Course Structure

PROGRAMME OVERVIEW

PRTF’s AI-centric PGDM is a two-year, full-time program structured across six trimesters (or terms). The program offers two specialization (or major or elective) domains:

Marketing and Finance
AI and Data Sciences

During the first year (Terms I–III), all students—irrespective of their academic background—are required to complete a set of core (or foundation) courses. These courses are mandatory and designed to build strong fundamentals across key management disciplines, including marketing, finance, human resources, operations, and analytics.

Aligned with the AI-centric vision of the program, the first-year (Terms I–III) curriculum also integrates foundational concepts in AI and Data Sciences, specifically tailored for managerial application. This ensures that all students develop a robust understanding of how emerging technologies can be effectively leveraged in business decision-making.

Summer Internship [4 to 5 weeks]: Upon completion of Term III, all students will undertake a paid summer internship in AI and Data Sciences, providing hands-on industry exposure and practical application of their learning.

Industry-ready personality and Interview training [2 weeks]

MCQ-based screening test on foundational concepts in AI and Data Science.

Duration: 30 minutes

Number of questions: 25

No negative marking.

In the second year [Term IV and V], students will select one of the two specialization domains—Marketing and Finance or advance AI and Data Science. These terms are designed to deliver advanced, domain-specific knowledge and build deeper expertise aligned with career pathways.

Fieldwork and Project: The final Term VI is dedicated to fieldwork and project-based learning, enabling students to apply their cumulative knowledge to real-world business challenges through guided research and industry-oriented projects.

Placement process: The placement policy of the PGDM Program is designed to provide structured, transparent, and equitable career opportunities for all eligible students. The pre-placement preparation process commences in Term IV, encompassing mock interviews, Group Discussion sessions, and comprehensive training in aptitude and skill assessment.

Short-term certificate course

First certificate course – During term II
Second certificate course – During term V

NUMBER OF CREDITS

First year (I, II, III terms): 54 credits of core courses.

Second year (IV, V, VI terms): 42 credits of elective [or specialization] courses.

Internship: 06 credits

Total credits: 102

1 Credit = Aprox. 10 hours of classroom instruction (theory)

SYLLABUS

As per AICTE model curriculum and NEP 2020

YEAR 1 – Foundation and Core learning

Trimester I	Trimester II	Trimester III
Managerial (micro) economics	Indian economy and Policy	Legal and Business environment
Business communication	Corporate finance	Marketing research
Financial reporting, Statements & analysis	Operations management	Business analytics
Marketing management	Human resource management	Corporate strategy
Organizational behaviour	Business communication	Business ethics and Indian ethos
Quantitative techniques	AI in Marketing, Finance & Operations	Strategic management and AI Strategy
Introduction to AI for managers	Cloud Computing (Amazon Web Services, Microsoft Azure, Google Cloud Platform)	AI business ethics & ESG
Python, SQL & Notebook basics	Data visualization (Tableau, Power BI)	AI strategy & Competitive advantage
Statistical foundations (with AI tools)		AI Business Case (ROI, TCO)
LLM tools lab (ChatGPT, Claude, Gemini)		AI product management
		AI in CX, HR, Retail, Sustainability
		Intelligent process automation (RPA)

YEAR 2 – Specialization courses

MARKETING AND FINANCE

MARKETING

Consumer behaviour
Product and Brand management
Digital and Social Media Marketing
Integrated Marketing Communications (IMC)
Sales and Distribution Management

FINANCE

Investment analysis and Portfolio management
Financial markets and Services
Corporate valuation
Financial derivatives
Mergers, Acquisitions and Corporate restructuring
International finance

AI AND DATA SCIENCE

DATA SCIENCE

Machine learning
Big data (Hadoop, Spark)
Data engineering basics
NLP and Sentiment analysis
Decision support systems

ADVANCED AI

Deep learning and Generative AI
Multi-agent systems and Agentic AI
MLOps (deployment)
Intelligent Automation (IPA)
Domain elective (Finance / Marketing / Ops)

EVALUATION SYSTEM

Student performance is assessed through a combination of continuous internal evaluation and end-term examination, in line with All India Council for Technical Education guidelines. Continuous evaluation includes quizzes, assignments, class tests, case analyses, presentations, and attendance. The end-term assessment may comprise written examinations, practical, viva-voce, projects, and reports, as applicable.

The weightage of internal and end-term components is as prescribed by AICTE norms. Evaluation of practical, projects, and viva may involve both internal and external examiners where required. Final grades are awarded based on a ten-point grading system with corresponding letter grades.

MOOCs (Massive Open Online Courses)

To complement traditional classroom learning with flexible, self-driven education, the Institute has integrated MOOCs into the regular PGDM curriculum. This initiative provides students with the opportunity to learn specialized areas of business management from globally recognized experts and leading academic platforms.

MOOCs encourage independent, goal-oriented learning and enable students to enhance their knowledge, industry exposure, and professional competencies beyond the classroom. Students are guided throughout the process by the MOOC Coordinator, who provides detailed orientation, academic support, and assistance in course selection and completion.