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 ...

The mantra for advancement in technology is to reduce or replace human labor with machines. Traditional human driven systems are being replaced by smart machines and automation. In other words, we can say that the dependence on human decision-making is dwindling very rapidly. If we consider an example of autonomous vehicles like self-driven cars, we can see how AI and machine learning applications are extensively used in self-driven cars these days to avoid collisions, enhance cruise control, self-parking, detect blind-spots, provide drifting warnings and more. All this has become possible with the advancements in technology and the advent of automation in the technology segment, which has transformed the way we deal with objects in our daily life. Now, let’s take a quick look at the most promising AI and machine learning trends for 2018.  Healthcare Sector: So Much Advancement Is Going on  In the last few years, we have seen how the healthcare industry has embrace...

If you don’t have a team of data science professionals in your organization, chances are you will have one soon. According to the Edvancer study, data science and analytics is one of the fastest growing job fields in India. As every business organization is producing data on a large scale, it becomes important for enterprises from different industry verticals such as retail, healthcare, manufacturing, information technology (IT) and others to strengthen their data teams. India is developing into one of the world’s data science capitals with renowned brands, including PayPal, Mercedes-Benz, AIG and Walmart setting up data science centers in the country. Furthermore, research from the Everest Group clearly indicates that India holds the lion’s share of the global analytics services market.   The number of data science and analytics jobs in India nearly doubled from April 2016 to April 2017. Today, many large and mid-sized business enterprises are looking for skilled professional...

Data science may have become a popular buzzword in the past few years, but its existence can be traced back to the late 1990s. As more and more businesses are transforming into data-driven enterprises, the demand for data science professionals is increasing at an exponential rate. Today, leading business organizations across the world are exploiting data to create new business strategies, opportunities, actions and growth. Many small and mid-sized enterprises (SMEs) are also discovering the potential of utilizing data and the importance of leveraging data in one form or the other to benefit the business. Now let’s take a quick look at the top trends in data science and analytics. 1. Talent Trends in the Data Science and Analytics Industry The massive growth of the data science industry has paved the way for several new employment trends. A large number of IT professionals are moving into the data science and analytics industry. As the number of jobs for data science and anal...

Today business organizations across the world are leveraging the power of artificial intelligence (AI) to derive result-driven insights from raw and unstructured data to solve complex business problems. Many of them are using machine learning–based tools to automate the decision making process. In fact, you would be astonished to know that corporate investment in artificial intelligence and AI based tools is predicted to reach $100 billion by the year 2025. In the last year alone, a whopping investment of $5 billion in machine learning ventures has come into effect. From this we can say that artificial intelligence (AI) will the biggest disruptor in the next 5-8 years. It will have a profound impact on the workplace. You might know that machine learning is already making a huge impact on businesses from every industry vertical. It is allowing companies to optimize their business operations, expand their top-line growth and increase their customer satisfaction. Here are a few e...