u/tastychaii

Hi all!

I just got the BenQ MA270S 27" 5K monitor today and the display looks amazing!

Unfortunately whilst setting up I observed multiple flexible gaps on the bottom bezel that flex when lightly pressed and I'm not sure if this is normal or not.

Looking for advice if this is a defect or an issue and whether I should get it replaced?

Video:
https://imgur.com/a/p8wg7is

Thanks.

Hi all!

I just got the BenQ MA270S 27" 5K monitor today and the display looks amazing!

Unfortunately whilst setting up I observed multiple flexible gaps on the bottom bezel that flex when lightly pressed and I'm not sure if this is normal or not.

Looking for advice if this is a defect or an issue and whether I should get it replaced?

Video:
https://imgur.com/a/p8wg7is

Thanks.

Hi guys,

I had a AC technician come over to my parent’s place for them to fix a few things and this technician who was explaining something to my dad wrote a D using his pen on the air temperature sensor.

How on earth can I get rid of this mark? I just noticed it and my dad did not bother mentioning anything.

Thanks!

Hey guys,

A little about me. I have around 9 years relevant experience in IT. I work as an IT Business Analyst and have worked previously as a BI Engineer and Data Analyst. My formal education background is in Electronics Engineering.

I want to get into the machine learning space and on a program that has CSP.

Has anyone taken this Master of Science in Health Data Science program?

It would help with data analyst/scientist roles in the medical industry however curious on people’s thoughts on its usefulness in data science roles outside of health as well?

Also how would you compare it to the normal “Data Science” university programs? (I know it would be different based on the country and uni - I'm in australia btw).

I got the following from someone else's post here however it is relevant for me as well:

1. Day-to-day work: How much of your work is data cleaning/SQL vs statistical modeling vs ML?
2. Skill leverage: Which skills matter most in practice:- statistics, ML, SQL, or healthcare domain knowledge?
3. Modeling depth: How often are advanced ML models used compared to classical statistical approaches, and why?
4. Career growth: Where do you see the demand for healthcare Data Scientists / ML Engineers be?
5. Salary trajectory: How does long-term salary growth in healthcare data science compare with more generic data science roles?
6. Job market reality: Do you feel the field is getting saturated, or is demand still strong for well-skilled profiles?
7. Transferability: How easy or difficult is it to pivot from healthcare data science into other data science roles later in one’s career?
8. AI Safe: How much safer do you say are Data Science / ML roles vs other traditional IT such as developers, Business Analysts etc.
9. Tooling: Do you use mostly R or Python? What would you say is the ratio of these two vs SQL in Data Science roles?

This is the program I'm interested in:
https://www.unsw.edu.au/study/postgraduate/master-of-science

Thanks!

Hey guys,

A little about me. I have around 9 years relevant experience in IT. I work as an IT Business Analyst and have worked previously as a BI Engineer and Data Analyst. My formal education background is in Electronics Engineering.

I want to get into the machine learning space and on a program that has CSP.

Has anyone taken this Master of Science in Health Data Science course?

It would help with data analyst/scientist roles in the medical industry however curious on people’s thoughts on its usefulness in data science roles outside of health as well?

Also how would you compare it to the normal “Data Science” course at UNSW and others?

I got the following from someone else's post here however it is relevant for me as well:

1. Day-to-day work: How much of your work is data cleaning/SQL vs statistical modeling vs ML?
2. Skill leverage: Which skills matter most in practice:- statistics, ML, SQL, or healthcare domain knowledge?
3. Modeling depth: How often are advanced ML models used compared to classical statistical approaches, and why?
4. Career growth: Where do you see the demand for healthcare Data Scientists / ML Engineers be?
5. Salary trajectory: How does long-term salary growth in healthcare data science compare with more generic data science roles?
6. Job market reality: Do you feel the field is getting saturated, or is demand still strong for well-skilled profiles?
7. Transferability: How easy or difficult is it to pivot from healthcare data science into other data science roles later in one’s career?
8. AI Safe: How much safer do you say are Data Science / ML roles vs other traditional IT such as developers, Business Analysts etc.
9. Tooling: Do you use mostly R or Python? What would you say is the ratio of these two vs SQL in Data Science roles?

This is the program I'm interested in:
https://www.unsw.edu.au/study/postgraduate/master-of-science

Thanks!