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Dive into Algorithms

 
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Hello. With too many different programming languages out there, what do you think about learning multiple ones? I started off with C, then move to Java, C# but to be honest I was just learning the basics (looping, conditionals, functions). I never actually built something meaningful. I am told projects are a great way to hone one's coding skills so I got this great book from No Starch (Python Crash Course) and Python is now my favorite language. After getting through with PCC, I plan to get into Data Science, particularly Deep Learning for medical research, so your book definitely catches my eye. I will take on Linear Algebra and Statistics as I am told they are both rather important in DS. Say, do you think it is a good idea to stick with a single language and get really good at it or should one learn at least a second one? I've stuck to Python for a while now and am really enjoying it.
 
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Welcome to the Ranch

Most people think one should learn multiple languages. Have you ever tried LISP or Forth? Now those are different languages
 
R Castro
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Campbell Ritchie wrote:Welcome to the Ranch

Most people think one should learn multiple languages. Have you ever tried LISP or Forth? Now those are different languages

I haven't but will definitely take a look at both of them. Thanks!
 
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Hi R Castro,

It's a great question. Maybe I can answer by giving you an algorithm for a coding career:

(1) Learn one language really well - this is your language #1.
(2) Get a job based on your expertise in language #1.
(3) At your job, pick up random skills not related to language #1, pick up little snippets of other languages, and spend a little spare time studying other languages and other things at least at a shallow level.
(4) Look at job openings. If there are lots of great jobs that interest you related to language #1, just keep honing your expertise there and get jobs related to that. Otherwise, rely some of the random skills you learned in step #3 to get the jobs you like best.
(5) Repeat steps 3 and 4. If the available jobs that interest you are consistently not related to language #1, you can consider making another language your "main language". Otherwise, stick with language #1 and become a top expert in it.
(6) As you progress in your career, you'll pick up lots of skills and languages in a way that almost feels effortless, just because every job will teach you a little bit every day, and you'll get a clearer idea of what your main focus should be.

To answer more specifically, I'm also a data scientist, and I've noticed that Python is dominant in DS. At my last job, I used Python every day but I picked up random skills related to Spark and Hadoop. Currently, I still work with Python every day but I've been polishing my SQL skills and even doing a little PHP. I would think that if you're applying to data science jobs, being able to say that you're really good at Python, that it's your main language, will get you far in job interviews. But it will help if you have at least some basic skills in other areas, especially SQL. I hope this helps. Good luck! And all the best,

Bradford
 
R Castro
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I'm also a data scientist, and I've noticed that Python is dominant in DS.

BradfordIf I may, Bradford, do you know which is more used in Bioinformatics for say, cancer reasearch? Natural Language Processing or Computer Vision? Thanks a lot! Highly appreciate it.
 
Bradford Tuckfield
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Hi R Castro,

I'm not an expert on that field, but I think that computer vision is much more common than NLP in cancer research. For example, here's a review of dozens of computer vision research articles just about one type of cancer (esophageal): https://ieeexplore.ieee.org/abstract/document/8772048. I've seen NLP used for chemistry research to identify new uses for chemical compounds, but I can't think of many NLP applications to cancer research that I've seen. Best regards,

Bradford
 
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https://cacm.acm.org/news/244370-cobol-programmers-are-back-in-demand-seriously/fulltext

Didn't this happen last year??
 
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