How to Become a Data Scientist
Over the last decade there has been an explosion in the amount of data collected and retained by various industries. Every decision taken in every firm these days is data-driven. And, data scientists are those who make sense of this data using various tools and help businesses make important decisions and also solve strategic marketing and risk-management problems. If you are someone who has a flair for numbers and loves working with data, then you must take the online course on Data Science available on the Fair & Lovely Career Foundation.
An estimated 2.5 quintillion bytes of data is created every single day, according to IBM. As per statistics, the number of data science jobs is projected to rise by 15% by 2022. The job of a data scientist is one of the highest paying jobs today. So, if you are someone that loves to work in this field, then this is the right time for you to become a data scientist. In case you are unsure about the right path to take for becoming a data scientist, then make use of the free career guidance available on the Fair & Lovely Career Foundation website.
What is data science?
Data science is a field of study that makes use of scientific methods, processes, algorithms and systems to extract insights from the data available. It combines statistics, data analytics, machine learning and the knowledge of Maths to make sense of such large amounts of data. The basic requirement of a data scientist is that she should be able to do data mining at a granular level and understand complex behaviours, trends, and patterns observed in a particular set of data.
What is the right path to becoming a data scientist?
Primarily, a data scientist should be able to connect science & technology with business. Prospective data scientists should have a deep understanding of statistical and machine learning algorithms. Basically, they should be good at Mathematics, should have a passion for numbers and an analytical mind. Here is the path you can follow to become a data scientist:
1. First, you must study at least one programming language, preferably Python. This will help you to test algorithms and ideas efficiently. The Fair & Lovely Career Foundation provides an online certification course in Python which you can easily study on your own.
2. Next, you should study statistics. Statistics is the practice of collecting and analyzing numerical data in large quantities. Hence, this forms the very base of data science. Do a free online course with certification in statistics on the Fair & Lovely Career Foundation.
3. The next course you should do is Data Visualization. As a data scientist, you will have to work on multiple spreadsheets that contain enormous amounts of data. When you work on many sheets at the same time, you might find it difficult to gain sharp insights. This is where ‘data visualization’ comes into play. It is nothing but the representation of information in the form of a chart, diagram, picture, etc. This will help you to improve your efficiency in working with piles of data and also help you draw insights very quickly. The online data visualization course on the Fair & Lovely Career Foundation website covers the main tasks required from data analysts today, including importing, summarizing, interpreting, analyzing and visualizing data. It aims to equip you with the tools that will enable you to be an independent data analyst.
4. It’s time to get into machine learning now. Once you get a good grip on the aforementioned courses, you can then prepare yourself to study machine learning. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. In the world of data science, machine learning is used to identify patterns in data and use them to automatically make predictions or decisions. You can do an online course in Machine Learning on the Fair & Lovely Career Foundation website where you will learn how to use machine learning, with a focus on regression and classification, to automatically identify patterns in your data and make better predictions.
5. You must learn advanced machine learning gradually and then learn to deal with unstructured data, as most of the raw data you get will be in an unstructured format.
6. You can become a confident data scientist once you complete a course on Deep Learning as well. Deep Learning is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms.
With the demand for data scientists being on the rise, this is the best time for you to explore your interest in data interpretation and other related fields and become a successful professional.