The AI Apprenticeship Programme (AIAP)® was created to meet AI Singapore’s requirements for AI professionals. It grew out of a need for a core group of Singaporean AI talents working in AI Singapore, solving both Singapore’s and Singapore companies’ problem statements with AI.

While we hire from the open market, we could not find sufficient Singaporean AI talents, so we created our programme – the AIAP – to identify, train and groom these talents.

We focused on self-directed, passionate Singaporeans with some of the required AI technical knowledge and skills but may not have the opportunity to undertake real-world AI projects. We felt these Singaporeans could be offered a 2-month intensive deep-skilling training and then be put into a 7-month real-world AI project.

Today, AIAP is recognised as the leading AI deep-skilling programme in Singapore and the world. Many organisations and countries are learning from us and are trying to replicate our AIAP + 100E model. So, join us and experience the AIAP way.

application for AIAP Batch 17 Is Now Closed!

Timeline for AIAP Batch 17

Application Period

26 March – 21 April 2024

Technical Assessment

24 – 29 April 2024

Invitation to Interview

27 May 2024

Interview (Virtual)

1 June 2024


28 June 2024

Programme Period

2 September 2024 – 6 June 2025

Programme Period (Mature Mid-Career)

2 September 2024 – 5 September 2025

AIAP Batch 18 will open for applications on 14 June 2024!

Please sign up for our mailing list to stay informed of AIAP timelines and join our AI community at ConnectAI! For learning resources, head to LearnAI, use the AIAP Field Guide, or test your proficiency using our Past Years Series.

application for AIAP Batch 18 Is Now Open!

Timeline for AIAP Batch 18

Application Period

14 June 2024 – 14 July 2024

Technical Assessment

17-22 July 2024

Invitation to Interview

26 August 2024


7 September 2024


21 October 2024

Programme Period

20 January 2025 – 24 October 2025

Programme Period (Mature Mid-Career)

20 January 2025 – 23 January 2026

Real-world AI

Going beyond Jupyter notebooks to deploy real-world aI systems

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 real-world projects and deepen their skills in AI and machine learning (ML), and software engineering as they learn to deploy AI models into production.


Full Time

AIAP is a full-time programme. Apprentices will learn and work in AISG’s office Monday-Friday, 9 am – 6 pm.


2 + 7/10* months

2 months of deepskilling in AI Engineering and 7 months of on-the-job training on a real-world AI problem from the industry.

*For Singaporeans who are 40 years & above, the programme is extended for another 3 months (optional) where you will be assigned to project teams within AI Singapore to get additional business and technical hands-on experience.


Python & AI/ML

Candidates must have technical competency with Python and AI/ML. See competency requirements here.


$3.5k – $5.5k

A monthly training allowance of SGD 3,500 to 5,500 will be provided (dependent on no. of years of relevant working experience and qualifications).

The AIAP Life

Programme Structure

AIAP 9 Months Programme Structure

Apprentices will benefit from a range of content to gain exposure to machine learning concepts, develop career and technical assessment skills and ultimately, instil 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 the 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 the fundamentals of neural networks
  • Learn the process and methods for computer vision tasks
  • Learn the process and methods 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 utilise tests appropriately
  • Learn how to maintain proper and clear documentation
Self-directed Learning

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

Tailored Learning Discussion

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

100 Experiments

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.


Apprentices assigned Prompt Engineering projects will be equipped with in-depth knowledge and skills in Prompt Engineering, which is an emerging field in AI that specializes in creating and refining prompts, to effectively leverage the remarkable capabilities of Large Language Models to complete a diverse range of tasks.

Data Engineering

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.

AI Platforms

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.

Federated Learning

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.


Minimum Requirements

  • Singaporean
  • Graduated from a recognised University or Polytechnic
  • Eligible for TeSA CLT Funding

Competency requirements

  • Intermediate programming experience in one of these languages: Python, R, Scala, Java, C, C++, C#, Go.
  • Understand basic data pre-processing (handling missing data, outliers etc…)
  • Able to build machine learning models
  • Able to build data pipelines to train and build your models
  • Able to perform basic code documentation (Readme, docstrings and requirements.txt)
  • Able to deploy your models in Docker containers
  • Able to provision and use cloud computing infrastructure such as Google Cloud, Microsoft Azure or AWS.
  • Able to do Linux shell scripting
  • Able to use at least one of the following databases and data processing technologies such as SQL, NoSQL, Apache Hadoop and/or Apache Spark
  • Able to use GitHub/GitLab and perform proper code check-in/out and repository

Becoming an AI Apprentice

All candidates will be invited to the technical assessment via their registered email 

The technical assessment consists of two parts:

  • Exploratory Data Analysis
  • End-to-end machine learning pipeline

You are to complete the above-mentioned tasks based on a given problem statement within a given time frame. Your exploratory data analysis is to be performed in a Jupyter notebook (.ipynb file format). Your end-to-end machine learning pipeline is to be developed in Python scripts (.py file format).

Your submission will be assessed in the following four areas:

1. Appropriate data processing methods

2. Insightful exploratory data analysis

3. Appropriate model development pipeline

4. Programming proficiency

If you pass the technical assessment, you will be shortlisted to proceed to interview stage. This will involve a Technical presentation & Group exercise Please note: Shortlisted candidates are expected to present their technical solution which was submitted for the technical assessment.

The interview stage consists of two parts.

In the first part, you are given 10 minutes to present your technical assessment submission. The content of the presentation is decided by you. You can present directly from your submission (README, Jupyter Notebook) or prepare slides (PowerPoint, Google Slides).

The second part of the interview requires you to work on a case study together with 1 – 2 other candidates. The case study is only disclosed on that day itself.

Click HERE for Frequently Asked Questions

Tips from mentors and apprentices

Companies which Have hired our Apprentices

Ready to Become an

AI Apprentice?

Please sign up for our mailing list to be kept updated about the AI Apprenticeship Programme. You may also wish to join our AI community over at ConnectAI! And those who need some learning resources, use the AIAP Field Guide or test your technical proficiency using our Past Years Series.

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