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Course Overview

The ever-evolving landscape of AI makes it a necessity to continuously update course curricula to align with current trends and technologies. Incorporating modules on cloud development and Generative AI help to ensure that graduates have the technical prowess to navigate the current technological landscape and meet the evolving demands of the industry.


The synergy between AI and cloud computing has proven instrumental in accelerating innovation and providing scalable solutions across industries. A large number of organisations are transitioning to cloud-based AI services due to their convenience, scalability, and cost-effectiveness. By incorporating a module on cloud development, we aim to equip students with practical skills for creating, deploying, and managing AI solutions on cloud platforms. This addition will ensure that graduates have the technical prowess to navigate the current technological landscape and meet the evolving demands of the industry.


Generative AI, as demonstrated by models like GPT-3 and DALL-E 2, as well as applications such as ChatGPT, has showcased the unprecedented capabilities in creating original, high-quality outputs, revolutionising fields from content creation to design and arts. Including a comprehensive module on Generative AI will enable students to grasp the underlying principles and potential applications of these transformative technologies. By understanding how AI can create unique content, students will be better positioned to contribute to innovation and creativity in their respective careers.


The course aims to provide students with a balanced understanding of both the theoretical principles and practical applications of AI. This will keep the course content up to date with the latest advancements, enhancing the curriculum's industry relevance and graduates’ competitive advantage in the job market. Additionally, it will provide students with the necessary skills to effectively engage with AI in the future of work.



All students are required to bring their own notebooks for lessons. You may refer to the required technical specifications for notebooks HERE.

Entry Requirements

Minimum Entry Requirements


A Polytechnic Diploma or ITE Technical Diploma / Technical Engineer Diploma / Work-Learn Technical Diploma in Science, Technical, Engineering, Math (STEM) or equivalent


OR A Bachelor’s Degree or equivalent


OR A Post-Secondary Certificate with at least 3 Years of relevant working experience

Who Should Attend

This program is suitable for working IT professionals, IT entrepreneurs, IT business owners, or individuals with software development experience seeking strategic change in using AI to drive digital transformation. The course will deepen their skills in the areas of cloud computing, machine learning, deep learning, and natural language processing to capture opportunities in the AI industry.

What You'll Learn

Upon graduating from the course, graduates should be able to:


  • Understand the Intersection of Cloud and AI: Gain a deep understanding of the dynamic nexus between cloud computing and machine learning, including leveraging cloud platforms for scalable machine learning solutions.
  • Develop Hands-on Machine Learning Skills: Acquire practical skills in designing, deploying, and managing machine learning models in cloud environments, ensuring optimized performance and scalability.
  • Master Data Engineering for ML: Learn the intricacies of data collection, storage, preparation, analysis, and visualization tools, essential for analytics and machine learning applications.
  • Explore Advanced Deep Learning Concepts: Delve into complex deep learning architectures like neural networks, convolutional architectures, and recurrent models, and apply these in domains like computer vision and natural language processing using cloud infrastructures.
  • Harness Generative AI Techniques: Obtain hands-on experience with generative AI, learning to train and deploy Large Language Models and image generation services like Stable Diffusion in the cloud, and master prompt engineering to optimize generative outputs.


To be awarded the Specialist Diploma, participants are required to complete a total of 2 Post-Diploma Certificates (PDCs). A certificate will be issued upon successful completion of each PDC.

Subject Code Subject
CAI1C015 Fundamentals of Cloud Computing & Machine Learning

This subject introduces students to cloud computing concepts and the fundamental concepts of machine learning. Students will learn the security and architecture of cloud platforms, and a range of model-based and algorithmic machine learning methods, including regression and classification. Students will also gain a solid understanding of leveraging cloud platforms to label, build, train, and deploy a custom machine learning model through a guided, hands-on approach.

CAI1C016 Building Machine Learning Pipelines

This subject aims to equip learners with practical skills and knowledge related to data collection, storage, preparation, analysis, and visualisation tools commonly used in analytics and machine learning (ML) applications. As part of the course, students will delve into case studies derived from real-world scenarios. This exposure will empower them to make well-informed decisions when constructing data pipelines tailored to their specific applications. The course is structured to provide a balanced mix of theoretical knowledge and hands-on experience to ensure an in-depth understanding of data engineering concepts.

Subject Code Subject
CAI1C017 Deep Learning & Natural Language Processing

This subject introduces the fundamental concepts of deep learning neural network and Natural Language Processing. It covers concepts of several deep learning methods such as Convolutional Neural Network, Recurrent Neural Networks and Transformers that can be applied to fields such as computer vision and natural language processing. Students will learn cloud-based deep learning solutions by leveraging cloud platforms for training and deployment, implementing these solutions to different problems using cloud machine learning services.

CAI1C018 Generative AI in Practice

This is an immersive subject designed to provide learners with hands-on experience in leveraging generative artificial intelligence techniques. Participants will learn to train Large Language Models (LLMs) using custom data, cultivating a deeper understanding of their structure and parameters. They will gain practical skills in deploying image generation services on the cloud using existing models such as Stable Diffusion. Additionally, the course will cover prompt engineering and help learners understand prompt structures to optimise generative outputs. By the end of the course, participants will be equipped with the knowledge and tools to create and deploy their own custom generative AI models in a cloud environment, expanding their creative possibilities.

Modes of Assessment


The assessment would be based on a combination of coursework components such as written test /quiz, projects and presentations.

For more information on course fee / schedule, or to apply,

Career Opportunities

This course provides job opportunities for graduates to pursue AI/ML Engineer positions across the various sectors, leveraging their skills and knowledge in cloud-based AI technologies. They will also have the opportunity to apply their skills in Generative AI to develop cutting-edge and imaginative AI solutions.


Upon completing the part-time diploma course, graduates can look forward to taking up the following types of roles:


  • Machine Learning Engineer
  • Data Analyst
  • AI Developer
  • Natural Language Processing (NLP) Engineer
  • AI Consultant
  • Prompt Engineer

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Course Contact

  • Mainline 67881212
  • Monday - Thursday: 8:30am - 6:00pm
    Friday: 8:30am - 5:30pm
    Closed during lunchtime, 12:00pm - 1:00pm
    and on weekends and public holidays.

  • https://www.tp.edu.sg/tsa
  • Temasek SkillsFuture Academy (TSA)
    Temasek Polytechnic
    East Wing, Block 1A, Level 3, Unit 109
    21 Tampines Ave 1
    Singapore 529757

  • Temasek Polytechnic reserves the right to alter the course, modify the scale of fee, amend any other information or cancel course with low enrolment.