PGDM Course in Data Science

The PGDM in Data Science is a specialized program designed to equip professionals with advanced skills in data analysis, machine learning, and strategic decision-making. This program combines the core principles of management with cutting-edge data science techniques, preparing graduates to lead data-driven initiatives and leverage insights to drive business success.

Key Features:

1. Comprehensive Curriculum:
• Core Management Modules: Foundation in Finance, Marketing, Operations, Human Resources, and Strategy to build a robust understanding of business management.
• Data Science Specialization: In-depth training in Data Analytics, Machine Learning, Statistical Methods, Predictive Modeling, and Data Visualization.
2. Hands-On Learning:
• Practical Projects: Engage in real-world projects and case studies that provide practical experience in applying data science techniques to solve business problems.
• Internships: Opportunities for internships with leading companies, allowing students to gain industry experience and apply their skills in professional settings.
3. Cutting-Edge Tools and Technologies:
• Programming Languages: Training in Python and R for data analysis and statistical modeling.
• Data Processing Tools: Experience with big data technologies like Hadoop and Spark.
• Visualization Software: Skills in tools such as Tableau, Power BI, and other data visualization platforms.
4. Expert Faculty:
• Industry and Academic Leaders: Learn from a team of experienced faculty members who bring a blend of academic expertise and industry experience to the classroom.
5. Industry Connections:
• Guest Lectures: Regular sessions by data science professionals and industry experts who provide insights into current trends and future directions in the field.
• Networking Opportunities: Access to a network of professionals, alumni, and industry leaders through events, workshops, and seminars.
6. Career Support:
• Placement Assistance: Dedicated career services offering support in resume building, interview preparation, and job placement.
• Career Counseling: Personalized guidance to help students navigate their career paths and explore opportunities in data science and analytics.
7. Global Exposure:
• International Programs: Opportunities for global immersion programs and exchange initiatives with partner institutions.
• Cross-Cultural Experience: Interaction with a diverse cohort of students, enhancing cross-cultural communication and global business perspectives.
8. Holistic Development:
• Leadership and Soft Skills: Emphasis on developing leadership qualities, teamwork, and communication skills through various training programs and extracurricular activities.
• Extracurricular Engagement: Participation in clubs, seminars, and events that promote personal and professional growth.

Admission Criteria:

• Educational Qualification: A Bachelor’s degree in any discipline with a minimum of 50% marks.
• Entrance Exams: Valid scores in CAT, XAT, MAT, GMAT, or equivalent management entrance exams.
• Work Experience: Preferred but not mandatory; fresh graduates with a strong interest in data science are also encouraged to apply.
• Selection Process: Typically includes a personal interview, group discussion, and evaluation of academic performance and entrance exam scores.