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Skill Every Data Scientist Must Have


By NIIT Editorial

Published on 23/09/2021

6 minutes

Data science enthusiasts are aiming for prolific careers in the industry. And rightly so, given the salary inflation that such professionals are able to leverage. For this reason alone, the searches for AI ML courses are seeing an upsurge online. But online courses alone do not suffice for learners to bag jobs. They must have good knowledge of statistical data science if they are to fare well against stronger candidates for jobs. Some of the top-bracket, backbone skills of such practitioners include mathematics, statistics, computer science, and engineering. But while these are broad view competencies, there are technical tools as well which learners aiming for a data science career must aim for. In this article, we’ll list the key, in-demand skills that future-ready data scientists must display. 

Skills that Data Scientists Must Have 

Python 

Alongside Java, Perl, and C/C++, Python is high in a demand programming language. Overall, Python has been voted as the third most popular language in the StackOverflow Survey 2021. This programming language makes it easy to test code, along with running the same across a range of operating systems. As a side note, it uses a simple syntax that makes debugging easier. 

Hadoop

It offers a flexible schema for users, unlike traditional databases. Operations such as data mining and processing can be carried out easily on Hadoop. As per Stackoverflow, developers who work on Hadoop utilize Numpy or Pandas as a library. Data scientists turn to Hadoop whenever they face bottlenecks managing the volume of data. In addition to this, it can also be used for data summarization, filtration, exploration, and sampling. 

SQL 

Whether you are studying on your own or training online with an AI ML course for the data science industry, SQL is a default ask by recruiters. The basic use of SQL is in adding, deleting, and working on fields in a database. It was designed to work majorly with data so users could draw insights from databases. Precise commands do away with voluminous code and save on programming time. Relational databases are key to becoming a good data scientist which is why you need to learn SQL. 

Apache Spark 

Apache Spark is an analytics engine used for data analytics. There are plenty of similarities between Hadoop and Spark, yet Spark is faster than Hadoop. Apache Spark offers Application Programming Interfaces in languages such as Python, R, Java, and Scala. It optimizes query execution through in-memory caching which accounts for its significant advantage in speed over Hadoop. Users can run a variety of operations on it such as machine learning, analytics, and graph processing. 

Machine Learning 

Digital businesses need ML but there is a clear talent deficit in the labour pool. Since even institutional education is lacking in this domain, learners are turning to machine learning and data science courses online. Machine learning is the technique by which we can make a program self-learning in nature. It includes concepts such as logistic regression, decision trees, and supervised/unsupervised learning. Stock market trading, speech recognition, autonomous vehicles, virtual assistants, and image recognition are some applications of machine learning. 

R Programming Language 

R is used for end-to-end programming assignments like handling, storing, and analyzing data. It finds key applications in statistical modeling and data analysis. Developers run data visualizations using R alongside using it to clean, import, and analyze data.

Data Visualization 

We produce about 2.5 quintillion bytes of data each day. With so much raw data floating around, and the analysis on them going on, someone has to make sense of it all. Turns out that a crucial skill expected out of data scientists is that of data visualization. These techniques include an array of design operations such as depicting data through bar graphs, pie charts, and histogram plots among others. Some of the commonly used data visualization tools include Tableau, Matpotlib, and ggplot. They assist users in depicting data in a manner that is easy to follow. 

Leverage Machine Learning and Data Science Courses Online 

 NIIT’s Advanced PGP in Data Science & Machine Learning is designed for beginner to mid-level learners searching for an inlet into the data science industry. As mentioned, the talent pool for specialized professionals needs thousands of candidates to fill high-income profiles. This requires experiential expertise in fields like machine learning, natural language processing, deep learning, data visualization, and predictive analytics among other things. 

This 18-week online program comes with placement assurance so that your future is safeguarded from the start. Thanks to NIIT’s industry collaborations, eligible learners are offered jobs with a minimum CTC assurance of Rs.5LPA (Terms&ConsitionsApply). Learn in-demand technologies such as Python, Pandas, Tableau, MySQL, TensorFlow, and much more. Enrol now to learn data science and take the first step towards a future full of hope and professional rewards. 



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