PIN 101 AI and Data Reasoning for Professional-Builds practical AI and data literacy for professionals who need to lead, evaluate, or commission AI-enabled work, with emphasis on data quality, model evaluation, uncertainty, bias, explainability, and AI project scoping.

PIN 102 Generative and Agentic AI for Professional and Organizational Productivity-Develops practical capability in using generative and agentic AI to improve individual work, team performance, and organizational productivity across writing, analysis, communication, decision support, automation, and knowledge management.

PIN 103 Responsible AI Governance, Risk and Implementation-Prepares learners to evaluate, govern, and implement AI systems responsibly across the AI lifecycle, including risk classification, impact assessment, privacy, oversight, accountability, monitoring, and governance controls.

PIN 104 Professional Intelligence Seminar- Introduces real-world applications of AI and Professional Intelligence through expert talks, practitioner panels, case studies, and demonstrations, with emphasis on practical insight and responsible implementation.

PIN 111 Design Thinking and AI Innovation: Models and Methods- This module introduces the foundational models and methods of design thinking as an approach to complex problem solving. It further examines how AI-assisted collaboration can augment each stage of the methodological process, enabling students to develop intelligent capabilities for strategic analysis, problem framing, and solution development.

PIN 112 Design Thinking and AI Innovation: Case and Practices- This module forces on the practical application of design-thinking processes, methods, and tools. Through AI-supported case studies and hands-on exercises, students will develop the ability to apply human-centred innovation approaches to domain-specific challenges and translate conceptual insights into actionable professional practices.

PIN 121 Business Decisions with Data, Finance and AI- Builds business and financial literacy for professionals from technical, public-sector, and development backgrounds. Develops the ability to reason with data and finance, to use AI tools for analysis, and to translate this into sound management decisions.

PIN 122 Innovation, Venture and Responsible AI Products- Develops the ability to translate AI-enabled ideas into viable products, services, ventures or internal innovations — through customer discovery, business-model design, validation, AI product strategy, venture finance and scaling — with product-level safety and responsibility built in. 

PIN 131 Global Leadership, AI Transformation and Professional Ethics- Develops leadership capability for AI-enabled change across cultures, organizations, and sectors, including responsible influence, communication, ethics, stakeholder alignment, global collaboration, and transformation leadership.

PIN 132 Sustainability, ESG and AI for Value Creation- Builds understanding of sustainability as a strategic, operational, and ethical responsibility, using data and AI tools for ESG analysis, climate scenario thinking, reporting, and long-term value creation.

PIN 141 Applied Machine Learning for Professional Problem-Solving- Develops practical capability to use machine learning for real professional and organizational problems. Learners study how to frame problems, prepare data, select suitable models, evaluate results, interpret outputs, and communicate findings to decision-makers. The course emphasizes responsible use, data quality, uncertainty, bias, explainability, and the practical limits of machine learning. Students complete an applied project using real or realistic data to support professional decision-making or operational improvement.

PIN 142 Digital Workflow and AI Systems Integration- Introduces how AI can be connected with data, digital tools, cloud services, dashboards, and organizational workflows. Learners study the practical process of moving from raw data to usable AI-supported outputs, including data pipelines, automation, deployment, monitoring, and human-in-the-loop review. The course emphasizes reliable implementation, responsible operation, cost-aware design, and integration of AI into real work processes. Students complete an end-to-end project that prepares them for AI-enabled Capstone work.