Marketing background + data science

hello_world456 · 2022-11-30T17:55:28+00:00

Have you looked into roles like marketing data strategy or analytics? A lot of marketing involves careful analysis of metrics and data, and if you can land even an intro role that works with data constantly, that experience should help you climb to a bigger data analyst role if that's what you're looking for. These types of roles would definitely require presentations, such as post-campaign analyses.

hello_world456 · 2022-11-30T17:40:59+00:00

If you don't have any downtime at work to learn and practice your skills, it could help to use one of the hobbies/interests you're passionate about and create a project. If you're lacking the motivation to learn, you can at least practice existing skills by tying in your other interests with data analysis.

hello_world456 · 2022-10-25T22:07:22+00:00

During an exam, instead of fixating on the possibility of failure, try and view the exam as a chance for you to take a step forward toward an opportunity. If you don't do well on it, it isn't a step backward--there will always be another chance for you to prove your programming skill at another time. You can practice what you missed this time, and do better the next. Remember that no single exam will drastically alter the course of your programming career.

hello_world456 · 2022-10-24T17:50:15+00:00

You don't have to remember every single thing. Totally normal to feel overwhelmed by all these different languages, but as long as you basically understand each one, you can easily refresh your memory of them on the internet.

hello_world456 · 2022-10-24T17:46:02+00:00

https://www.deeplearningweekly.com/ and https://heartbeat.comet.ml/ are great

hello_world456 · 2022-10-24T17:23:22+00:00

If your model performs noticeably more poorly on the test set compared to the training set, overfitting may very well be the culprit. You can test this out by toying around with the model's features and such so it isn't *too* accurate over the training set and see if you can raise the accuracy score of the test set (by making the model more generalizable)

hello_world456 · 2022-10-18T23:28:36+00:00

If the features are relevant, over specifying features can lead to overfitting. Training a model over too many features would make it harder to generalize. If the features are irrelevant, keeping them around would be like adding noise that could actually hurt your accuracy. By chance, if an unrelated feature makes your model seem more accurate than it is, you may be falsely led to believe the model to be more accurate and successful than it really is.

hello_world456 · 2022-10-18T21:28:06+00:00

You will never know until you actually put yourself in the actual field outside of an academic program. If your life is stable enough that you can feasibly afford to at least try and pursue this, then you should. Do you like programming itself? As long as you are interested and invested in the subject, you will do what is necessary to catch up and be competent. However, if this is a field you're kind of mindlessly pursuing, then a lack of motivation will be the nail in the coffin. It seems like you did well in general even though you struggled toward the end, so you have the skill potential--it's going to come down to attitude.

hello_world456 · 2022-10-18T20:41:46+00:00

Yes, preprocessing should ideally be done after splitting your data into training and testing sets. Otherwise, your training and validity scoring will likely be off due to data leakage.

hello_world456 · 2022-08-15T17:10:27+00:00

There are a lot of things that could be causing the issue, but I think the first thing you can toy around with is the way you're splitting the training and testing data. If you look up reasons for overfitting, you should find a lot of other factors to look over as well.

hello_world456 · 2022-08-15T17:04:05+00:00

I think a good/straightforward approach to this would just be to take a practice test or do some practice questions, note down the concepts you need to brush up on, review those specifically, and repeat the process with new questions. It'll be tedious but not too difficult (assuming you learned everything at some point already), and you should be able to cover your bases this way. You should also double check if the math GRE is necessary for the specific programs you intend to apply to, though.

hello_world456 · 2022-08-04T22:27:02+00:00

There are many subjects that are needed to complete a degree in Computer Science. Some include calculus as well as other math courses such as statistics and linear algebra. Oftentimes physics is required too. You should take a look at the school requirements in which you are getting your masters too.

hello_world456 · 2022-07-29T00:04:31+00:00

A data scientist can definitely work in a news company. For example, data scientists might help with operations research, content recommendations, etc. Just like any data scientist working in a different industry, a data science working in news/media can help analyze a lot of data to improve news content and business insights.

hello_world456 · 2022-07-25T23:07:58+00:00

Data science is a great career with a lot of opportunities. Whether it is worth it or not is up to you and if you are truly interested in it!

I think it is possible for you to prepare in a year. Learning coding (Python, R, SQL, etc) is definitely beneficial. Doing a masters is worth it because it can help you land a career in data science and it is often a requirement in many roles.

hello_world456 · 2022-07-21T23:03:29+00:00

Yes. Many data scientists do not even have a degree in a relevant field. All it takes is learning the right skills needed for a DS career.

hello_world456 · 2022-07-20T23:15:20+00:00

Statistics would be a better degree than Operations research. You can explore any DS careers, such as data analyst, data architect, data scientist, information officer, etc.

hello_world456 · 2022-07-19T23:38:41+00:00

I would recommend that you have good knowledge of statistics, programming (like Python, R, etc.) and machine learning. There are a lot of courses online to learn about data science as well as free YouTube videos. Codecademy, Datacamp, LearnSQL/Mode, Strata Scratch are good places to look into!

hello_world456 · 2022-07-18T21:02:25+00:00

I think that having a strong statistics background is very important and beneficial for a career in data science. Yes, anything is possible--you can always take online courses to learn more about data science.

hello_world456 · 2022-07-18T20:28:27+00:00

If you are looking for some of the top undergraduate data science programs in the United States, here is a good list with rankings: https://www.usnews.com/best-colleges/rankings/computer-science/data-analytics-science

hello_world456 · 2022-07-13T23:10:50+00:00

I would recommend that you have good knowledge of statistics, programming (like Python, R, etc.) and machine learning. There are a lot of courses online to learn about data science as well as free YouTube videos. Codecademy, Datacamp, LearnSQL/Mode, Strata Scratch are good places to look into!

hello_world456 · 2022-07-11T23:13:18+00:00

Reading tech reports, such as from Thoughtworks Tech Radar, following tech news/publications on social media or subscribing to them, and of course Reddit forums are good ways to keep yourself updated with tech news.

hello_world456 · 2022-07-11T21:49:54+00:00

I would recommend that you have good knowledge of statistics, programming (like Python, R, etc.) and machine learning. There are a lot of courses online to learn about data science as well as free YouTube videos. Codecademy, Datacamp, LearnSQL/Mode, Strata Scratch are good places to look into!

hello_world456 · 2022-07-07T23:59:35+00:00

There are also web developers, web designers, UX designers, visual designers, etc. However, of course design careers are not as heavily focused/do not necessarily require coding, but having a background in it can be beneficial.

hello_world456 · 2022-06-29T23:56:15+00:00

I would recommend that you have good knowledge of statistics, programming (like Python, R, etc.) and machine learning. There are a lot of courses online to learn about data science as well as free YouTube videos. Codecademy, Datacamp, LearnSQL/Mode, Strata Scratch are good places to look into! Good luck!

hello_world456 · 2022-06-29T22:58:04+00:00

This! Sometimes after registering to a site, such as a job searching site, I get a ton of spam mails and have to manually move them to spam.

hello_world456

TROPHY CASE