Data is the new oil. It’s is valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc. to create a valuable entity that drives profitable activity; so, data must be broken down, analyzed for it to have value. — Clive Humby, 2006
Today, with the increasing adoption of digital technologies we have access to more data than we had at any point in human history. There is a huge volume of data that has been emanating from various digital sources including our cell phones, social media platforms, computers, financial institutions, and more. For companies to stay relevant and competitive in the 21st century, there is a need to transform this data into actionable insights. Over the past two decades, analytics has rapidly evolved from a simple number crunching exercise to a competitive strategy that is driving innovations across organizations. The explosive growth in the use of analytical methods in the recent years has been fuelled by three major developments – technological advancements leading to a tumultuous surge in data generation at both individual and organizational levels, methodological developments resulting in more effective computational approaches and faster algorithms for handling and exploring massive amount of data, and finally, exponential progress in computing power and storage capabilities.
According to a study by MicroStrategy, companies worldwide are using data to boost process and cost efficiency, drive strategy and change, and monitor and improve financial performance. It also says that over the next few years, the investments in analytics are predicted to accelerate for 71% of the global enterprises. However, as the requirement for skilled professionals in these fields soars, many companies continue to report the short supply of skilled employees. Quanthub has recently compiled data from major job services and reported a shortage of 250,000 in 2020 for skilled data scientists. In light of such trends, skills related to data science, machine learning, artificial intelligence, big data and operations research have become indispensable. And the need for relevant upskilling and specialization has become more important now than ever before.
The Post Graduate Certificate Program in Data Science & Business Analytics – Online (DSBA-Online) from IIM Amritsar provides an avant-garde curriculum with a special focus on the required tools and techniques to formulate, analyze and find solutions to the problems faced by businesses in today’s data-driven world. This rigorous 11-months program will be delivered in the online mode offering flexibility to the working professionals who aspire to develop analytical thinking and decision-making skills while continuing with their jobs. There is also an optional three (3) days long Campus Immersion module at IIM Amritsar campus in which the participants will have the opportunity to meet and interact with the IIM faculty. The program is designed to help aspiring professionals build a robust foundation and advance their careers in the fields of data science and business analytics. The participants will develop basics to advanced understanding of these areas using hands-on training with in-demand tools and techniques, case studies, and capstone projects.
Application Fee: INR 1,500/- + 18% GST
Programme Fee#: INR 1,65,000/- + 18% GST
Campus Immersion Fee (Optional) ## INR 21,000/- + 18% GST
# Fee includes tuition and study materials for the program.
## Not applicable for participants who have not opted for campus immersion. However, these participants will still attend the sessions online during this week.
|Application Submission (Last Date)||November 10, 2022|
|Online Interactions||December 05 –09, 2022|
|Admission Offers by||December 20, 2022|
|Registration & Orientation||January 14, 2023|
|Classes Start Date||January 15, 2023|
|Program Ends by||November, 2023|