From Data Science to Digital Marketing: Exploring the PW Skill Development Tracks Planned for MBU Students

The proposed PW Skills–MBU partnership seeks to address this need through four structured skill development tracks: Data Analytics and Data Science, Artificial Intelligence and Machine Learning, Full Stack Development, and Digital Marketing.

The programme is designed to bring industry-oriented learning into MBU's academic environment, combining university infrastructure and faculty support with PW Skills' curriculum, expert-led instruction and practical learning ecosystem.

Four Tracks, Four Different Skill Journeys

The proposed curriculum recognises that each discipline requires a distinct learning pathway.

1. Data Analytics and Data Science: From Raw Data to Insights

Proposed duration: 200 hours across four semesters, with an additional common DSA component.

The Data Analytics and Data Science track is designed to progress from foundational programming and data management to advanced analytical and AI-related capabilities.

• Semester 1: Python, data handling and databases.
• Semester 2: Statistics, exploratory data analysis and deployment.
• Semester 3: Machine learning and MLOps.
• Semester 4: Deep learning, natural language processing and generative AI.

The progression is intended to help students develop an understanding of data workflows, analytical methods and emerging AI applications.

2. Artificial Intelligence and Machine Learning: Building for an AI-Driven World

Proposed duration: 200 hours across four semesters, with an additional common DSA component.

The AI and Machine Learning track combines programming, mathematical foundations and machine learning with advanced AI concepts.

• Semester 1: Core Python for AI engineers.
• Semester 2: Mathematics, statistics and machine learning foundations.
• Semester 3: Deep learning and MLOps.
• Semester 4: Generative AI, agentic AI, retrieval-augmented generation (RAG) and LLMOps.

This structure is designed to introduce students to the foundations of AI before progressing towards contemporary AI systems and their operational requirements.

3. Full Stack Development: From Web Fundamentals to Application Development

Proposed duration: 180 hours across four semesters, with an additional common DSA component.

The Full Stack Development track covers the technologies and workflows involved in building web applications.

• Semester 1: Foundations and web basics.
• Semester 2: JavaScript and frontend engineering.
• Semester 3: Backend development, databases and APIs.
• Semester 4: Next.js, DevOps and a capstone project.

The curriculum is structured to move from core web concepts towards more comprehensive application development, with a capstone intended to provide an opportunity to bring together learning from the programme.

4. Digital Marketing: Connecting Content, Search and Performance

Proposed duration: 120 hours across four semesters.

The Digital Marketing track focuses on the changing digital landscape, where content, organic discovery, paid campaigns and analytics work together.

• Semester 1: Foundations and the digital consumer.
• Semester 2: Content, SEO and GEO.
• Semester 3: Performance marketing and paid media.
• Semester 4: Analytics, automation and a capstone project.

The inclusion of SEO and generative engine optimisation reflects the evolving ways in which audiences discover and interact with information online.

Shared Foundations for Career Preparation

Beyond the specialised curriculum, the proposed programme includes two common learning components.

Data Structures and Algorithms (DSA) is planned for 180 hours across three semesters for students in Data Analytics and Data Science, AI and Machine Learning, and Full Stack Development. It covers algorithms, data structures, interview preparation and advanced algorithms.

Interview Preparation (IP) is planned for 32 hours across four semesters and is common to all four tracks. The Digital Marketing track includes Interview Preparation without the common DSA module.

These shared components are intended to complement subject-specific learning with structured preparation for professional opportunities.

How the Partnership Supports Delivery

PW Skills is expected to contribute curriculum design, live instruction by industry experts, learning resources, assessments and an LMS. MBU would provide the university setting, academic infrastructure and on-campus support through assistant faculty trained in the PW Skills ecosystem.

The proposed two-teacher model combines live digital sessions with an on-campus mentor who can support students with doubts and classroom accountability.

Additional planned elements include bootcamps, student progress reporting, feedback mechanisms and career-readiness activities.

A Structured Approach to Skill Development

The four tracks provide different entry points into technical, analytical and marketing-oriented learning. Their semester-wise design aims to give students a clear progression from foundational concepts to specialised knowledge and applied work.

Through the proposed partnership, PW Skills and MBU aim to bring these learning pathways into a connected academic experience—one that combines the depth of university education with practical skill development.