Artificial Intelligence for Business Leaders

In this module, you learn to identify the applicability and limitations of AI/ML. We will begin to develop your analytical mindset and get comfortable with the language of AI.  

This module will equip you to:

• Establish reasons why business leaders need to learn AI. 
• Define and utilize common AI/ML terms.
• Explore AI concepts and discuss the evolution of AI/ML, including a summary of advances in algorithms, computing power, and data.
• Discuss ongoing issues around potential societal impacts of AI. 
• Determine the applicability of AI in tackling analytical problems and determine areas where business leaders should remain focused.
• Prioritize organizational considerations when operationalizing an AI project.

In this module, you explore how AI/ML informs major decision-making efforts in operations and capacity building, such as supply chain demand shaping, promotional and inventory strategies, and building contingencies.

This module will equip you to:

• Explain the applicability of Machine Learning (ML) methods to forecasting problems in the context of supply change management.
• Examine the critical role data plays in the success of ML projects.
• Discuss the potentials as well as the limitations of ML-based forecasting.

In this module, we will delve into customer segmentation and targeting strategies. We will explore industry-proven techniques for targeted marketing and discuss the critical components for developing effective targeted marketing capabilities: data management, analytical methods, and performance evaluation.

This module will equip you to:

• Utilize internal sales data, loyalty data, and social media data to improve marketing effectiveness through customer segmentation, personalization, and targeted marketing.
• Explore the challenges involved in handling data necessary for customer segmentation and targeted marketing.
• Identify well-established and frontier methods of statistical machine learning for segmentation and targeted marketing.
• Discover how ROI is measured when segmenting and targeting customers.

In this module, you will explore recent improvements in medical imaging and diagnostics that use deep learning to provide medical practitioners with new insights into patient care.

This module will equip you to:

• Describe the fundamental concepts of deep learning.
• Explore how deep learning models are built in Tensorflow and Keras.
• Observe how deep learning is applied to image data in healthcare for diagnosis.
• Design strategies to enhance trust of AI model adoption in your organization.

In this module, you discover the underlying factors that predict risk and the costs associated with it. Especially the risks associated with the interpretation of data.

This module will equip you to:

• Explain the applicability of Machine Learning (ML) methods to forecasting problems in Finance and Risk Management.
• Examine the importance of data in ML systems as the key differentiating factor for your business.
• Introduce Regression and Classification Trees and Random Forests as flexible and powerful ML methods.
• Discuss the potentials and issues with ML forecasting in Finance.

In this module, you will explore how human resources leverage new people analytics tools and techniques. Still, our focus will be on machine learning bias and algorithm fairness, which are central to any AI project whose outcomes impact people.

This module will equip you to:

• Describe how bias arises in AI projects and when it matters.
• Infer and cite how to monitor AI outcomes with respect to bias.
• Explain the many HR processes that AI and analytics can support.