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Application for AI Apprenticeship Programme Batch 11 is now closed.

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AI Apprenticeship Programme (AIAP)® 

Growing our own timber

Programme Structure

The AI Apprenticeship Programme (AIAP)® seeks to develop Singaporean AI talents and enhance career opportunities in AI-related roles. Apprentices will get to work on industry projects and deepen your skills not only in AI and machine learning (ML) but also in software engineering as you learn to deploy AI models into production.

Training Phase (2 Months)

Apprentices will benefit from a range of content, with the intention of gaining exposure to machine learning concepts, develop career and technical assessment skills and ultimately, to instill confidence to solve problems and handle the unknown. ​


Part 1- Machine Learning Fundamentals
Perform thorough exploratory data analysis and ability to utilise traditional machine learning models to solve AI/ML problems  

Topics covered:

  • Learn how to acquire and clean data for AI/ML workloads
  • Ability to clean and pre-process data appropriately for ML models
  • Learn how to conduct thorough exploratory data analysis
  • Learn how to feature engineer for AI/ML models
  • Understand fundamentals behind the different clustering models and when to apply such models
  • Ability to utilise dimensionality reduction techniques

Part 2 – Advanced Courses in Machine and Deep Learning
Use neural networks and deep learning techniques to solve problems

Topics covered:

  • Understand fundamentals of neural networks
  • Learn the process and methodologies for computer vision tasks
  • Learn the process and methodologies for natural language processing tasks   

Part 3 – Deployment
Containerise and deploy an AI/ML model         
(Note: Trainees will have to submit Python scripts and demonstrate a web application)    

Topics covered:

  • Understand fundamentals of application deployment
  • Understand how to appropriately utilise tests
  • Learn how to maintain proper and clear documentation

Learning is self-directed. Every week, apprentices will tackle individual assignments, explore existing solutions and contribute to extensive discussions with mentors and field experts.​

We tailor discussions to extend an apprentice’s knowledge, challenge them to think more deeply and also to impart the thinking and research skills essential to remaining relevant.​

Project Phase (AI Project Tracks)

In 100E projects, apprentices help companies to solve real-world business problems using AI. These companies span industries such as education, engineering, FMCG, healthcare, insurance, maritime and travel, as well as government agencies. You will build minimum viable products consisting of AI models and end-to-end pipelines which will be deployed into production. 100E projects allow you to experience what it is like to work with clients and stakeholders while developing applications that cover a wide range of AI technologies in computer vision, natural language processing and general ML.

Computer Vision Hub projects give apprentices the opportunity to solve real world problems using cutting-edge computer vision models for pose estimation, object detection, image segmentation and activity recognition. You will learn to combine these models and algorithms to develop unique computer vision solutions.

The NLP Hub exposes apprentices to common NLP problems that industries face, and ways of addressing them through end-to-end solutioning that goes beyond model deployment. You will learn how to solve problems such as question answering and summarisation, and package them into open-source solutions for industry and the community to use.


AI Bricks are plug-and-play ML tools that allow users to learn, build and deploy simple ML solutions. You will have the opportunity to develop AI Bricks based on published papers and source code from leading AI researchers in Singapore as well as feedback from the industry, and create usable solutions and products for businesses.

Through data engineering projects, you will learn how to develop a secure data management platform to support rapid iteration of ML experiments and enable the results to be reproduced. In addition to traditional data management features such as security and availability, the platform will enable data onboarding, discovery, data governance as well as integration with ML frameworks.

You will learn to build robust AI and ML applications using modern infrastructure and tools. Aligned with AI/ML best practices, these platforms empower researchers, engineers and collaborators to work together on projects such as the development of AI Bricks, and to solve challenging business problems.

You will have the opportunity to work on Synergos, a federated learning system platform developed by AI Singapore. The Synergos platform enables organisations to train a machine learning model collaboratively without exposing data to one another. This helps to address the privacy concern associated with explicit data sharing.

SecureAI lies at the intersection of ML, systems and security. You will work with experts from the fields of AI, ML, adversarial learning methods and computer systems security to identify risks and improve the safety, robustness and trustworthiness of AI systems.

You will get to work on an audit framework that allows Chartered AI Engineers (CAIE) to confidently sign off on AI projects. Leveraging industry best practices and existing open source frameworks, the audit will assess AI projects from an end-to-end perspective encompassing data, modelling, deployment and ethics and governance, and lead to the AI Trust Mark (AITM) award.

Life in AIAP

minimum Requirements

Knowledge and proficiency requirements

Recruitment Process

Assessment 1

  • Assessed topics include Python, SQL, Software Engineering and AI & ML.
  • Passing mark: 72
  • Total duration: 60 minutes 
  • Number of attempt: 1
  • For more information on the Assessment 1, click here

Assessment 2

  • 6 days to perform exploratory data analysis in iPython notebook (.ipynb file format) and build an end-to-end machine learning pipeline in Python scripts (.py file format)
  • Submission will be assessed in the following four areas: Appropriate data processing methods, Insightful exploratory data analysis, Appropriate model development pipeline and Programming proficiency
  • For more information on the Assessment 2, click here

Assessment 3

  • Prepare a presentation of the Assessment 2 submission.
  • Problem-solve an undisclosed case-study with other like-minded applicants.
  • For more information on the Assessment 3, click here


Tips from mentors and apprentices

Want some tips? Learn about what we are looking for in a candidate!

Articles to help you get started on your AIAP journey!

After Graduating from AIAP

Find out how our graduates are doing after the programme

Companies which hired our apprentices

Timeline for AIAP Batch 11

Application Period
9 May - 5 June 2022
Assessment 1 Due Date
6 June 2022
Invitation to Assessment 2
by 8 Jun 2022
Assessment 2
15 - 20 Jun 2022
Invitation to Assessment 3 (Interview)
by 8 Jul 2022
Assessment 3 (Interview)
16 Jul 2022
by 8 Aug 2022
Programme Period
3 Oct 2022 - 7 Jul 2023
Programme Period (Matured Mid Career)
3 Oct 2022 - 6 Oct 2023

Application for Batch 11 is now closed

Frequently Asked Questions

Check out this page for FAQs on the AI Apprenticeship Programme. 

Keen to become an apprentice?

Move beyond books and MOOC, and gain real-world AI experience in the award-winning AI Apprenticeship Programme. 

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AIAP® is a registered mark filed under the Singapore Trade Marks Act 1998 with the trade mark number 40201927366U.   

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