u/GOATEDSTARS

I’m considering buying PromptBuilder - AI Prompt Engineer: Starter Plan Lifetime Subscription, but I’m skeptical of paid “prompt engineering” tools in general.

This is not a promotion. I’m including the URL only so people know the exact product I’m asking about.

The product claims to help generate, optimize, and organize prompts for tools like ChatGPT, Claude, Gemini, DeepSeek, Perplexity, and other AI assistants. The lifetime pricing looks appealing at first, but my concern is that many AI prompt tools seem to repackage material that is already available for free through GitHub prompt libraries, official OpenAI/Anthropic/Google documentation, PromptingGuide.ai, Learn Prompting, and similar free resources.

For anyone who has used PromptBuilder, or a similar paid prompt-generation tool:

• Did it produce meaningfully better prompts than what you can build manually with free resources?
• Is the workflow actually useful, or is the main benefit just convenience?
• Are the monthly prompt/request limits restrictive in real use?
• Does it stay current with newer models and prompting methods?
• Is the prompt quality advanced, or mostly generic “act as…” style templates?
• Are there hidden downsides, upsells, weak support, or account limitations?
• Would you buy it again?
• For serious use cases like research, writing, coding assistance, data analysis, business productivity, or AI workflow design, does it add real value?

I’m not looking for hype or affiliate-style answers. I’m trying to determine whether this product provides enough practical value to justify buying it, or whether someone already comfortable using ChatGPT/Claude/Gemini directly would be better off learning prompt engineering manually and using free resources.

Appreciate honest feedback from anyone who has tested it.

Product link for reference only:
https://www.stacksocial.com/sales/promptbuilder-ai-prompt-engineer-starter-plan-lifetime-subscription

I’m considering buying PromptBuilder - AI Prompt Engineer: Starter Plan Lifetime Subscription, but I’m skeptical of paid “prompt engineering” tools in general.

This is not a promotion. I’m including the URL only so people know the exact product I’m asking about.

The product claims to help generate, optimize, and organize prompts for tools like ChatGPT, Claude, Gemini, DeepSeek, Perplexity, and other AI assistants. The lifetime pricing looks appealing at first, but my concern is that many AI prompt tools seem to repackage material that is already available for free through GitHub prompt libraries, official OpenAI/Anthropic/Google documentation, PromptingGuide.ai, Learn Prompting, and similar free resources.

For anyone who has used PromptBuilder, or a similar paid prompt-generation tool:

• Did it produce meaningfully better prompts than what you can build manually with free resources?
• Is the workflow actually useful, or is the main benefit just convenience?
• Are the monthly prompt/request limits restrictive in real use?
• Does it stay current with newer models and prompting methods?
• Is the prompt quality advanced, or mostly generic “act as…” style templates?
• Are there hidden downsides, upsells, weak support, or account limitations?
• Would you buy it again?
• For serious use cases like research, writing, coding assistance, data analysis, business productivity, or AI workflow design, does it add real value?

I’m not looking for hype or affiliate-style answers. I’m trying to determine whether this product provides enough practical value to justify buying it, or whether someone already comfortable using ChatGPT/Claude/Gemini directly would be better off learning prompt engineering manually and using free resources.

Appreciate honest feedback from anyone who has tested it.

Product link for reference only:
https://www.stacksocial.com/sales/promptbuilder-ai-prompt-engineer-starter-plan-lifetime-subscription

UTD Business Analytics and Artificial Intelligence: What should I prioritize before fall as a transfer student with limited programming experience?
I was recently admitted to UTD for the B.S. in Business Analytics and Artificial Intelligence in JSOM, with a planned concentration in Finance and Risk Analytics.

I am transferring from community college and would appreciate honest advice from current students, alumni, JSOM analytics majors, MIS students, or anyone who has taken BUAN/ITSS courses. My main concern is preparing properly before the fall semester because I have very limited formal programming experience.

Right now, I am learning Python independently. I have completed about 100 out of 527 steps in the freeCodeCamp Python course. My plan is to finish freeCodeCamp first, then complete Harvard CS50P: Introduction to Programming with Python before classes begin. I have about three months before the fall semester starts.

From reviewing the degree plan, it looks like the main programming and technical tools used across the major are Python, SQL, NoSQL, R, and possibly Hive/Spark in selected courses.

Python appears in courses such as:
ITSS 3311 — Introduction to Programming
BUAN 4381 — Object Oriented Programming with Python
BUAN 4353 — Business Analytics
BUAN 4383 — Advanced Applied Artificial Intelligence/Machine Learning
FIN 4346 — Applied Machine Learning in Finance, Insurance, and Real Estate
SQL appears especially relevant for:
BUAN 4320 — Database Fundamentals for Analytics
BUAN 4351 — Foundations of Business Intelligence
BUAN 4353 — Business Analytics

My main question is whether completing freeCodeCamp Python and Harvard CS50P would be enough preparation to enter the program successfully, or whether I should also spend part of the summer learning SQL, Excel modeling, statistics, or basic data analytics tools.

For those who have taken these courses, I would also appreciate insight on which BUAN/ITSS courses tend to be the biggest adjustment for transfer students, especially students who started programming later.
I am not trying to avoid the technical side of the degree. I am willing to put in the work. I just want a realistic understanding of what to prioritize before fall so I can start the program prepared instead of reacting late.

Any advice from transfer students, students who started programming late, JSOM analytics students, MIS students, or alumni would be appreciated.

UTD Business Analytics and Artificial Intelligence: What should I prioritize before fall as a transfer student with limited programming experience?
I was recently admitted to UTD for the B.S. in Business Analytics and Artificial Intelligence in JSOM, with a planned concentration in Finance and Risk Analytics.

I am transferring from community college and would appreciate honest advice from current students, alumni, JSOM analytics majors, MIS students, or anyone who has taken BUAN/ITSS courses. My main concern is preparing properly before the fall semester because I have very limited formal programming experience.

Right now, I am learning Python independently. I have completed about 100 out of 527 steps in the freeCodeCamp Python course. My plan is to finish freeCodeCamp first, then complete Harvard CS50P: Introduction to Programming with Python before classes begin. I have about three months before the fall semester starts.

From reviewing the degree plan, it looks like the main programming and technical tools used across the major are Python, SQL, NoSQL, R, and possibly Hive/Spark in selected courses.

Python appears in courses such as:
ITSS 3311 — Introduction to Programming
BUAN 4381 — Object Oriented Programming with Python
BUAN 4353 — Business Analytics
BUAN 4383 — Advanced Applied Artificial Intelligence/Machine Learning
FIN 4346 — Applied Machine Learning in Finance, Insurance, and Real Estate
SQL appears especially relevant for:
BUAN 4320 — Database Fundamentals for Analytics
BUAN 4351 — Foundations of Business Intelligence
BUAN 4353 — Business Analytics

My main question is whether completing freeCodeCamp Python and Harvard CS50P would be enough preparation to enter the program successfully, or whether I should also spend part of the summer learning SQL, Excel modeling, statistics, or basic data analytics tools.

For those who have taken these courses, I would also appreciate insight on which BUAN/ITSS courses tend to be the biggest adjustment for transfer students, especially students who started programming later.
I am not trying to avoid the technical side of the degree. I am willing to put in the work. I just want a realistic understanding of what to prioritize before fall so I can start the program prepared instead of reacting late.

Any advice from transfer students, students who started programming late, JSOM analytics students, MIS students, or alumni would be appreciated.

UTD Business Analytics and Artificial Intelligence: What should I prioritize before fall as a transfer student with limited programming experience?
I was recently admitted to UTD for the B.S. in Business Analytics and Artificial Intelligence in JSOM, with a planned concentration in Finance and Risk Analytics.

I am transferring from community college and would appreciate honest advice from current students, alumni, JSOM analytics majors, MIS students, or anyone who has taken BUAN/ITSS courses. My main concern is preparing properly before the fall semester because I have very limited formal programming experience.

Right now, I am learning Python independently. I have completed about 100 out of 527 steps in the freeCodeCamp Python course. My plan is to finish freeCodeCamp first, then complete Harvard CS50P: Introduction to Programming with Python before classes begin. I have about three months before the fall semester starts.

From reviewing the degree plan, it looks like the main programming and technical tools used across the major are Python, SQL, NoSQL, R, and possibly Hive/Spark in selected courses.

Python appears in courses such as:
ITSS 3311 — Introduction to Programming
BUAN 4381 — Object Oriented Programming with Python
BUAN 4353 — Business Analytics
BUAN 4383 — Advanced Applied Artificial Intelligence/Machine Learning
FIN 4346 — Applied Machine Learning in Finance, Insurance, and Real Estate
SQL appears especially relevant for:
BUAN 4320 — Database Fundamentals for Analytics
BUAN 4351 — Foundations of Business Intelligence
BUAN 4353 — Business Analytics

My main question is whether completing freeCodeCamp Python and Harvard CS50P would be enough preparation to enter the program successfully, or whether I should also spend part of the summer learning SQL, Excel modeling, statistics, or basic data analytics tools.

For those who have taken these courses, I would also appreciate insight on which BUAN/ITSS courses tend to be the biggest adjustment for transfer students, especially students who started programming later.
I am not trying to avoid the technical side of the degree. I am willing to put in the work. I just want a realistic understanding of what to prioritize before fall so I can start the program prepared instead of reacting late.

Any advice from transfer students, students who started programming late, JSOM analytics students, MIS students, or alumni would be appreciated.

UTD Business Analytics and Artificial Intelligence: What should I prioritize before fall as a transfer student with limited programming experience?
I was recently admitted to UTD for the B.S. in Business Analytics and Artificial Intelligence in JSOM, with a planned concentration in Finance and Risk Analytics.

I am transferring from community college and would appreciate honest advice from current students, alumni, JSOM analytics majors, MIS students, or anyone who has taken BUAN/ITSS courses. My main concern is preparing properly before the fall semester because I have very limited formal programming experience.

Right now, I am learning Python independently. I have completed about 100 out of 527 steps in the freeCodeCamp Python course. My plan is to finish freeCodeCamp first, then complete Harvard CS50P: Introduction to Programming with Python before classes begin. I have about three months before the fall semester starts.

From reviewing the degree plan, it looks like the main programming and technical tools used across the major are Python, SQL, NoSQL, R, and possibly Hive/Spark in selected courses.

Python appears in courses such as:
ITSS 3311 — Introduction to Programming
BUAN 4381 — Object Oriented Programming with Python
BUAN 4353 — Business Analytics
BUAN 4383 — Advanced Applied Artificial Intelligence/Machine Learning
FIN 4346 — Applied Machine Learning in Finance, Insurance, and Real Estate
SQL appears especially relevant for:
BUAN 4320 — Database Fundamentals for Analytics
BUAN 4351 — Foundations of Business Intelligence
BUAN 4353 — Business Analytics

My main question is whether completing freeCodeCamp Python and Harvard CS50P would be enough preparation to enter the program successfully, or whether I should also spend part of the summer learning SQL, Excel modeling, statistics, or basic data analytics tools.

For those who have taken these courses, I would also appreciate insight on which BUAN/ITSS courses tend to be the biggest adjustment for transfer students, especially students who started programming later.
I am not trying to avoid the technical side of the degree. I am willing to put in the work. I just want a realistic understanding of what to prioritize before fall so I can start the program prepared instead of reacting late.

Any advice from transfer students, students who started programming late, JSOM analytics students, MIS students, or alumni would be appreciated.

UTD Business Analytics and Artificial Intelligence: What should I prioritize before fall as a transfer student with limited programming experience?
I was recently admitted to UTD for the B.S. in Business Analytics and Artificial Intelligence in JSOM, with a planned concentration in Finance and Risk Analytics.

I am transferring from community college and would appreciate honest advice from current students, alumni, JSOM analytics majors, MIS students, or anyone who has taken BUAN/ITSS courses. My main concern is preparing properly before the fall semester because I have very limited formal programming experience.

Right now, I am learning Python independently. I have completed about 100 out of 527 steps in the freeCodeCamp Python course. My plan is to finish freeCodeCamp first, then complete Harvard CS50P: Introduction to Programming with Python before classes begin. I have about three months before the fall semester starts.

From reviewing the degree plan, it looks like the main programming and technical tools used across the major are Python, SQL, NoSQL, R, and possibly Hive/Spark in selected courses.

Python appears in courses such as:
ITSS 3311 — Introduction to Programming
BUAN 4381 — Object Oriented Programming with Python
BUAN 4353 — Business Analytics
BUAN 4383 — Advanced Applied Artificial Intelligence/Machine Learning
FIN 4346 — Applied Machine Learning in Finance, Insurance, and Real Estate
SQL appears especially relevant for:
BUAN 4320 — Database Fundamentals for Analytics
BUAN 4351 — Foundations of Business Intelligence
BUAN 4353 — Business Analytics

My main question is whether completing freeCodeCamp Python and Harvard CS50P would be enough preparation to enter the program successfully, or whether I should also spend part of the summer learning SQL, Excel modeling, statistics, or basic data analytics tools.

For those who have taken these courses, I would also appreciate insight on which BUAN/ITSS courses tend to be the biggest adjustment for transfer students, especially students who started programming later.
I am not trying to avoid the technical side of the degree. I am willing to put in the work. I just want a realistic understanding of what to prioritize before fall so I can start the program prepared instead of reacting late.

Any advice from transfer students, students who started programming late, JSOM analytics students, MIS students, or alumni would be appreciated.