Data Science is emerging as one of the fastest- growing and most in-demand fields in the world. Many large companies and industries have drastically increased their investments in their digital platforms over the past few years. This gigantic wave of data has led to a brisk demand for Data Scientists in the market.
The studies have shown a significant gap between the demand and supply of skilled Data Scientists in today’s technology-driven era dominated by data. Thus, Data Science proves to be a promising and fruitful career choice for the youth as modern businesses are flooded with data.
To become a Data Scientist, you need to learn Data Science from scratch, starting from its core concepts to why it is so crucial and its applications.
Learning Data Science is a process in itself that involves several steps, such as:
1. Get adapted to Mathematics: A Data Scientist must not only be familiar with the various theories and concepts of mathematics such as data distribution, statistics, probability theory, etc., but also master them. A good knack for these concepts is an essential prerequisite for performing the primary functions of Data Science, which include analysing and interpreting data and predicting the probability of a particular event in the future.
2. Getting the hang of coding: Another primary skill that you need to learn to kick-start your career as a Data Scientist is coding. For this, you need to have knowledge of various programming languages like Java, MySQL, Python etc. These programming languages help in writing efficient codes, intensive Machine Learning algorithms and developing models using them as well as managing data which includes retrieving, modifying, deleting, updating and manipulating it.
3. Master in Database: Data Science is all about dealing with copious amounts of data at every single step. Therefore, to be a successful Data Scientist, you need to understand the A to Z of database to be able to process and manipulate the data in the right direction to get useful and valuable insights and information.
4. Become an expert in Visualization and Reporting: Visualization plays an inherently important role in Data Science, to enable advanced data analysis. It involves examining and presenting data in a visually appealing manner using software such as Tableau. Reporting is equally important to provide the results of data analysis in a report.
5. Learn Big Data: Data Science and Big Data are interdependent and it is impossible to understand or apply one without the other. Big Data refers to the ample volume of structured and unstructured data that needs to be analyzed. Proper knowledge and understanding of Big Data is crucial for a meticulous and accurate analysis of the insights that ultimately help the business to make better and informed strategic decisions.
Boston Institute of Analytics is a world-renowned institution that offers training programs in various emerging technologies across the globe. The Data Science training program offered by BIA consists of two modules — core and advanced with a unified mode of delivery. It is a comprehensive and in-depth course covering all facets of Data Science. The students will learn different data science tools like Python, MySQL and Power BI. It also provides an opportunity to work on real case studies along with hands-on training and learning. The course also has other benefits like 100% placement support and scholarships.