Editor's Note: If you're interested sharing your data science and AI expertise, you can apply to write for our blog here. Data Science as a discipline and profession demands its practitioners possess various skills, ranging from soft skills such as communication, leadership to hard skills such as deductive reasoning, algorithmic thinking, programming, and so on. But there's a crucial skill that should be attained by Data Scientists, irrespective of their experience, and that is writing. Even Data Scientists working in technical fields such as quantum computing, or healthcare research need to write. It takes time to develop strong writing ability, and there are challenges that Data Scientists confront that might prevent them from expressing their thoughts easily.

Algorithms tend to scare a lot of ML practitioners away, including me. The field of machine learning arose as a method to eliminate the need to implement heuristic algorithms to detect patterns, we left feature detection to neural networks. Still, algorithms have their place in the software and computing domain, and certainly within the machine learning field. Practising the implementation of algorithms is one of the recommended ways to sharpen your programming skills. Apart from the apparent benefit of building intuition on implementing memory-efficient code, there's another benefit to tackling algorithms which is the development of a problem-solving mindset.