CURRICULUM

1. Statistics and Data Analysis: Learning foundational statistical concepts and techniques to extract meaningful insights from data
2. Data Visualization: Understanding how to create visual representations of data to communicate findings effectively. They also learn how to effectively communicate insights drawn from data through visualizations and presentations.
3. Data Mining: Exploring methods to discover patterns, trends, and relationships within large datasets.
4. Machine Learning and Deep Learning: Introducing machine learning and deep learning algorithms to solve business problems and automate decision-making processes.
5. Big Data Analytics: Focuses on dealing with large and complex datasets using technologies like Hadoop and Spark.
6. Business Intelligence: Applying data-driven insights to solve business problems, improve strategies, and enhance decision-making.
7. Predictive and Prescriptive Analytics: Using historical data to make predictions about future outcomes and recommending optimal actions. This course covers advanced techniques for using historical data to predict future outcomes and trends.
8. Text and Social Media Analytics: This course focuses on analyzing unstructured data like text from social media, customer reviews, or surveys. Techniques like NLP, Sentiment Analysis, etc., are covered during the course.
9. Business Intelligence and Reporting: Train the students on how to design and develop dashboards and reports to monitor key performance indicators (KPI) and track business metrics.
10. Functional Electives: Students explore to how data analytics can be applied in different functional domains like Finance, HR, Marketing, Operations and Healthcare
11. Ethical and Legal Aspects: Discuss the ethical considerations and legal implications of using data for business decisions.
12. Case Studies and Projects: Engaging in hands-on projects and case studies to apply learned concepts to real-world scenarios.

The hybrid mode of instruction combines both online and in-person learning experiences. This approach allows working professionals to balance their existing job responsibilities with their educational pursuits. Online lectures, readings, assignments, and discussions provide flexibility in terms of when and where students engage with the material, while occasional in-person sessions, workshops, and networking events provide valuable face-to-face interactions.

Duration: 1 year program

The program is typically divided into semesters with the Capstone project. Each semester will last for a duration of 4+1 months and the capstone project is for 2 months. During the course students explore how data analytics can be applied in different functional domains like Finance, HR, Marketing, Operations and Healthcare. Each semester may include multiple courses focused on different aspects for specific subjects.

The program often emphasizes practical application through case studies, projects, and assignments that mirror real-world business challenges. This approach enables students to apply theoretical concepts to practical scenarios, enhancing their problem-solving and decision-making skills.

In conclusion, the PGDBA program in a hybrid mode offers a tailored educational experience for students and working professionals seeking to enhance their business acumen and career prospects. Its flexible structure, combination of online and in-person learning, and focus on practical application make it a valuable option for those looking to balance their professional commitments with their educational aspirations.