Comprehensive Course Schedule Across 8 Semesters

Semester	Course Code	Full Course Title	Credit Structure (L-T-P-C)	Pre-requisites
1	DM-101	Introduction to Digital Marketing	3-0-0-3	-
1	DM-102	Business Communication Skills	2-0-0-2	-
1	DM-103	Introduction to Computers & Programming	2-0-0-2	-
1	DM-104	Mathematics for Engineers	3-0-0-3	-
1	DM-105	Science Elective I	2-0-0-2	-
2	DM-201	Consumer Behavior & Psychology	3-0-0-3	DM-101
2	DM-202	Digital Platforms & Technologies	3-0-0-3	DM-103
2	DM-203	Data Analysis & Visualization	3-0-0-3	DM-104
2	DM-204	Database Systems	2-0-0-2	DM-103
2	DM-205	Science Elective II	2-0-0-2	-
3	DM-301	Digital Advertising Fundamentals	3-0-0-3	DM-201, DM-202
3	DM-302	SEO & SEM Techniques	3-0-0-3	DM-202
3	DM-303	E-commerce Strategy	3-0-0-3	DM-201
3	DM-304	Marketing Research Methods	2-0-0-2	DM-203
3	DM-305	Departmental Elective I	3-0-0-3	-
4	DM-401	Advanced Analytics for Marketing	3-0-0-3	DM-301, DM-302
4	DM-402	Social Media Marketing	3-0-0-3	DM-301
4	DM-403	User Experience Design	3-0-0-3	DM-202
4	DM-404	Content Strategy & Creation	3-0-0-3	DM-301
4	DM-405	Departmental Elective II	3-0-0-3	-
5	DM-501	Digital Customer Experience	3-0-0-3	DM-401, DM-402
5	DM-502	Performance Marketing	3-0-0-3	DM-401
5	DM-503	Mobile App Marketing	3-0-0-3	DM-402
5	DM-504	Marketing Automation Tools	3-0-0-3	DM-401
5	DM-505	Departmental Elective III	3-0-0-3	-
6	DM-601	AI in Marketing & Predictive Modeling	3-0-0-3	DM-501, DM-502
6	DM-602	Cybersecurity & Data Privacy	3-0-0-3	DM-501
6	DM-603	Global Marketing & Localization	3-0-0-3	DM-501
6	DM-604	Marketing Innovation Lab	3-0-0-3	DM-501, DM-502
6	DM-605	Departmental Elective IV	3-0-0-3	-
7	DM-701	Capstone Project I	4-0-0-4	All previous semesters
7	DM-702	Internship Program	3-0-0-3	-
8	DM-801	Capstone Project II	4-0-0-4	DM-701
8	DM-802	Professional Internship	3-0-0-3	-

Advanced Departmental Elective Courses Overview

Departmental electives are designed to deepen specialization and provide students with advanced knowledge in niche areas of digital marketing. These courses go beyond general principles and dive into industry-specific applications and emerging trends:

• AI in Marketing & Predictive Modeling: This course introduces students to machine learning algorithms used in marketing analytics, including regression models, clustering techniques, neural networks, and natural language processing. Students learn how to build predictive models that forecast consumer behavior, optimize ad spend, and personalize customer journeys.
• Cybersecurity & Data Privacy: As data breaches become more frequent, this course explores the intersection of marketing and cybersecurity. Topics include GDPR compliance, privacy regulations, secure data handling practices, and risk assessment strategies for digital campaigns.
• Global Marketing & Localization: Students examine cultural nuances, language variations, and local market dynamics that affect global branding strategies. Case studies from multinational corporations highlight successful localization efforts across different regions.
• Digital Customer Experience: This course focuses on designing seamless customer journeys through multiple touchpoints. It covers UX research methods, persona development, journey mapping, and feedback collection mechanisms to enhance satisfaction and loyalty.
• Performance Marketing: Students learn about paid advertising platforms (Google Ads, Meta Ads), bidding strategies, conversion tracking, and attribution modeling. Practical exercises include campaign setup, optimization techniques, and ROI measurement using industry-standard tools.
• Mobile App Marketing: With mobile-first strategies dominating modern marketing, this course delves into app store optimization, in-app purchase strategies, push notifications, user retention tactics, and monetization models for various platforms like iOS and Android.
• Marketing Innovation Lab: This experiential learning module allows students to work on real-world projects under faculty supervision. Teams collaborate with startups or established brands to solve practical challenges using digital marketing frameworks and tools.
• Content Strategy & Creation: Beyond copywriting, this course teaches students how to develop comprehensive content strategies aligned with brand identity and target audience preferences. It includes multimedia creation, SEO integration, social media content planning, and cross-channel storytelling.
• Marketing Automation Tools: Students gain hands-on experience with automation platforms like HubSpot, Marketo, and Pardot. They learn to set up workflows, segment audiences, track engagement, and automate email campaigns based on user behavior and preferences.
• Social Media Marketing: This course covers platform-specific strategies for platforms like Facebook, Instagram, LinkedIn, Twitter, TikTok, and YouTube. It explores influencer partnerships, community management, viral content creation, and brand advocacy programs.

Project-Based Learning Philosophy

Our program emphasizes project-based learning as a cornerstone of education. From Year One, students engage in mini-projects that allow them to apply theoretical concepts in practical scenarios. These projects are designed to foster critical thinking, teamwork, and innovation.

Mini-Projects Structure

Mini-projects span 3–4 weeks and involve small teams of 3–5 students working on real-world marketing challenges. Each project begins with a detailed problem statement provided by faculty or industry partners. Students are required to:

• Conduct market research and competitive analysis
• Identify target audiences and define personas
• Design and implement digital strategies
• Analyze results using appropriate tools and metrics
• Present findings to peers and faculty mentors

Evaluation is based on process documentation, strategic thinking, execution quality, presentation skills, and peer feedback. These projects are evaluated by both internal faculty and external industry experts.

Final-Year Capstone Project

The capstone project represents the culmination of a student's learning journey. Over 12–16 weeks, teams of 4–6 students work on a substantial, real-world problem submitted by a partner organization or initiated independently.

• Project Selection Process: Students submit proposals outlining their project ideas, feasibility, and expected outcomes. Faculty mentors guide selection and assign projects based on alignment with academic goals and industry relevance.
• Mentorship Model: Each team is assigned a faculty advisor and an industry mentor. Regular meetings ensure progress tracking, problem-solving, and access to resources.
• Deliverables: The final deliverable includes a comprehensive report, presentation deck, prototype or tool demonstration, and a live implementation plan.
• Evaluation Criteria: Assessments focus on innovation, technical depth, strategic clarity, impact potential, and presentation quality. External reviewers from partner organizations provide additional perspectives.