Programme outline
Learning objectives and structure
By the end of the course, participants will:
- Understand Core Artificial Intelligence (AI) Concepts
- Define AI, machine learning, deep learning, and related technologies.
- Recognise various AI techniques and their applications across business functions.
- Understand Business Analytics Fundamentals
- Grasp the basic concepts of business analytics including descriptive, predictive, and prescriptive analytics.
- Learn how analytics supports decision-making and drives business value.
- Understand key data visualisation and reporting techniques.
- Understand Data Management Essentials
- Understand the role of data as the foundation for AI and analytics initiatives.
- Learn the basics of data collection, storage, quality assurance, and governance practices.
- Recognise the importance of data integrity and ethical data handling.
- Explore Business Impacts and Ethical Considerations
- Analyse how AI, business analytics, and sound data management can transform business processes and drive competitive advantage.
- Evaluate case studies of integrated AI and analytics solutions to understand ROI implications.
- Identify ethical considerations and biases in AI and data usage, and understand governance frameworks and regulatory standards.
- Assess Organisational Readiness:
- Evaluate your organisation鈥檚 digital infrastructure, data quality, and workforce competencies to determine its preparedness for AI adoption.
- Identify gaps that may impede the integration of AI, particularly those affecting overall business productivity (we could use alternative preferred tools to assess AI readiness that map back to AISG鈥檚 AI Readiness Index as the common lingo in articulating AI readiness of companies)
- Identify Productivity-Related Business Challenges:
- Recognise key operational inefficiencies and productivity bottlenecks that can be addressed through AI solutions.
- Analyse existing business processes to pinpoint areas where AI-driven interventions could streamline operations and enhance productivity.
- Develop Clear Problem and Opportunity Statements:
- Formulate precise, actionable problem statements that clearly articulate the business challenges and productivity issues at hand.
- Develop opportunity statements that link AI solutions directly to measurable improvements in productivity, cost reduction, and process optimisation.
- Apply Analytical Frameworks:
- Utilise frameworks such as Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, cost-benefit analysis, and impact-effort matrices to prioritise challenges and articulate the expected productivity gains from potential AI solutions.
Day 1
- Understand Core AI Concepts
- Business Analytics Fundamentals
- Data Management Fundamentals
- Exploring Business Impacts and Ethical Considerations
- Synthesis: What research and practice are telling us about the future of work in the age of AI
- Assess Organisation Readiness
- Identify Productivity-Related Business Challenges
- Develop Clear Problem and Opportunity Statements
- Apply Analytical Frameworks
- Summary and Assessment
Assessment
Class participation and in-class project presentation