GRE

The Master of Business Administration (MBA) program is specially designed keeping in mind the current and future needs of the industry. It prepares young, energetic and curious minds to handle the complexities in the ‘technology led’ future. The unique specializations offered during the second year prepare you to meet the emerging needs to the industry. Experienced faculty drawn from various disciplines and geographies will teach in the program.

The full-time residential Fellow Programme in Management (FPM) is designed to enhance research capabilities of the participants and prepare them for research, academics, and consulting roles. The Programme is approved by the All India Council for Technical Education (AICTE).

MBA (Business Analytics) program at Jindal Global Business School is designed for experienced business professionals and provide essential analytical and soft skills in contemporary business analytics. The program will enable the students to define problems, use analytical tools and techniques to identify patterns, gain insights, develop business strategies and make better decisions. The students will acquire analytical mindset and understand methodologies that will facilitate innovative application of analytics across different functional areas of management.

• The MBA Programme is taught by Global Faculties from Wharton Business School, Cornell University, Kellogg School of Management, NYU Stern School of Business, Singapore Management University and the University of Texas at Austin, amongst others.
• A multidisciplinary curriculum which understands that management and technology are intertwined. A holistic approach that tackles not only core management topics but also communication and interpersonal skills, critical for leadership today.

• 9 month full-time Post Graduate Program in Data Science (PGPDS) with Machine Learning (ML) and Artificial Intelligence (AI) designed to create Data Scientists for the industry

• Comprehensive 550+ hours of curriculum with focus on technology and tools, modeling techniques, business and domain applications

• Tools covered: Python, R, SAS, Tableau; Techniques: Statistics, ML, DL, AI, Time Series, Visualization; Platforms: Hadoop, Spark, TensorFlow, Keras