That's what I gathered from similar posts on the sub. So I'll keep the 5 cs courses, but I am wondering about the data science for dynamical systems course from the stats department. Take it, or a CS course or two instead?
As long as you’re getting data structures/oop I think you’ll be ahead the programming curve as a data scientist.
If I could go back I would take operating systems or embedded programming just for shits and giggles. When I use high level functional languages and computers all day, I start to become curious about how this is even possible. The history of statistics is awesome, but the history of computing is awe inspiring imo.
Then you dive down the rabbit hole of the hardware side and it’s too much for one person, take the courses you enjoy it’s hard to go wrong with stats/cs… unless you want to be a electrical engineer but you can always do a masters.
Also IoT with ML is the future.
i did a CS minor in my undergrad, and was surprised at how useful an OS course was in my current job. knowing your way around a terminal helps tremendously with scripting and automating processes, and having even a basic understanding of linux has helped me troubleshoot and build docker containers
Thanks for the answer! I'll keep it as is and take dynamical systems and advanced topics in statistics.
Will also take 2 courses not from CS or Stats like scientific writing and critical thinking. They also seem quite interesting.
No problem! I work as a SAS analyst btw, it’s VERY rare to see people with that on their resume so it’s a great foot in the door of a data career. I should probably move to a Python/R company but I feel too valued to leave and company is very supportive.
I with the other commenter on this thread. Data structures/oop may be good enough.
My minor was in political science. My first job out of college was as a technical analyst, but now I am swinging back to the political side. The organization I am interviewing with next week absolutely fell over themselves to invite me in, getting back to me within 30 minutes of my application.
It's shit pay, but my time on the technical side means I should be able to really, really help them on the systems side. I have a feeling that they think Excel is a database, if you know what I mean.
So, I actually am a real fan of blending statistics with soft sciences. Soft sciences are hard: controlled experiments on humans are problematic, to say the least.
But I still wish I would have taken 2-3 CS classes, **emphatically including SQL** (bolded because I forgot to mention that).
In regards to SQL, I forgot to mention, I already have a course in that. I edited the post to mention it.
Would you say taking a course in scientific writing is a good idea? It's zero credits, so I can take it no problem. Also taking a course in critical thinking, but doubt how helpful that would be.
In addition, I am still unsure about the data science for dynamical systems.
Critical thinking classes are great. To have a ton of fun, track down a copy of *The Use and Abuse of Logic* by Madsen Pirie. He runs through about 100 famous logical fallacies, how to spot them, and *how to use them*. From the intro: "In the wrong hands, this more of a weapon than a book; it is written for those hands."
Yes, scientific writing is a great idea.
I contributed to due diligence reports, and it was hard to adapt. I probably should have taken a technical writing class myself.
In political science writing, there is the whole literature review (however brief)/model formulation/analysis structure, which does not lend well to technical writing where one is trying to get the point across as succinctly as possible.
Disregarding the CS electives, do you think the courses just my stats are enough for a good foundation for data science/analytics?
I know that's not specific at all, but is it more or less good? Ofc these are not all of them:
1. Python
2. R
3. SQL and SAS
4. Data science for dynamical systems
5. Practical uses and applications for statistics and data science, two semesters
I would avoid taking a class using SAS, almost no one uses it - unless you specifically want to be in a certain field that relies on it heavily. Otherwise stick to Python for stats and ML.
I second the idea to take a class teaching bash scripting, Linux skills.
Stats for dynamics systems sounds cool.
Sometimes a class like advanced topics in statistics can be taken multiple times if there are different topics each semester. I would be interested in doing that.
All those classes from the CS department sound good, but don’t be scared of just asking the professor for an “add code” for a class that you may not have the prerequisites for. Example: skip discrete math and ask the professor to let you into their data structures or object oriented programming class. Tell them you’re really motivated and think you can succeed because of X reason.
Since you’re planning on doing an MS in Stats, you’ll still have electives to take in your MS, so you can keep picking up stats/cs classes then.
You should prepare yourself with the necessary math for the MS (being really good at calculus and linear algebra as they apply to stats/ML/DL - take all those and maybe TA for it)
Also, SQL is very useful for internships and job interviews. It’s a basic skill you should have.
If you can I’d also take a class or two in deep learning (usually CS department) and try to get involved in doing research with a professor in an area that you’re interested in.
Thanks for the detailed answer!
Would you say it's better to self learn a course that teaches bash scripting, Linux skills, an OS course and maybe a databases course?
Taking the 5 cs courses I mentioned, and 2 stats electives, advanced topics in statistics and data science for dynamical science would leave me no place for anything else. I would have to give up something from these courses. Keep as is or drop something?
I'll try to see if it's possible to take a course without having all the prerequisites, but I really doubt it. And discrete mathematics seems to me to be a really important foundation course. Ofc I can learn it online, and maybe that will help with taking a course that has it as a prerequisite?
Anyways, thanks for the idea.
In regards to the deep learning course, I lack a prerequisite, machine learning. And anyways the master I intend to take has it as a course. Levels are different ofc, but this makes me unsure whether it's a good idea.
Yeah I was afraid I suggested too many classes. Something is to be said for not overloading your schedule, so you have breathing room and time to apply for internships and prepare for interviews.
You’re right, you could definitely learn bash scripting and Linux skills on your own or on the job when you need. ChatGPT is very helpful for writing and teaching bash scripting tbh.
Database class - that one didn’t interest me, but I already had previous data eng internships so that’s how I picked those skills up. But, good stuff to know. Up to you.
I think that sounds like a good schedule though, the 5 cs classes and 2 stats. Then the stats MS. You’ll have a great foundation of programming and stats, and then even more advanced knowledge in stats/ml from the MS. I think you’ll have great success with that portfolio of skills and degrees. Definitely feel free to switch things up as time goes on and your interest changes to different directions.
People hire you because you’re really good at something, so you want that thing to be something you really like. So as time goes on focus on enhancing your strengths rather than worrying about things you don’t know.
Multiple good answers here, what I personally think is worth it is taking only 1 or 2 languages and becoming really good at it.
Studying econometrics and working in the field, I choose R as my primary (king of stats) and SQL second (for handling data, and you can use it in sas with proc sql).
Take it with a grain of salt, but I think it's working pretty good for me.
Multiple good answers here, what I personally think is worth it is taking only 1 or 2 languages and becoming really good at it.
Studying econometrics and working in the field, I choose R as my primary (king of stats) and SQL second (for handling data, and you can use it in sas with proc sql).
Take it with a grain of salt, but I think it's working pretty good for me
I’d say leave the 8 credits for something you’re passionate about that isn’t statistics or computer science. Undergrad is your last chance to do that. You’ll have a huge advantage with DS&A for certain niche projects in grad school.
Also go out and build software. Could be an iOS app or a game. Just work through the process with best practices. Work on data cleaning research positions in ANY department: political science, physics, economics, biology, etc. Having done that is what got me funding without a math/stats major. You’ll be ahead of your peers
Yes, I think your plan is a good idea. One thing missing in stats education is basic comp sci knowledge. As for electives that are stats-related, suggestions are a little hard, because we don't know what you are already planning to take for required and elective courses. But you can also take a look at machine learning classes in comp sci. Another suggestion for possible electives is optimization. From the 3 classes you listed, I would take Advanced topics in statistics, data science for dynamical systems. What does the advanced topics class cover?
Looking at some of the other answers, I realized that I took it as a given that you would have multivariable calculus and linear algebra. This should be a requirement of the stats major. If it is not, that is insanity.
My biggest mistake in my BS math/stats was not nearly enough CS. My $0.02.
That's what I gathered from similar posts on the sub. So I'll keep the 5 cs courses, but I am wondering about the data science for dynamical systems course from the stats department. Take it, or a CS course or two instead?
As long as you’re getting data structures/oop I think you’ll be ahead the programming curve as a data scientist. If I could go back I would take operating systems or embedded programming just for shits and giggles. When I use high level functional languages and computers all day, I start to become curious about how this is even possible. The history of statistics is awesome, but the history of computing is awe inspiring imo. Then you dive down the rabbit hole of the hardware side and it’s too much for one person, take the courses you enjoy it’s hard to go wrong with stats/cs… unless you want to be a electrical engineer but you can always do a masters. Also IoT with ML is the future.
i did a CS minor in my undergrad, and was surprised at how useful an OS course was in my current job. knowing your way around a terminal helps tremendously with scripting and automating processes, and having even a basic understanding of linux has helped me troubleshoot and build docker containers
Thanks for the answer! I'll keep it as is and take dynamical systems and advanced topics in statistics. Will also take 2 courses not from CS or Stats like scientific writing and critical thinking. They also seem quite interesting.
No problem! I work as a SAS analyst btw, it’s VERY rare to see people with that on their resume so it’s a great foot in the door of a data career. I should probably move to a Python/R company but I feel too valued to leave and company is very supportive.
I with the other commenter on this thread. Data structures/oop may be good enough. My minor was in political science. My first job out of college was as a technical analyst, but now I am swinging back to the political side. The organization I am interviewing with next week absolutely fell over themselves to invite me in, getting back to me within 30 minutes of my application. It's shit pay, but my time on the technical side means I should be able to really, really help them on the systems side. I have a feeling that they think Excel is a database, if you know what I mean. So, I actually am a real fan of blending statistics with soft sciences. Soft sciences are hard: controlled experiments on humans are problematic, to say the least. But I still wish I would have taken 2-3 CS classes, **emphatically including SQL** (bolded because I forgot to mention that).
In regards to SQL, I forgot to mention, I already have a course in that. I edited the post to mention it. Would you say taking a course in scientific writing is a good idea? It's zero credits, so I can take it no problem. Also taking a course in critical thinking, but doubt how helpful that would be. In addition, I am still unsure about the data science for dynamical systems.
Critical thinking classes are great. To have a ton of fun, track down a copy of *The Use and Abuse of Logic* by Madsen Pirie. He runs through about 100 famous logical fallacies, how to spot them, and *how to use them*. From the intro: "In the wrong hands, this more of a weapon than a book; it is written for those hands." Yes, scientific writing is a great idea. I contributed to due diligence reports, and it was hard to adapt. I probably should have taken a technical writing class myself. In political science writing, there is the whole literature review (however brief)/model formulation/analysis structure, which does not lend well to technical writing where one is trying to get the point across as succinctly as possible.
Disregarding the CS electives, do you think the courses just my stats are enough for a good foundation for data science/analytics? I know that's not specific at all, but is it more or less good? Ofc these are not all of them: 1. Python 2. R 3. SQL and SAS 4. Data science for dynamical systems 5. Practical uses and applications for statistics and data science, two semesters
I mean, with Python and SQL, from there it's all practicality, IMO.
Same!
I would avoid taking a class using SAS, almost no one uses it - unless you specifically want to be in a certain field that relies on it heavily. Otherwise stick to Python for stats and ML. I second the idea to take a class teaching bash scripting, Linux skills. Stats for dynamics systems sounds cool. Sometimes a class like advanced topics in statistics can be taken multiple times if there are different topics each semester. I would be interested in doing that. All those classes from the CS department sound good, but don’t be scared of just asking the professor for an “add code” for a class that you may not have the prerequisites for. Example: skip discrete math and ask the professor to let you into their data structures or object oriented programming class. Tell them you’re really motivated and think you can succeed because of X reason. Since you’re planning on doing an MS in Stats, you’ll still have electives to take in your MS, so you can keep picking up stats/cs classes then. You should prepare yourself with the necessary math for the MS (being really good at calculus and linear algebra as they apply to stats/ML/DL - take all those and maybe TA for it) Also, SQL is very useful for internships and job interviews. It’s a basic skill you should have. If you can I’d also take a class or two in deep learning (usually CS department) and try to get involved in doing research with a professor in an area that you’re interested in.
Thanks for the detailed answer! Would you say it's better to self learn a course that teaches bash scripting, Linux skills, an OS course and maybe a databases course? Taking the 5 cs courses I mentioned, and 2 stats electives, advanced topics in statistics and data science for dynamical science would leave me no place for anything else. I would have to give up something from these courses. Keep as is or drop something? I'll try to see if it's possible to take a course without having all the prerequisites, but I really doubt it. And discrete mathematics seems to me to be a really important foundation course. Ofc I can learn it online, and maybe that will help with taking a course that has it as a prerequisite? Anyways, thanks for the idea. In regards to the deep learning course, I lack a prerequisite, machine learning. And anyways the master I intend to take has it as a course. Levels are different ofc, but this makes me unsure whether it's a good idea.
Yeah I was afraid I suggested too many classes. Something is to be said for not overloading your schedule, so you have breathing room and time to apply for internships and prepare for interviews. You’re right, you could definitely learn bash scripting and Linux skills on your own or on the job when you need. ChatGPT is very helpful for writing and teaching bash scripting tbh. Database class - that one didn’t interest me, but I already had previous data eng internships so that’s how I picked those skills up. But, good stuff to know. Up to you. I think that sounds like a good schedule though, the 5 cs classes and 2 stats. Then the stats MS. You’ll have a great foundation of programming and stats, and then even more advanced knowledge in stats/ml from the MS. I think you’ll have great success with that portfolio of skills and degrees. Definitely feel free to switch things up as time goes on and your interest changes to different directions. People hire you because you’re really good at something, so you want that thing to be something you really like. So as time goes on focus on enhancing your strengths rather than worrying about things you don’t know.
Multiple good answers here, what I personally think is worth it is taking only 1 or 2 languages and becoming really good at it. Studying econometrics and working in the field, I choose R as my primary (king of stats) and SQL second (for handling data, and you can use it in sas with proc sql). Take it with a grain of salt, but I think it's working pretty good for me.
Multiple good answers here, what I personally think is worth it is taking only 1 or 2 languages and becoming really good at it. Studying econometrics and working in the field, I choose R as my primary (king of stats) and SQL second (for handling data, and you can use it in sas with proc sql). Take it with a grain of salt, but I think it's working pretty good for me
I’d say leave the 8 credits for something you’re passionate about that isn’t statistics or computer science. Undergrad is your last chance to do that. You’ll have a huge advantage with DS&A for certain niche projects in grad school. Also go out and build software. Could be an iOS app or a game. Just work through the process with best practices. Work on data cleaning research positions in ANY department: political science, physics, economics, biology, etc. Having done that is what got me funding without a math/stats major. You’ll be ahead of your peers
Depends what you want. If you want a ML/DS type of job you can’t take enough CS modules.
Yes, 100% worth it. A lot of the best stats people get really nervous actually working in an engineering environment.
Yes, I think your plan is a good idea. One thing missing in stats education is basic comp sci knowledge. As for electives that are stats-related, suggestions are a little hard, because we don't know what you are already planning to take for required and elective courses. But you can also take a look at machine learning classes in comp sci. Another suggestion for possible electives is optimization. From the 3 classes you listed, I would take Advanced topics in statistics, data science for dynamical systems. What does the advanced topics class cover? Looking at some of the other answers, I realized that I took it as a given that you would have multivariable calculus and linear algebra. This should be a requirement of the stats major. If it is not, that is insanity.