Which are top 4 Data Science concepts for a data scientist?

Asked by Disna Rai almost 2 years ago

Answers 1
Gautam Kumar

Gautam Kumar

Building better software for USA based HealthTech and EdTech businesses

There are many important concepts in data science that we can list here. But I understand that won’t be practical. What’s better is that based on the relevancy and demand now in data science, we can point out the top 4 concepts. It would be more relevant, more accurate and beneficial than it is currently in diamonds.

So as of now, the best 4 skills or say data science concepts I would suggest are Machine Learning, Programming, Statistics and Visualization. Basically, you can count down thousands of job professions under these 4 concepts in data science. These are very important elements and need to be understood if you are a data science enthusiast. Let's look at these separately to understand better.

Machine Learning - Machine learning is basically an automated process of use in data science. It makes data-informed predictions in real-time without any human intervention. When working with huge data sets, you can’t always perform tasks efficiently. Because the information is huge in numbers, if you get to work manually, it would take years to resolve simple big data. Machine learning is basically an automatic training process to eliminate a lot of work.

Programming - Programming has always been the most important skill for a data scientist. Without it, it makes no sense for you to do a data science course and career. A candidate with a background in software is self-sufficient to work with data without any outside help. For instance, instead of looking for external resources, a programmer can query data just by using a black box tool or a dedicated program.

Statistics - Statistics is at the core of sophisticated machine learning algorithms. In data science, it captures and translates data patterns into actionable evidence. It’s not all about numbers and algorithms also, various processes in data science are needed to gather, analyze, review, and draw conclusions. Because you will need to apply quantified mathematical models to appropriate variables.

Visualization - Data visualization is simply the graphical representation of information and data. It deals with visual elements like charts, graphs, and maps. Data visualization tools are very important to offer accessible ways so data scientists can see and understand trends, outliers, and patterns available in data. In other words, it makes your task easier.

Some other important data science concepts are Statistics, Operationalization, Strategy, Engineering etc. However when looking at it deeply, they all consist of the top 4 data science concepts mentioned above. Get to know your subject before making a big decision related to it. If you want to know the different areas and specializations in data science , feel free to ask. I have done some data science courses myself to know much about this subject.



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