STUDY

This module provides an introduction to the artificial intelligence (AI) and data science fields, covering the history of AI and exploring a variety of fundamental topics, such as probability, statistics and machine learning. The curriculum is designed to equip you with a thorough understanding of these foundational techniques, enabling them to apply AI and data science methods to solve complex practical problems. The module also provides an opportunity to reflect on the ethical dimension of AI and data science and sets the stage for more advanced topics later in the course.

Python is a popular programming language used by scientists working in the fields of artificial intelligence and data science. SQL (Structured Query Language) is a language used to query data stored in a relational database where large datasets are organised across multiple interconnected tables. An understanding of Python, SQL and relational databases and how the three technologies can integrate with each other is essential for solving problems within artificial intelligence and data science. This module will cover the key elements of Python programming and build towards harnessing the standard Python libraries and packages to create solutions. Best practices of Python coding will be embedded throughout the module. Relational database design and the SQL language will also be covered to enable the student to design and query datasets. You will also learn how to integrate all three technologies to create robust data-orientated applications.

The evolution of big data analytics has been significantly influenced by the advent of cloud computing. Historically, data analytics required substantial on-premises infrastructure, which was both costly and inflexible. However, with the emergence of cloud computing in the early 2000s, organisations gained the ability to process and analyse large datasets more efficiently and cost-effectively. This shift has enabled the rapid growth of big data analytics, transforming how businesses and researchers approach data-driven decision-making. This module provides a comprehensive grounding in cloud computing and NoSQL concepts and solutions, buttressed with extensive practicals to build experience in individual services and architectural designs. Moreover, the module will delve into the integration of AI and machine learning within cloud ecosystems, offering data analysts the tools to derive deeper insights and drive innovation. As the University of Suffolk is an AWS Academy partner institution, the module will give you an opportunity to acquire AWS certification(s) if you so wish.

Recent advancements in computing power, large-scale datasets and key theoretical insights have propelled the development of deep learning techniques. These techniques have significantly improved accuracy in a variety of computational tasks, such as computer vision, natural language processing, speech recognition and autonomous driving, thereby making numerous applications feasible. This module provides an in-depth introduction to deep learning models, including their fundamental components and training processes. You will explore a range of deep neural architectures, including recurrent neural networks, convolutional neural networks and transformers, as well as other AI models derived from them such as generative AI and deep reinforcement learning.

The Masters Project is the culmination of our taught MSc degrees. This project is your opportunity to apply the knowledge and skills acquired from all the earlier modules on a real task – it is very likely a project proposed by a company or research organisation.

This module provides an introduction to the artificial intelligence (AI) and data science fields, covering the history of AI and exploring a variety of fundamental topics, such as probability, statistics and machine learning. The curriculum is designed to equip you with a thorough understanding of these foundational techniques, enabling them to apply AI and data science methods to solve complex practical problems. The module also provides an opportunity to reflect on the ethical dimension of AI and data science and sets the stage for more advanced topics later in the course.

Python is a popular programming language used by scientists working in the fields of artificial intelligence and data science. SQL (Structured Query Language) is a language used to query data stored in a relational database where large datasets are organised across multiple interconnected tables. An understanding of Python, SQL and relational databases and how the three technologies can integrate with each other is essential for solving problems within artificial intelligence and data science. This module will cover the key elements of Python programming and build towards harnessing the standard Python libraries and packages to create solutions. Best practices of Python coding will be embedded throughout the module. Relational database design and the SQL language will also be covered to enable the student to design and query datasets. You will also learn how to integrate all three technologies to create robust data-orientated applications.

The evolution of big data analytics has been significantly influenced by the advent of cloud computing. Historically, data analytics required substantial on-premises infrastructure, which was both costly and inflexible. However, with the emergence of cloud computing in the early 2000s, organisations gained the ability to process and analyse large datasets more efficiently and cost-effectively. This shift has enabled the rapid growth of big data analytics, transforming how businesses and researchers approach data-driven decision-making. This module provides a comprehensive grounding in cloud computing and NoSQL concepts and solutions, buttressed with extensive practicals to build experience in individual services and architectural designs. Moreover, the module will delve into the integration of AI and machine learning within cloud ecosystems, offering data analysts the tools to derive deeper insights and drive innovation. As the University of Suffolk is an AWS Academy partner institution, the module will give you an opportunity to acquire AWS certification(s) if you so wish.

Recent advancements in computing power, large-scale datasets and key theoretical insights have propelled the development of deep learning techniques. These techniques have significantly improved accuracy in a variety of computational tasks, such as computer vision, natural language processing, speech recognition and autonomous driving, thereby making numerous applications feasible. This module provides an in-depth introduction to deep learning models, including their fundamental components and training processes. Students will explore a range of deep neural architectures, including recurrent neural networks, convolutional neural networks and transformers, as well as other AI models derived from them such as generative AI and deep reinforcement learning.

The Masters Project is the culmination of our taught MSc degrees. This project is your opportunity to apply the knowledge and skills acquired from all the earlier modules on a real task – it is very likely a project proposed by a company or research organisation.