Expertise in Analytics and Data Science requires knowledge and skills to understand the business problem, convert it into an analytical problem, identify and gather the input requirements to solve the problem, execute the solution and implement and track the outcome of the implementation. The Analytics and Digital Business Track prepares students to become effective professionals in this space. The program focuses on creating expertise around:
Considering the practical nature of this career track in the real world, the program will be delivered by a multifaceted mix of renowned scholars, successful industry practitioners, and faculty of international repute.
“If you put a limit on everything you do, physical or anything else, it will spread into your work and life. There are no limits, there are only plateaus, and you must not stay there, you must go beyond them”
– Bruce Lee, Martial Artist
Analytics & Digital Business Career Track
Today Analytics is a buzzword. Even amid mass layoffs reported in the major tech companies globally, the employment opportunities for data scientists show no sign of decline underlining the ever-increasing focus on this domain. Forbes has projected a 36% growth between 2021-31 in the career paths for Data Scientists. Spending on big data, analytics, and ML is ever increasing. While banking has the highest spending market share of 18.4% in 2021, telecommunications, manufacturing, and the Indian Government are other important spenders on analytics.
While the relevance and criticality of this domain is unquestionable challenges remain on how we can use it to make a real difference in how we manage and run successful organizations. A few of the areas of focus in the world of analytics are:
Data cleaning, integration and transformation to prepare it for analytics
Explores the power of machine learning algorithms to find meaningful patterns from data
Analysis of user-generated content such as text images and videos to extract actionable advice.
Use of AI in marketing, finance, HR and supply chain with real-world case studies
Handling large and diverse data volumes on the cloud
Allocating resources efficiently through linear and non-linear optimization
Analyzing unstructured data particularly images and text to make better decisions
Collecting and Analyzing business requirements for IT projects
Harnesses various cloud computing platforms to store and manage organizational data
Business use cases involving generative AI and LLMs