitment.

Please be brutally honest, I'd rather hear something uncomfortable and make the right decision than hear what I want and regret it. Any advice, personal experience, or career recommendations are genuinely welcome. Thank you!

Hey everyone, I'm in a situation where I need to make my final university decision and I'm genuinely struggling. The deadline has already passed and I've accepted multiple schools but I need to commit to one. I've done a ton of research but I want real perspectives from people who've actually been in this situation before I make the most important decision of my life.

My situation:

I've been accepted to and already accepted offers at:

UCSB Statistics & Data Science (B.S.)

SFSU Computer Science (B.S.)

Cal State Fullerton CS + Cybersecurity Concentration

I'm a transfer student so only 2 years at whichever school I choose. All three are potentially fully funded including housing so cost is not a factor at all.

Important context: All three schools are completely free for me including tuition, housing, and living expenses. Cost is not a factor in this decision at all. This means I'm choosing purely based on which school and degree sets me up best for my career.

I also have waitlists at UCSD CS and UC Davis CS but I need to make my decision based on guaranteed acceptances.

I need to pick ONE and commit. That's where I need your help.

My background:

Currently in the Bay Area

Strong in math and analytical thinking

No strong preference yet for a specific career, still exploring

My career goals honest answer: I don't fully know yet

I'm being honest here, I'm in 2026 and the tech landscape is changing so fast that I want to keep my options open. I haven't locked into one specific career path yet and I plan to do more research over the next year to figure out what direction fits me best.

What I do know:

I want to work in tech in some capacity

I want a high salary and strong job security

I want to be working with AI in some way whether building it, analyzing it, or applying it

I am not very interested in traditional Software Engineering the reason being that AI is automating a significant portion of entry level coding jobs in 2026 and I've seen many fresh SWE graduates struggling to find work. It feels like a risky path for someone graduating in 2028

Beyond that I'm open to recommendations from people with real experience

Research I've already done:

I've gone through real job postings at OpenAI, Google, and Anthropic and found:

OpenAI's Applied AI Engineer role ($230K–$385K) requires strong Python, ML product experience, model evaluation, and prompt engineering does NOT specifically require a CS degree

OpenAI's Applied Data Scientist role ($290K–$441K) names Statistics as the first accepted degree before CS

OpenAI has 20+ Data Scientist and AI roles beyond pure engineering

Google's Student Researcher program explicitly names Statistics as a primary accepted degree alongside CS

For pure engineering roles SWE, AI Systems, Android infrastructure CS clearly has an advantage

For AI and data science roles specifically, Stats & DS is equally or more competitive than CS

What I'm torn between:

UCSB Stats & DS:

UC brand recognized by top tech companies and passes resume screening more easily

Statistics degree = deep math foundation, strong understanding of how AI models actually work at a mathematical level

Matches what OpenAI and Google data science and AI postings specifically ask for

Santa Barbara is 5 hours from Bay Area, slightly harder internship access

Need to self-study Python seriously since degree is math-heavy not coding-heavy

Fewer backup career options if primary path doesn't work out

SFSU CS:

San Francisco location Bay Area tech companies literally next door, easier internship access

Stronger coding foundation from day one

More flexible opens more career doors including cybersecurity, DevOps, data engineering

Weaker brand at top tech companies compared to UC schools

More generic degree competing against thousands of CS graduates every year

Weaker math and statistics foundation for AI and ML understanding specifically

Cal State Fullerton CS + Cybersecurity:

Cybersecurity concentration is genuinely in demand

Weakest brand of the three for top tech company hiring

Southern California location further from Bay Area tech scene

Good backup option but not my first choice

My specific questions for you:

Given that I'm genuinely unsure about my exact career path, which degree and school gives me the most flexibility and best long term options in tech in 2026?

For anyone working in tech right now, what careers do you think are most future-proof and in demand for someone graduating in 2028? I'm especially interested in roles that work WITH AI rather than getting replaced by it

Is the coding gap between Stats & DS and CS graduates actually significant when applying for tech jobs, or can it be closed through self-study and portfolio projects?

For anyone who has hired in tech, does the school brand (UC vs CSU) actually matter when screening resumes for AI, data science, or engineering roles?

For UCSB students specifically, how accessible are Bay Area internships from Santa Barbara? Is the 5 hour distance a real obstacle or manageable?

Did anyone here choose Stats & DS over CS or vice versa, do you regret it or feel it was the right call looking back?

Is my concern about traditional SWE being automated by AI valid or am I overthinking it? Should that even factor into my school decision?

Anyone in a similar situation, what do you wish you knew before choosing? What would you do differently?

What I'm currently leaning toward:

Based on my research I'm leaning toward UCSB Statistics & Data Science because the UC brand recognition, the deep math foundation for AI roles, and the degree matching what top companies specifically ask for seems to outweigh SFSU's location advantage. But I'm genuinely unsure and I want real honest perspectives before I make this final commitment.

Please be brutally honest, I'd rather hear something uncomfortable and make the right decision than hear what I want and regret it. Any advice, personal experience, or career recommendations are genuinely welcome. Thank you!

Hey everyone, I'm in a situation where I need to make my final university decision and I'm genuinely struggling. The deadline has already passed and I've accepted multiple schools but I need to commit to one. I've done a ton of research but I want real perspectives from people who've actually been in this situation before I make the most important decision of my life.

My situation:

I've been accepted to and already accepted offers at:

UCSB Statistics & Data Science (B.S.)

SFSU Computer Science (B.S.)

Cal State Fullerton CS + Cybersecurity Concentration

I'm a transfer student so only 2 years at whichever school I choose. All three are potentially fully funded including housing so cost is not a factor at all.

Important context: All three schools are completely free for me including tuition, housing, and living expenses. Cost is not a factor in this decision at all. This means I'm choosing purely based on which school and degree sets me up best for my career.

I also have waitlists at UCSD CS and UC Davis CS but I need to make my decision based on guaranteed acceptances.

I need to pick ONE and commit. That's where I need your help.

My background:

Currently in the Bay Area

Strong in math and analytical thinking

No strong preference yet for a specific career, still exploring

My career goals honest answer: I don't fully know yet

I'm being honest here, I'm in 2026 and the tech landscape is changing so fast that I want to keep my options open. I haven't locked into one specific career path yet and I plan to do more research over the next year to figure out what direction fits me best.

What I do know:

I want to work in tech in some capacity

I want a high salary and strong job security

I want to be working with AI in some way whether building it, analyzing it, or applying it

I am not very interested in traditional Software Engineering the reason being that AI is automating a significant portion of entry level coding jobs in 2026 and I've seen many fresh SWE graduates struggling to find work. It feels like a risky path for someone graduating in 2028

Beyond that I'm open to recommendations from people with real experience

Research I've already done:

I've gone through real job postings at OpenAI, Google, and Anthropic and found:

OpenAI's Applied AI Engineer role ($230K–$385K) requires strong Python, ML product experience, model evaluation, and prompt engineering does NOT specifically require a CS degree

OpenAI's Applied Data Scientist role ($290K–$441K) names Statistics as the first accepted degree before CS

OpenAI has 20+ Data Scientist and AI roles beyond pure engineering

Google's Student Researcher program explicitly names Statistics as a primary accepted degree alongside CS

For pure engineering roles SWE, AI Systems, Android infrastructure CS clearly has an advantage

For AI and data science roles specifically, Stats & DS is equally or more competitive than CS

What I'm torn between:

UCSB Stats & DS:

UC brand recognized by top tech companies and passes resume screening more easily

Statistics degree = deep math foundation, strong understanding of how AI models actually work at a mathematical level

Matches what OpenAI and Google data science and AI postings specifically ask for

Santa Barbara is 5 hours from Bay Area, slightly harder internship access

Need to self-study Python seriously since degree is math-heavy not coding-heavy

Fewer backup career options if primary path doesn't work out

SFSU CS:

San Francisco location Bay Area tech companies literally next door, easier internship access

Stronger coding foundation from day one

More flexible opens more career doors including cybersecurity, DevOps, data engineering

Weaker brand at top tech companies compared to UC schools

More generic degree competing against thousands of CS graduates every year

Weaker math and statistics foundation for AI and ML understanding specifically

Cal State Fullerton CS + Cybersecurity:

Cybersecurity concentration is genuinely in demand

Weakest brand of the three for top tech company hiring

Southern California location further from Bay Area tech scene

Good backup option but not my first choice

My specific questions for you:

Given that I'm genuinely unsure about my exact career path, which degree and school gives me the most flexibility and best long term options in tech in 2026?

For anyone working in tech right now, what careers do you think are most future-proof and in demand for someone graduating in 2028? I'm especially interested in roles that work WITH AI rather than getting replaced by it

Is the coding gap between Stats & DS and CS graduates actually significant when applying for tech jobs, or can it be closed through self-study and portfolio projects?

For anyone who has hired in tech, does the school brand (UC vs CSU) actually matter when screening resumes for AI, data science, or engineering roles?

For UCSB students specifically, how accessible are Bay Area internships from Santa Barbara? Is the 5 hour distance a real obstacle or manageable?

Did anyone here choose Stats & DS over CS or vice versa, do you regret it or feel it was the right call looking back?

Is my concern about traditional SWE being automated by AI valid or am I overthinking it? Should that even factor into my school decision?

Anyone in a similar situation, what do you wish you knew before choosing? What would you do differently?

What I'm currently leaning toward:

Based on my research I'm leaning toward UCSB Statistics & Data Science because the UC brand recognition, the deep math foundation for AI roles, and the degree matching what top companies specifically ask for seems to outweigh SFSU's location advantage. But I'm genuinely unsure and I want real honest perspectives before I make this final commitment.

Please be brutally honest, I'd rather hear something uncomfortable and make the right decision than hear what I want and regret it. Any advice, personal experience, or career recommendations are genuinely welcome. Thank you!

Body:

Hey everyone, I'm in a situation where I need to make my final university decision and I'm genuinely struggling. The deadline has already passed and I've accepted multiple schools but I need to commit to one. I've done a ton of research but I want real perspectives from people who've actually been in this situation before I make the most important decision of my life.

My situation:

I've been accepted to and already accepted offers at:

UCSB Statistics & Data Science (B.S.)

SFSU Computer Science (B.S.)

Cal State Fullerton CS + Cybersecurity Concentration

I'm a transfer student so only 2 years at whichever school I choose. All three are potentially fully funded including housing so cost is not a factor at all.

I also have waitlists at UCSD CS and UC Davis CS but I need to make my decision based on guaranteed acceptances.

I need to pick ONE and commit. That's where I need your help.

My background:

Currently in the Bay Area

Strong in math and analytical thinking

No strong preference yet for a specific career, still exploring

My career goals honest answer: I don't fully know yet

I'm being honest here, I'm in 2026 and the tech landscape is changing so fast that I want to keep my options open. I haven't locked into one specific career path yet and I plan to do more research over the next year to figure out what direction fits me best.

What I do know:

I want to work in tech in some capacity

I want a high salary and strong job security

I want to be working with AI in some way whether building it, analyzing it, or applying it

I am not very interested in traditional Software Engineering the reason being that AI is automating a significant portion of entry level coding jobs in 2026 and I've seen many fresh SWE graduates struggling to find work. It feels like a risky path for someone graduating in 2028

Beyond that I'm open to recommendations from people with real experience

Research I've already done:

I've gone through real job postings at OpenAI, Google, and Anthropic and found:

OpenAI's Applied AI Engineer role ($230K–$385K) requires strong Python, ML product experience, model evaluation, and prompt engineering does NOT specifically require a CS degree

OpenAI's Applied Data Scientist role ($290K–$441K) names Statistics as the first accepted degree before CS

OpenAI has 20+ Data Scientist and AI roles beyond pure engineering

Google's Student Researcher program explicitly names Statistics as a primary accepted degree alongside CS

For pure engineering roles SWE, AI Systems, Android infrastructure CS clearly has an advantage

For AI and data science roles specifically, Stats & DS is equally or more competitive than CS

What I'm torn between:

UCSB Stats & DS:

UC brand recognized by top tech companies and passes resume screening more easily

Statistics degree = deep math foundation, strong understanding of how AI models actually work at a mathematical level

Matches what OpenAI and Google data science and AI postings specifically ask for

Santa Barbara is 5 hours from Bay Area, slightly harder internship access

Need to self-study Python seriously since degree is math-heavy not coding-heavy

Fewer backup career options if primary path doesn't work out

SFSU CS:

San Francisco location Bay Area tech companies literally next door, easier internship access

Stronger coding foundation from day one

More flexible opens more career doors including cybersecurity, DevOps, data engineering

Weaker brand at top tech companies compared to UC schools

More generic degree competing against thousands of CS graduates every year

Weaker math and statistics foundation for AI and ML understanding specifically

Cal State Fullerton CS + Cybersecurity:

Cybersecurity concentration is genuinely in demand

Weakest brand of the three for top tech company hiring

Southern California location further from Bay Area tech scene

Good backup option but not my first choice

My specific questions for you:

Given that I'm genuinely unsure about my exact career path, which degree and school gives me the most flexibility and best long term options in tech in 2026?

For anyone working in tech right now, what careers do you think are most future-proof and in demand for someone graduating in 2028? I'm especially interested in roles that work WITH AI rather than getting replaced by it

Is the coding gap between Stats & DS and CS graduates actually significant when applying for tech jobs, or can it be closed through self-study and portfolio projects?

For anyone who has hired in tech, does the school brand (UC vs CSU) actually matter when screening resumes for AI, data science, or engineering roles?

For UCSB students specifically, how accessible are Bay Area internships from Santa Barbara? Is the 5 hour distance a real obstacle or manageable?

Did anyone here choose Stats & DS over CS or vice versa, do you regret it or feel it was the right call looking back?

Is my concern about traditional SWE being automated by AI valid or am I overthinking it? Should that even factor into my school decision?

Anyone in a similar situation, what do you wish you knew before choosing? What would you do differently?

What I'm currently leaning toward:

Based on my research I'm leaning toward UCSB Statistics & Data Science because the UC brand recognition, the deep math foundation for AI roles, and the degree matching what top companies specifically ask for seems to outweigh SFSU's location advantage. But I'm genuinely unsure and I want real honest perspectives before I make this final commitment.

Please be brutally honest, I'd rather hear something uncomfortable and make the right decision than hear what I want and regret it. Any advice, personal experience, or career recommendations are genuinely welcome. Thank you!

Any (in state) got in for Computer science??

Has anyone dealt with this with UCI TAG before?

I was denied UCI TAG for Computer Engineering because of a missing circuits analysis requirement. However, when I checked the official ASSIST agreement between UCI and my community college, the course is listed as “No Course Articulated.”

My understanding was that “No Course Articulated” means there is no approved equivalent at the community college, so the course would normally be completed after transfer at the UC.

So my question is:

Should a student be denied TAG for a requirement that ASSIST lists as “No Course Articulated” at their home college?

I already submitted a TAG inquiry and got denied for the second time. Now my case has been moved to formal appeal. I’m trying to understand if anyone else experienced something similar this cycle.