PGPDM in Data Science and Machine Learning

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...

The term deep learning brings up several questions in the mind of those people who have never heard or worked using this technology. What is it, what benefits can it bring to tech-driven companies, and what is its technical background? As a subset of artificial intelligence (AI), deep learning stands strong behind several enthralling innovations including self-driving cars, image recognition, voice recognition, and more. You might know that this powerful technology has covered multiple facets of human lives. Over the past few years, deep learning has started grabbing enormous attention and for good reason. Today, it is achieving results that were not even imaginable before. If reports of the Fortune , are to be believed, startups primarily focused on AI had raised around $7.5 billion in the second quarter of 2016. Such huge interest in both artificial intelligence(AI) and deep learning technologies is based on their advantages. So, let’s try to understand what exactly deep...

By the time we reach 2020, we will be producing 50 times more data than we were producing in 2011. Considering this, it is obvious that we need more data scientists who can analyze and evaluate data and create insights from it to drive business growth. Since the time “Data Scientist” was ranked as the hottest job of the 21st century by the Harvard Business Review, coupled with alluring paychecks, there has been a significant rise in demand for data-savvy enthusiasts in several businesses, nonprofit organizations, and public enterprises.  So if you are planning to become a data scientist, but wondering from where to begin, you’ve landed at the right place at the right time. Here is a complete guide to becoming a data scientist. Important Steps You Should Follow to Become a Data Scientist #1 Brush Up Your Skills in Mathematics and Statistics You might know that statistics and probability tools are required in every predictive analysis, since mathematics and statistics ar...

Today, our economy is inclined more towards big data, data science, and data analytics, since companies have been producing a huge amount of data every day. According to LinkedIn, there is an incessant demand for professionals who can interpret and mine humongous data sets. These are called data scientists.   What is a Data Scientist? Data scientists are a blend of computer scientists, mathematicians, and trend-spotters. The role of a data scientist is to decode humongous data sets and carry out further analysis to spot the latest trends in the data. The goal is to gain meaningful insight into what it all means. Data scientists operate somewhere between the IT world and business, and drive business enterprises by monitoring, analyzing and evaluating complex datasets to gain insights that businesses can leverage into result driven actions. What Data Science Roles are Out There? Here are some common job titles for data scientists: 1. Data Mining Engineer A Da...