DIFFERENT LANGUAGES AND SKILLS A DATA SCIENTIST NEEDS TO BE PROFICIENT IN

Data science is a field which requires multiple types of skills and expertise. It requires in-depth knowledge of both technical and business acumen. This is why professionals from different fields can enter big data. There are different certification courses, diplomas, bachelor and master courses, and boot camps which one can attend to get trained in different aspects of data science.

Different skills and subjects that one needs to get trained in are:

Python coding

One of the greatest programming languages ever created, which is widely used by most of the data scientist across the globe as it is one of the most versatile coding languages which is helpful throughout the data pipeline. It can import data, format data, create data sets and also find data sets from a different search engine.

R programming

This is a programming language specifically created for a data science purpose, which makes it one of the most widely used analytical tools. Though it takes a bit of time to master, however, it is not impossible if one gets ample training period and real-world practical knowledge.

SQL coding

This is one of the basic query languages which is being used since the very early days of coding. One should be skilled in writing and executing queries in SQL. Through SQL, one can carry out different operations on the database and simplify the complex ones for better understanding.

Hadoop platform

It is expected of a data scientist to be trained in Hive and Pig also, they should have experience in Amazon S3. Platforms like Hadoop and Apache help in handling big volumes of data. They are also helpful in summarizing, filtering and exploring the data.

Machine learning

This is the highest level of skill which a data scientist should have knowledge in, but it is also the most difficult and complex skill to acquire. Machine learning and artificial intelligence are all about using different data components into algorithms which will give a predictive theory about business problems. One should be trained in regression techniques, time series, computer vision, decision trees, and many other advanced skills.

Data visualization

Tools like ggplot, Matplottlib, etc. are those which can help convert complex data into something which is easily comprehensible. This is important for the data scientist to make the management understand the results of an entire data cycle in a simple language which is not technical. It helps in visualizing the complex structured data through simple charts and graphs.

The above mentioned are all those skills which one needs to be an expert in, but it is not a fast process. It takes gradual understanding and practice under guided supervision.

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If thinking about becoming a data scientist, there are several things to learn both in theory and practice for which one need to choose the best data science course for themselves. Now the search for the best certification courses for the professionals in Singapore is over as they can now avail quality modules at excelr.