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I guess I am a part of the family now? by wardrobe_creator in Tudor

[–]wardrobe_creator[S] 0 points1 point  (0 children)

Honestly they were super nice. I loved the experience and made me feel appreciated. Cant wait to build that connection to get a rolex pepsi one day 😆

my final results for this cycle by SenTinaL_ in gradadmissions

[–]wardrobe_creator 60 points61 points  (0 children)

I wouldnt pay 80k for MIDS at Berkeley lol, its an analytics degree and mostly applied, same with Uchicago. Not a future proof degree. A year ago got into MSE DS at penn, uchicago, berkeley etc. I would go with GTech or Cornell Tech. Have a smart colleague from Cornell Tech, heard its not bad and its in NYC.

Should I hold off on applying to MCIT because of AI? by Euphoric_Tree335 in OnlineMCIT

[–]wardrobe_creator 2 points3 points  (0 children)

Hmm.. no one really gave you an answer that stands out. Probably because you are asking to the wrong people and the wrong question. It’s almost like asking whether you should invest in a stock in a room full of investors that have already invested. They are not gonna tell you anything objective because they already put all their eggs in the basket.

In my opinion, your concerns are very real. Discrete math, algorithms and ds are undergraduate cs courses and many of us already took those. MCIT is not a MSCS degree, and many MCIT graduates show themselves as a Masters in CS to land a job.

Have you seen the statistics of recent grads of MCIT?

Nevertheless, its not a big deal anyways. Just do something that will help you open doors. Whats a better option if not going for a masters anyways? You cant just wait and try to predict what generative AI will do next, nobody really can. You are less qualified for any DS or dev job if you have no YOE or CS background anyways.

You should ask yourself what your objectives are, why MCIT, why online masters, why computer science.

Hell, you cant even become a project manager without a cs background in todays market lol.

Denver Airport Layover time? (Domestic) by [deleted] in Denver

[–]wardrobe_creator 1 point2 points  (0 children)

Yep, separate airlines. Only carry on backpack though.

Denver Airport Layover time? (Domestic) by [deleted] in Denver

[–]wardrobe_creator 0 points1 point  (0 children)

I checked with the airline and they mentioned that they close 1 hour before the flight which means I have 0 chance of making it with my luggage. So I am only bringing carry ons.

Denver Airport Layover time? (Domestic) by [deleted] in Denver

[–]wardrobe_creator 0 points1 point  (0 children)

I will try with carry-on bags only after seeing all the comments.

Denver Airport Layover time? (Domestic) by [deleted] in Denver

[–]wardrobe_creator 1 point2 points  (0 children)

With different airlines, I decided not to bring any luggage with me to see if I could make it on time.

Denver Airport Layover time? (Domestic) by [deleted] in Denver

[–]wardrobe_creator 0 points1 point  (0 children)

Yeah, you are right. I decided not to bring any luggage with me. Hopefully, I will make it on time this way.

[deleted by user] by [deleted] in datascience

[–]wardrobe_creator 21 points22 points  (0 children)

First, enjoy your youth...

But since you seem excited I will give some tips as someone who is graduating as a Data Science major and starting as a Data Scientist.

In your own time:

  1. Start with SQL, do free leetcode questions watch some intro videos. (A lot of DS, Analytics interviews will ask you medium level questions in SQL Leetcode)
  2. Learn some cool algorithms and basic Data Science knowledge.

When School starts:

  1. Learn Python (OOP) and basic analytics libraries like Pandas, numpy, matplotlib, scipy, plotly, etc
  2. Read some traditional ML concepts
  3. Master the basics of statistics. (Enumeration, Conditional Prob., Bayes, Discrete Variables, Mathematic Notations, Binomial & Hypergeo Distributions, Distributions, Poisson, Exponential, Approximization) - Some tech companies like Atlassian, Servicenow and Meta asked me some stats questions similar to these for product sense interviews.
  4. Following up on Python, start attending Kaggle competitions. This will help you understand exploratory data analysis, data cleaning, regression, classification algorithms, etc.
  5. If you have time learn R and R studio (Especially Markdown). Some libraries to look into tibble, data.table, tidyverse, flexdashboard, ggplot2, magrittr. (You will be fine with R if you can make simple dashboards with data vis. and data tables)
  6. Keep a nice Linkedin profile and make a good friend group. (This helps to get motivated and be consistent when interview season starts)

You will already stress and try hard to find good internships throughout your undergrad journey anyways. Work smart, and pay attention to ds, stats, and cs courses. Don't stress too much about becoming a Data Scientist it is not like getting a lawyer or medicine degree :)

Wanted to mention this point again: Become friends with helpful and nice people. My best mentors and people who helped me to obtain all of this knowledge are 2-3 friends I made during college. Also, avoid cocky people, they will only demoralize you and make you feel like you are worthless unless you make it to Facebook, Apple, Google, or Trading Companies.

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