PGPDM in Data Science and Machine Learning

Over the last few years, there has been a meteoric rise in the number of online courses and training programs to prepare the next generation of data scientists. This is in response to the talent gap and the perceived demand for data scientists. Though finding a data scientist who can mine large data sets and derive actionable insights is still a challenging task, the increasing number of bootcamps, MooCs, post-graduate in data science and online training programs are somehow addressing the issue. In our opinion, there are many companies out there that are not necessarily short on data science talent, it is that the top management of the company does not properly use the talent they already have in the company. Business directors, managers, and VPs must adapt to work with data scientists if they want their company to make the best use of data; in a nutshell, they need to be more data fluent. While the structure of many business organizations is highly complex, this simplified di...

Today, data scientists are leveraging data science and machine learning algorithms to solve complex predictive analytics problems. Some examples of these problems include predictive maintenance, churn prediction, entity matching, and image classification. Though everyone wants to forecast the future, fully exploiting data science for predictive analytics remains the domain of only a few. To expand the reach of data science (the most in-demand skill), the modern data architecture needs to meet the following requirements: ·          Bring predictive analytics to the IoT Edge ·          Enable applications to consume predictions and become smarter ·          Become faster, easier, and more accurate to deploy and manage ·          Fully support data science life cycle   Data Smart Applications You might kn...

Numbers don't lie, the demand for data scientists has increased tremendously in the past few years. According to Glassdoor, data science was the highest paying job in 2016. For three years in a row, the data science job has been chosen the best job in the United States of America. Undoubtedly, the data scientist title has become a coveted one in most companies. From large business organizations to small and mid-sized enterprises (SMEs), all are now looking for data science professionals who can mine and interpret large data sets and derive meaningful insights to help them take more informed decisions. Listed below are some top reasons for making a career in data science.   1. Shortage of Skilled Resources According to a report by McKinsey & Company, the worldwide management consulting firm, the United States of America will face a sharp shortage of around 140,000–190,000 data scientists and around 1.5 million data analysts who can understand and make informed business ...