Syllabus

In this module, we explore strategies for monetising data within an organisation. Discover how leveraging data can significantly impact product quality, production costs, and customer experience. Understanding these concepts is crucial for staying competitive in today's data-driven economy. We discuss key principles for identifying data monetisation opportunities, as well as real-world examples of successful strategies. 

Participants will learn to:

Unlock the potential of data to drive revenue and profit in organisations. 

Leverage data to impact product quality, production costs, and customer experience. 

Learn from existing data-driven business models. 

Identify data monetisation opportunities to stay competitive in today's data-driven economy. 

In this module, we cover fundamental elements of any organisation's data strategy. We explore options for storing data in a structured and accessible/manageable way. We discuss the necessary hardware and software requirements, as well as available business solutions. We also address key topics such as data collection, data quality, and data protection.  

Participants will learn to:  

Navigate comfortably in the operation and function of data collection, storage, and management. 

Cultivate effective communication and collaboration with data infrastructure professionals. 

Gain a basic knowledge of database systems, cloud computing, and data warehousing concepts. 

Apply fundamental principles to understand the broader context of data infrastructure components. 

In this module, we explore how to develop effective teams, identify essential skill requirements, foster co-creation among business, science, and engineering teams, and implement strategies to drive innovation. These topics are critical to improving team performance, fostering collaboration, and achieving success in data science projects.

Participants will learn to: 

Master the full spectrum of recruiting, training, and managing data science teams. 

Use talent identification strategies for building effective data science teams. 

Implement team structuring principles to optimise collaboration and productivity.  

Apply effective leadership principles to foster an innovative environment and drive progress on data science projects. 

This module will cover the fundamentals of how data infrastructure solutions are implemented in business environments. In particular, the module will create an understanding of different data storage options, and how data is processed and managed within a data ecosystem. In addition, data integration and interoperability of various systems will be discussed, as well as how an appropriate data infrastructure powers analytics, data science and machine learning.

Participants will learn to:

Efficiently allocate resources across projects. 

Strategically prioritise and deprioritise projects based on organisational goals.

Identify and assess project risks to mitigate potential failures. 

Align projects with organisational objectives to ensure overall success. 

In this module, we examine ethical considerations in data use and decision-making, covering legal compliance, privacy laws, and responsible data handling. These topics are crucial for maintaining integrity and trust in data-driven practices. 

Participants will learn to:

Navigate ethical considerations in data use. 

Master legal compliance, privacy laws, and responsible data handling for integrity.