Thank you for the feedback, I appreciate it. I will try to keep a balance between technical and general videos. I have a few videos lined up about the progress of my side project.
Hey thanks for the detailed overview, it helps to get a clearer perspective into the field! If I may ask, how long did it take you to reach your actual position, and on typical schedule how many hours a day/week do you spend working?
Thank you for the feedback. Generally, my schedule fluctuates based on the season. We are much busier in Q2 and Q3 but this past 6 months we’ve been short staffed so I needed to do a little more heavy lifting. When I first joined as an intern I was putting in probably 60 hours a week then eventually things started slowing down. These days, as long as I plan well enough and there are no fires to be put out, I can safely say 40 hours a week is sufficient. There are occasions where things happen and I need to participate in discussion or provide support after hours for migrations but those are rare. It took me about 3 months to convert from an intern to a full time position.
Hey Ranesh since you are a data scientist I would like to ask if majoring in computer science or statistics is more worth it? I am a junior in high school and Ik that data science is really just very complex applied stats. Maybe something like a combination of major in CS and minor in stats would work? Would that be a good combination because it can lead to other opportunities like data engineer or just SWE? Thanks.
Hey Alex, great question and it’s amazing that you’re thinking about this while you’re still in high school. Here’s my take: I would stick to a CS major and possibly do a double major with stats or maths. If you can’t do a double major, a minor in stats will suffice. The reasoning behind this is because from my experience, a data science undergraduate is basically just a makeshift degree combining some stats, comp sci and business. They don’t really curate it for data science specifically. You won’t be able to dive deep into any concepts. If you do a stats only degree, you might get great theory and understanding of statistical concepts but lose out on fundamental programming skills and concepts. Thats fine if you already know how to code but even so, I would encourage a CS degree. It’s just way more marketable and flexible which will allow you to pivot into almost any tech career in the future. I changed my major from a CS degree to a DS degree and I think I would’ve benefited more from a CS degree. Almost all of the complex ML I learned came from work experience or external self learning. I just don’t think undergraduate degrees are sufficient for data science just yet so I would probably do a CS undergraduate and a DS graduate degree. Hope this helps
Theoretically you could learn all of this outside of school without a degree if you had the will to do so but a CS degree on paper is just more valuable these days, imo
Ranesh, I've just completed the Google Data Analytics certificate, and since I have plenty of time during this break and the next semester, I'm considering starting to learn IBM Data Science. I noticed that you completed this certificate through LinkedIn, but my concern is that I'm not a computer science student, and I don't know how to code. Do you think it's a good idea for me to pursue IBM Data Science despite my lack of coding knowledge?
Hi Tharun, I would recommend starting with some projects first to get yourself more experience and then move onto the IBM Data Science course. Taking courses are great but if you don't apply the skills you learn, you won't maximize your learning ability. You don't need to be a computer science student to know to code, I think it's something everyone should have a basic understanding of. I believe they did teach coding in R in the Google Data Analytics certification too.
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I personally enjoy the more technical content and like how you explain things (i.e shadow model) with annotations.
Thank you for the feedback, I appreciate it. I will try to keep a balance between technical and general videos. I have a few videos lined up about the progress of my side project.
Great vid!
Thanks lemonade!
Hey thanks for the detailed overview, it helps to get a clearer perspective into the field! If I may ask, how long did it take you to reach your actual position, and on typical schedule how many hours a day/week do you spend working?
Thank you for the feedback. Generally, my schedule fluctuates based on the season. We are much busier in Q2 and Q3 but this past 6 months we’ve been short staffed so I needed to do a little more heavy lifting. When I first joined as an intern I was putting in probably 60 hours a week then eventually things started slowing down. These days, as long as I plan well enough and there are no fires to be put out, I can safely say 40 hours a week is sufficient. There are occasions where things happen and I need to participate in discussion or provide support after hours for migrations but those are rare. It took me about 3 months to convert from an intern to a full time position.
Hey Ranesh since you are a data scientist I would like to ask if majoring in computer science or statistics is more worth it? I am a junior in high school and Ik that data science is really just very complex applied stats. Maybe something like a combination of major in CS and minor in stats would work? Would that be a good combination because it can lead to other opportunities like data engineer or just SWE? Thanks.
Hey Alex, great question and it’s amazing that you’re thinking about this while you’re still in high school. Here’s my take:
I would stick to a CS major and possibly do a double major with stats or maths. If you can’t do a double major, a minor in stats will suffice. The reasoning behind this is because from my experience, a data science undergraduate is basically just a makeshift degree combining some stats, comp sci and business. They don’t really curate it for data science specifically. You won’t be able to dive deep into any concepts. If you do a stats only degree, you might get great theory and understanding of statistical concepts but lose out on fundamental programming skills and concepts. Thats fine if you already know how to code but even so, I would encourage a CS degree. It’s just way more marketable and flexible which will allow you to pivot into almost any tech career in the future. I changed my major from a CS degree to a DS degree and I think I would’ve benefited more from a CS degree. Almost all of the complex ML I learned came from work experience or external self learning. I just don’t think undergraduate degrees are sufficient for data science just yet so I would probably do a CS undergraduate and a DS graduate degree. Hope this helps
Theoretically you could learn all of this outside of school without a degree if you had the will to do so but a CS degree on paper is just more valuable these days, imo
Custoomer attrition 🙊
Oops 😂
Ranesh, I've just completed the Google Data Analytics certificate, and since I have plenty of time during this break and the next semester, I'm considering starting to learn IBM Data Science. I noticed that you completed this certificate through LinkedIn, but my concern is that I'm not a computer science student, and I don't know how to code. Do you think it's a good idea for me to pursue IBM Data Science despite my lack of coding knowledge?
Hi Tharun, I would recommend starting with some projects first to get yourself more experience and then move onto the IBM Data Science course. Taking courses are great but if you don't apply the skills you learn, you won't maximize your learning ability. You don't need to be a computer science student to know to code, I think it's something everyone should have a basic understanding of. I believe they did teach coding in R in the Google Data Analytics certification too.