I’m currently proficient in Python and SQL, and I’ve observed that some job advertisements emphasize experience in C or C++. In my academic training, the focus was exclusively on Python, R, and SQL without any exposure to C/C++. I’m keen to understand how these languages integrate into data science projects and whether dedicating extra time to learn them would enhance my career opportunities.
c and c++ can rly boost heavy computations. if you bump into performance chokepoints, even a little knowlege can save u. not every datascience role needs it, but it could be neat for low level tweaking.
Experience indicates that while Python and R are favored for ease of use in prototyping and analysis, C and C++ offer significant benefits when it comes to performance enhancement. In my work, I have resorted to these languages for parts of code requiring high computational efficiency, particularly for algorithms that need to run at scale or within real-time systems. Moreover, many high-performance libraries frequently used in data science rely on C/C++ under the hood. Therefore, gaining familiarity with them can provide a competitive edge in roles where optimizing execution speed is essential.
hey, i think c++ can be neat for custom, speedy device even if it seems extra work sometimes. i’ve seen it patch up performance issues in niche cases. have u seen instances where tinkering with c made a diff? curious to hear ur thoughts!
i think having a basic knowlege of c/c++ can be a secret weapon for optimizing heavy code sections, even if its not your daily tool. it comes in really handy when you need fine control over performance bottlenecks in computation-intensive tasks.
My experience with data science projects suggests that familiarity with C and C++ can be highly advantageous, though they are not always immediately essential compared to Python, R, or SQL. In one case, I integrated a custom C++ module to handle a computationally demanding simulation, which notably reduced processing time. This approach not only added performance gains to the application but also enriched my problem-solving toolkit. Even a working knowledge of these languages can prove useful in optimizing critical code paths in data-intensive projects.