5 Key Skills of Data Scientist

Key Skills of Data Scientist

Data is the new oil and this is the century of data. The 21st century has given a new rise to the new fields of study and it is going to grow exponentially in the upcoming time. With the rise of new technologies like Data Science, Machine Learning, Artificial Intelligence, and Business Intelligence, the demand for data professionals has seen an upward curve in the last 2-to 3 years.

In this article, we’re going to share the key skills of data scientist.

In order to become a data scientist, you need a lot of skills, experience, and vision to explore the data with the mindset of an analyst. Data professionals are visionary and they look at data, unlike everyone.

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Here are the 5 key skills of a data scientist:

1. Knowledge of a Programming Language

2. Python Libraries

3. Big Data Tools

4. Machine Learning

5. Business Intelligence Tools

Now, we’ll explain one by one the 5 skills of data scientist and explain how having these skills can land you high-paying jobs as a data professional.

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1. Knowledge of Programming Language: Data professionals are one of the most advanced and hi-tech working professionals in the 21st century. To start your journey as a data professional, one must have good knowledge of a programming language that gets used in data analytics.

The programming languages used in data analysis are Python, R programming language, Scala, SQL, and Java. Of all these programming languages, one of the most preferred languages by companies is the Python programming language. Python was developed in 1991 by a Dutch programmer named Guido van Rossum.

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Python is an easy to learn and easy to use programming language used by the majority of companies around the globe. The demand for data professionals, having knowledge of Python programming language is only increasing with each passing day. If you want to know Why Learning Python is Useful in 2022, explore our previous article.

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2. Python Libraries: If you’re a fresher starting in the field of data or a working professional from different background, you must be wondering, what are libraries? Most programming languages consist of a pre-built set of functions that make it easy for programmers to use code like never before.

The best thing about the Python programming language is that it has more than 1 lakh libraries that programmers can use to write code. Due to its popularity, Python has a huge community of developers from all around the globe.

Some of the most used libraries in Python programming are Numpy, Pandas, matplotlib, and Seaborn.

If you are a data enthusiast and planning to move ahead in the data field, you can browse these amazing data science certification programs by Console Flare:

a. Python For Data Analytics Certification Program

b. Masters in Data Science With Power BI Certification Program

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3. Big Data Tools: Data is getting bigger and so is the data domain. The demand for data professionals who are skilled in Big Data tools is getting higher. One of the most preferred tools for Big Data Analysis is Spark by the renowned company Apache.

Knowledge of Apache Spark not only can bring big companies to you but also is capable of getting you a handsome salary package.

4. Machine Learning: To become a data scientist, one must have good knowledge of ML tools like Scikit Learn. The knowledge of statistics is also a must-have skill for a data scientist.

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5. Business Intelligence Tools: Knowledge of BI tools like Microsoft Power BI or Tableau is can be a gem in the crown of a data scientist. BI tools are used in Data reporting & dashboard creation, that help company in making decisions based on immersive reports and interactive data.

If you are willing to pursue Data Science as a career, you must start your journey by learning the most in-demand data technologies. certification programs by Console Flare are capable of getting you high salary packages across the top global companies.

a. Python For Data Analytics Certification Program

b. Masters in Data Science With Power BI Certification Program

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