Diploma in Applied AI and Analytics (S30)
What You'll Study
Year 1 - Semester 1
Communicating for Project (Proposal) EffectivenessMore
This module aims to equip students with the skills to articulate and communicate ideas persuasively and to work effectively in teams. They will be taught to pitch ideas or concepts and to write proposals to an intended audience.
Critical and Analytical Thinking (CAT)More
This module aims to equip students with skills in critical and analytical thinking, which includes the ability to evaluate different perspectives, articulate a point of view and support it with relevant and credible evidence. The module also provides students with opportunities to practise information literacy, and critical and analytical thinking through the exploration of contemporary local and global issues.
Equips students with knowledge in mathematics and analytical skills to solve problems related to infocomm technology. Topics include matrices, linear transformation, number systems, set theory, logic, Boolean algebra, techniques of counting and probability.
Education and Career Guidance 1: Personal DevelopmentMore
This module aims to help you discover your strengths, values and interests. It also supports you in making informed educational and career choices to achieve your career aspirations.
Front-End Web DevelopmentMore
Aims to equip students with the knowledge and skills in developing effective front-end web applications using Hypertext Markup Language (HTML) and Cascading Stylesheets (CSS). Students will learn to use front-end web development frameworks to further enhance their ability for rapid prototyping responsive web application.
Fundamentals of ProgrammingMore
Aims to help students pick up a programming language and learn how to solve and automate tasks through programming. Students will be taught programming fundamentals such as variables, data types, operators, control structures, methods and data structures such as arrays. At the end of the module, students will be competent in using programming for problem solving.
Fundamentals of ComputingMore
This module aims to provide students with an understanding of computer networking concepts and hands-on sessions on with operating systems using Command-Line Interfaces. Students will be taught on the use of various UNIX commands / system tools for user management, software installation, network administration and configuration of services. These topics are essential and prerequisite to an Application Developer for building and deployment of a software system.
Year 1 - Semester 2
Narrative Thinking (NAT)More
This module aims to equip students with the skills to critically evaluate the elements of narratives used in a variety of contexts, and to appreciate and harness the power of storytelling in our daily life. Students will analyse narratives to connect and contextualise self to society, and learn to craft impactful personal narratives to inspire or influence others.
Statistics for Data ScienceMore
Provides students with an introduction to elementary probability theory and statistical concepts and principles that lay the foundation to understand and learn the statistical procedures and methods. Topics include descriptive statistics, rules of probability, probability distributions of discrete and continuous random variables, sampling distributions, statistical estimation and hypothesis testing.
Back-End Web Development More
Aim to equip students with the skill in developing database driven web application. Students will learn about server-side programming and be able to create-database-driven web applications using a scripting language and programming frameworks.
Teaches students techniques to generate reports and dashboards that aid organisations to gain deeper insights into their business data. Students will learn best practices for creating effective data visualizations to support strategic data analysis and data-driven decisions using popular industry software such as Excel, Tableau and Power BI.
Programming for Data AnalyticsMore
Provides students with the fundamental skills to code applications to retrieve, manipulate, process and analyze data using the Python programming language. Students will learn to code in the Python Programming Language and key concepts such as exploratory data analysis and perform data analysis using Numpy, Pandas and Statsmodels on the data to gain useful insights for business decisions.
Communicating for Project EffectivenessMore
Equips students with the essential communication and interpersonal skills necessary for work and the pursuit of further studies.
Social Innovation ProjectMore
This module aims to equip students with a Design Thinking mindset in a social innovation context. Students collaborate in multi-disciplinary groups to apply Design Thinking tools and methods to create innovative prototype solutions for local social issues. In the process, they will develop a better understanding of themselves, and empathy for a local community in need.
Mathematics for AIMore
Equips students with key mathematical concepts in data mining, machine learning, data preparation and model building. Students will learn linear algebra, singular value decomposition (SVD), and principal component analysis (PCA). Students learn the numerical algorithms to solve mathematical equations. This module also provides students with knowledge of how linear algebra is applied to neural networks.
Education and Career Guidance 2: Career DevelopmentMore
This module aims to help you develop the skills, knowledge and attitudes needed for work effectiveness.
AI & Machine LearningMore
Provides students with the fundamental concepts in Artificial Intelligence (AI) and Machine Learning. The module aims to provide students with hands-on experience in building applications that use machine learning and neural networks. The students will also learn skills to build intelligent agents, such as Chatbots and integrate cognitive service APIs to add intelligence into their applications.
Covers the fundamental concepts to build and work with data pipelines. Students are taught how to work with traditional large datastores such as enterprise data warehouses and how to integrate data from multiple data sources into a single repository using Extract-Transform-Load (ETL) workflows via automated methods such as stored procedure triggers.
Teaches students neural network architectures and deep learning neural networks. Students will learn to frame problems and prepare machine trainable data sets. Students will apply deep learning frameworks such as Tensorflow and PyTorch to train deep learning models. They will also learn to deploy the trained models into applications.
DevOps & Automation for AIMore
Aims to provide students with DevOps knowledge in integrating their AI applications with docker and containerized cloud services such as kubernetes. Automating the AI workflow through Infrastructure-as-Code automation tools and services is essential for bringing AI code into production. Robotic Process Automation (RPA) is another software automation tool that enabled AI to be integrated with diverse data sources and service endpoints.
Data Structures & Algorithm (AI)More
Aims to teach students advanced Object-Oriented concepts and data structures and algorithms using Python. Through this module, students will learn how to implement stacks, queues, linked lists, dictionaries and solve problems using these data structures. Algorithms to improve code efficiency and search will also be taught.
This module teaches students practical AI skills such as data preparation and feature
engineering using cloud platforms for a variety of domains. This module equips students with skills to apply AI to vertical industry domains such as digital marketing, cybersecurity, Fintech and advanced manufacturing. It introduces students to the processes using data from social media platforms. They will also learn to perform in-depth analysis on the data to improve digital marketing.
Please refer to below footnote.
## Second year students are required to take 2 Poly-Wide elective modules, each per semester
This module aims to provide students with work exposure to an industrial environment, with opportunity to relate what is taught in the classroom to actual work situation. It creates a valuable learning opportunity for students to sharpen their skills and knowledge, as well as contributing to the development tasks of participating organisations.
Applied AI and Analytics ProjectMore
Provides students an opportunity to integrate the knowledge and technical skills they have acquired from the course, and experience the AI and Analytics workflow (Problem Framing /Data Exploration & Preparation / Data Engineering / Feature Engineering / Analytics and Computational Modelling / Data Analysis / Data Visualization), problem solving, project management, communication and working in a team to implement an AI and Analytics project. The project can be based on any AI or Analytics application area, subject to the approval of the school.
Infocomm Professional SeminarMore
Provides students an opportunity to monitor and integrate emerging technology trends and developments, structured data gathering for the identification of new and emerging technological products, services and techniques. Students are to conduct research and identify opportunities for new and emerging technology to support businesses with consideration of the ethical principles and implications with IT law.
Please refer to below footnote.
## Third year students are required to take 1 Poly-Wide elective module
Please note: Course structure subjected to change.