Which is better data science or competitive programming?

Competitive programming solves problems by implementing some algorithms by yourself. Data science, in other hand, is also solving problems, but it doesn’t involve algorithms implementation to it. Also, it’s worth to pursue if you want to become a software engineer because it has lots of algorithm implementation to it.

Is there a lot of competition in data science?

And there are a lot of competitions on Kaggle that you can enter to sharpen your data science skills. These competitions range from identifying wheat using image analysis to predicting lung function decline due to pulmonary fibrosis.

Is Data Science hard for non programmers?

Any organization looking to hire a data scientist requires someone with a diverse skill set and not just programming. No doubt, programming is an essential skill for a data scientist job but that does not mean that you have to be a die-hard programmer to pursue a career in data science.

Is competitive programming waste of time?

Definitely no. Competitive programming requires very little of language knowledge, and my C++ skills were below average even from competitive programming point of view. I learned more C++ in first several weeks of my internship at Google than I learned by doing competitive programming for multiple years.

Is competitive programming necessary?

So, is competitive programming required to do well in interviews? Though it will definitely help you in getting to the solution faster and coding it quickly if you are good at CP. So, the short answer is: It is not essential but is definitely something that we would encourage you to try and see if you like it.

Is data scientist still in demand?

While career growth may shift by industry and economic activity, the rise of data science is on an overall upward trend. With Glassdoor ranking data science as the #2 job in America for 2021, exploring demand trends within the field can only lead to beneficial insights.

Is data science harder than computer science?

Data science is easier to summarize than computer science. This discipline focuses almost entirely on collecting, organizing, and analyzing data and can be described as a mix of math, statistics, and computer science.

Is it worth pursuing competitive programming in data science?

Data science, in other hand, is also solving problems, but it doesn’t involve algorithms implementation to it. Therefore, it’s a different field. It still worth pursuing competitive programming if you want to solve a new data science problem that don’t have any implementation of given ML algorithm.

What is a data science competition?

Overall, data science competition that exists mostly on analyzing your data and also modelling to achieve higher accuracy. You do not write the algorithm explicitly just like on competitive programming that is from scratch, but you only use the ready-to-use packages for such algorithms.

Why is competitive programming so challenging?

Competitive programming has become a popular competition on computer science community until now. For me, competitive programming is challenging because you have to solve the problem and solve it using algorithms that exist or implementing your own algorithm.

What is the best online programming competition site?

TopCoder TopCoder is one of the most popular platforms for online programming competitions. Anyone can join the Topcoder Community to participate and compete in challenges. The TopCoder Community has majorly 4 segments – Design, Development, Data Science, and Competitive Programming.