7/25/2023 0 Comments Statistics basics for data science![]() So… is there a lot of math here? Honestly, for this role what you need is a practical understanding of statistics, not theoretical statistics. A combination of coding in a simple language like R, with some theoretical background about statistics should be a good fit, and there are many courses that get this mix just right. However, classical statistics sits on a solid tradition and a firm theoretical ground. You don’t need to take a classical statistics course with nothing but theorems unless you want to become a statistician/mathematician yourself. You should get familiar working with tools such as ggplot2 (in R), or matplotlib’s pyplot (in Python). The bread and butter of almost any kind of Data Science work. I would suggest R in case you are starting from scratch, and Python if you have at least some programming background. The skills you should probably look forward to learning are: ![]() To perform data analysis, you need to understand how to collect and organize data, how to extract the information you want, and how to interpret the results. Data Analysis: Making sense of dataĭata analysis involves finding patterns and trends in large amounts of data with the goal of providing insights that can help solve problems and improve business decisions. Most of the work I’ve been recently doing lies in the field of remote sensing, trying to make sense of vasts amounts of satellite data. I acquired what we now call Data Skills mostly in Computational Statistics courses, using the old-fashioned method of reading books, and doing research. I believe Data Science is mostly about coding, statistics, and domain-specific knowledge.īy the way, my formal education has been an MSc and a PhD in Applied Mathematics. ![]() Honestly, it’s a good idea to stop making things seem more complicated than they actually are. This post is an honest attempt to try to answer that question. I get often asked what is the role of mathematics in the data industry. “When we are in front of a blackboard, we call it statistics when in front of a computer, it becomes machine learning and in a business presentation, we refer to the process as artificial intelligence“.
0 Comments
Leave a Reply. |