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Hey! currently I am pursuing a Bachelors degree in marine engineering but I think my interest lies in data science and analytics. I am a college sophomore. Please advice.
#college #science
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Herman’s Answer
To me, it seems like you have 3 primary options, assuming you really want to be working in data science / analytics:
1) Switch your major from marine engineering to something more aligned with data science (Computer Science, Statistics, etc.). This may be difficult to do depending on your school
2) Complete your marine engineering degree, but develop data science skills to pivot to that field
3) Complete your marine engineering degree, and follow it up with a masters in analytics / data science
#1 would be the most straight forward IF you can do it without having to, say, repeat a year (which will cost a lot more money).
In the case that #1 is not feasible, #2 should be a viable route. As someone who's worked in data science, your major matters, but the skill set and specific experience is more critical. Since data science is still a developing field in its modern sense, people from all sorts of quantitative majors pivot to data science: CS, stats, physics, all types of engineering, etc.
What you'll need to do is demonstrate to employers that you can do well in an analytics / data science role. You'll be able to do that via:
1) Developing core skills relevant to data science
2) Applying those skills in a practical way
For #1, the first thing you'll want is a solid foundation in stats and computer science. If you've already taken these courses as part of your engineering degree, great. If not, no worries - try to enrol in them at your university. If that's not possible, then you can still just do them on Coursera or MIT Opencourseware online in your spare time! Another course I'd recommend is basic database management (ex. relational database theory). These are foundational courses for the field.
Then, you'll want to start picking up tools. Python is perhaps the most commonly used language in data science. Once again, there are many resources online that you can leverage to learn Python for data science & analytics. R is also common. SQL is another tool that'll be helpful (this is used for querying data sets).
Once you have the skills and knowledge: apply them! The easiest way to do this is through personal projects. That is, pick a problem / data set that you want to analyze and make a solution! Kaggle is a great source for clean datasets, so it's great for beginners. They'll even state what the "challenge" is for that dataset, so it's all well defined for you.
As you progress, I encourage you to start doing original projects. That is, make up your own problem statement and find and cleanse your own data. The data collection, cleansing, and engineering process is *much* harder than it seems and takes up most of the time. However, this is what real data science looks like. For example, suppose you're a basketball fan. Maybe you could try to build a model that will predict whether a rookie will be a future all-star or not? It's best to take this project completely end-to-end: from the raw data all the way to a simple interactive tool for the model that users can play with.
Overall, you should be able to get into data science / analytics with hard work, even from marine engineering.
Develop core knowledge (stats, CS, databases) via online learning (Coursera, MITOCW)
Learn relevant tools and languages (Python, SQL, R, Excel)
Apply your knowledge and skills to simple projects (Kaggle competitions)
Apply your knowledge and skills to personal projects created by you end-to-end
Use these projects to create your portfolio, and try to secure an internship in data science / analytics
1) Switch your major from marine engineering to something more aligned with data science (Computer Science, Statistics, etc.). This may be difficult to do depending on your school
2) Complete your marine engineering degree, but develop data science skills to pivot to that field
3) Complete your marine engineering degree, and follow it up with a masters in analytics / data science
#1 would be the most straight forward IF you can do it without having to, say, repeat a year (which will cost a lot more money).
In the case that #1 is not feasible, #2 should be a viable route. As someone who's worked in data science, your major matters, but the skill set and specific experience is more critical. Since data science is still a developing field in its modern sense, people from all sorts of quantitative majors pivot to data science: CS, stats, physics, all types of engineering, etc.
What you'll need to do is demonstrate to employers that you can do well in an analytics / data science role. You'll be able to do that via:
1) Developing core skills relevant to data science
2) Applying those skills in a practical way
For #1, the first thing you'll want is a solid foundation in stats and computer science. If you've already taken these courses as part of your engineering degree, great. If not, no worries - try to enrol in them at your university. If that's not possible, then you can still just do them on Coursera or MIT Opencourseware online in your spare time! Another course I'd recommend is basic database management (ex. relational database theory). These are foundational courses for the field.
Then, you'll want to start picking up tools. Python is perhaps the most commonly used language in data science. Once again, there are many resources online that you can leverage to learn Python for data science & analytics. R is also common. SQL is another tool that'll be helpful (this is used for querying data sets).
Once you have the skills and knowledge: apply them! The easiest way to do this is through personal projects. That is, pick a problem / data set that you want to analyze and make a solution! Kaggle is a great source for clean datasets, so it's great for beginners. They'll even state what the "challenge" is for that dataset, so it's all well defined for you.
As you progress, I encourage you to start doing original projects. That is, make up your own problem statement and find and cleanse your own data. The data collection, cleansing, and engineering process is *much* harder than it seems and takes up most of the time. However, this is what real data science looks like. For example, suppose you're a basketball fan. Maybe you could try to build a model that will predict whether a rookie will be a future all-star or not? It's best to take this project completely end-to-end: from the raw data all the way to a simple interactive tool for the model that users can play with.
Overall, you should be able to get into data science / analytics with hard work, even from marine engineering.
Herman recommends the following next steps:
Updated
Jess’s Answer
Take classes on data science and analytics to see if you're really interested in it. Another option is to minor in those majors. You can switch major completely once you're sure you want to do it (unless you completely hate your current major right now).
I agree, pursuing a minor is a good way to build skills without completely jumping ship before knowing what that really means. Sometimes it can mean that your original major becomes your minor and your new minor becomes your major too, which is reasonable.
Charles Bosse
Updated
Patryk’s Answer
Hi Skaa
I would recommend that you talk to your college advisor about this. They would be able to tell you more about the program and if it might be a good fit for you. If you are very comfortable with statistics, computers, analysis, etc. then maybe analytics is a good choice for you. Maybe you can take an introductory course for data science/analytics to see if you like it. If you are really passionate about analytics and data science, then you should also research potential careers and see if those are jobs you see yourself doing!
Patryk
I would recommend that you talk to your college advisor about this. They would be able to tell you more about the program and if it might be a good fit for you. If you are very comfortable with statistics, computers, analysis, etc. then maybe analytics is a good choice for you. Maybe you can take an introductory course for data science/analytics to see if you like it. If you are really passionate about analytics and data science, then you should also research potential careers and see if those are jobs you see yourself doing!
Patryk
Yes! It's good to talk to a human! It's also important to remember to focus on what you want and not what the smoothest path is.
Charles Bosse
Updated
Charles’s Answer
On one hand, you need to be aware of the resources, including time, that you have available, and on the other hand, you need to step back from the idea of pursuing something simply because of sunk cost. You can ALWAYS switch majors, even though it may cost you a year or two more education or significantly complicate your course load, or in the worst case require switching schools. If you have had a chance to try it and it's really the right thing for you, then that's worth while. If you haven't tried it and are just unsure, then you need to find a way to make sure you aren't "out of the frying pan and into the fire" so to speak, and do some classes and/or an internship before switching majors.
Updated
Vineeth’s Answer
Dear Harman,
My suggestions would be like something below.
1. You complete your marine engineering. And learn more about data analytics and data science. These days we have data everywhere and those who can really crack the data problem survive in any industry. I am sure you can use your marine engineering knowledge and if you learn more about data science you can use the same in that field. It can be an innovation. It may scale up your career.
2. Learn and opt for some certifications in Data science and try for a career in that area.
Where ever you are learn more about what is your passion and get into that career.
My suggestions would be like something below.
1. You complete your marine engineering. And learn more about data analytics and data science. These days we have data everywhere and those who can really crack the data problem survive in any industry. I am sure you can use your marine engineering knowledge and if you learn more about data science you can use the same in that field. It can be an innovation. It may scale up your career.
2. Learn and opt for some certifications in Data science and try for a career in that area.
Where ever you are learn more about what is your passion and get into that career.