What are the Prerequisites for Data Scientist?
INTRODUCTION
Data Science is a fast-growing, trending tech career track. With such a huge demand for the role, a lot of professionals and graduates are stepping into this field to fulfill the demand and build lucrative careers. However, to become a successful Data Scientist, you need to be proficient in different technical and non-technical skills. These skills will make your life as a Data Scientist easier. You can even choose to learn with Data Science Training Institute in Gurgaon for easy learning. Different job roles require different qualities. Thus, being a data scientist also requires some perquisites
Prerequisites for a Data Scientist
SQL Databases
SQL is a programming language useful in managing and querying data held in a relational database management system. It is used to read, retrieve, update, insert new data or delete existing data. Most companies expect candidates to be able to write complex SQL queries, to gain insights from data. SQL seems to be very concise when it comes to commands, and thus, reduces the amount of programming you need to do and saves a lot of time.
Hadoop Platform
There can be times when the amount of data that you have exceeds the memory of your system. In such cases, you may require to send that data to different servers. Hadoop solves the problem for you by quickly conveying data to various points in the system. It is useful in exploring data, filtering, sampling, and summarizing it.
Python Programming
Python is versatile and useful in almost all the processes of Data Science. Be it data mining or running embedded systems, python can do almost everything. Python can take data in different formats and import SQL tables to your code easily.
R Programming
With R programming, you can solve any Data Science related problem that you might encounter. It is however the most popular language among Data Scientists. They preferably use it for solving statistical problems. It is one of the most essential Data Science Prerequisites.
Machine Learning and Artificial Intelligence
ML helps in analyzing a large quantity of data using algorithms. However, only a small percentage of Data Scientists are proficient with certain advanced machine learning techniques like adversarial learning, neural networks, reinforcement learning, Time Series, etc.
Mathematics and Statistics
Mathematics is one of the most common Prerequisites for Data Science. Probability and Statistics go hand in hand and are used for data imputation, visualization of features, feature transformation, model evaluation, feature engineering, dimensionality reduction, and data preprocessing.
Apache Spark
Just like Hadoop, Apache Spark is considerably a big data computation framework. However, the basic difference is that Spark is comparatively faster. Hadoop basically reads from and writes to disk, whereas Spark catches its computations in the memory of the system. Thus, making it faster than Hadoop. Moreover, the design of Spark is specifically for Data Science, to run complex algorithms faster. It helps you save time while processing a big sea of data.
Data Visualization
Data visualization is basically a representation of data visually, through graphs and charts. A data scientist should be able to represent data graphically, with charts, graphs, maps, etc. Visualization seems to be very important to make sense of the large amount of data generated each day.
Excel and Tableau
Both Excel and Tableau, are very important to understand, manipulate, analyze and visualize data. Excel is useful when there are a lot of manipulations and computations to be done on the data. Tableau is further useful when you need to gather all the data in one place and display it using powerful visualizations on the dashboard. Moreover, a combination of both helps a lot in generating insights.
CONCLUSION
Data Science is moreover a bit more challenging to learn than other fields in technology. It however needs more practice and hard work. This is one of the reasons for its high demand and one of the most well-paying career options. Looking at the demand curve, it will be beneficial to start a career in this field. To help you in this, Data Science Training in Delhi can be a good start. Also, it is one of the most well-paying jobs in the tech world. With data becoming the backbone of business decision-making, the number of Data Scientists required is increasing exponentially. Moreover, companies are now implementing Machine Learning and Big Data methodologies. Thus, accelerating the demand for Data Science jobs.
