Blog > Careers & Salary>AI Singapore’s AIAP: Your Complete Guide & How Heicoders Academy Prepares You
AI Singapore’s AIAP: Your Complete Guide & How Heicoders Academy Prepares You
The AI Apprenticeship Programme (AIAP) by AI Singapore (AISG) is one of the most coveted pathways for Singaporeans looking to transition into machine learning and AI roles. Like the Technology in Finance Immersion Programme (TFIP) we previously covered, AIAP combines structured training with real-world industry projects.
The good news? AIAP has rolling intakes nearly every two months, which means you won’t have to wait long to try again if you don’t succeed the first time. In fact, many successful applicants didn’t pass on their first attempt, but used the assessment as a valuable benchmark to identify gaps and track their progress.
You’re encouraged to keep trying, and each attempt brings you one step closer.
This article outlines what AIAP involves, what to expect during the selection process, and how Heicoders Academy’s Artificial Intelligence Nanodegree can give you a competitive edge.
What is AIAP?
AIAP is a nine-month full-time programme designed to groom Singaporean AI talent. The first two months focus on intensive AI engineering training, while the remaining seven months place apprentices on real-world projects with AISG’s 100 Experiments team and industry partners.
Applicants must demonstrate:
- A solid foundation in Python and machine learning concepts
- The ability to pass a technical assessment and an interview
Programme Benefits
✅ Real-world experience: Work on industry-grade projects and learn how to deploy AI models into production
👥 Mentorship & network: Learn from experienced AISG engineers and join a growing AI alumni community
💰 Monthly stipend: Offset opportunity cost with a stipend of SGD 3,500–5,500
🚀 Strong employment outcomes: Apprentices often secure full-time roles with their host companies or leverage their project portfolio to land AI/ML roles elsewhere in the industry.
Inside the AIAP Selection Process
Technical Assessment
This is a take-home exercise that tests your ability to build an end-to-end machine learning pipeline. Specifically you will have to demonstrate abilities in the following areas:
- Part 1: Exploratory data analysis (EDA) on an unseen dataset, involving data extraction, loading, and analysis
- Part 2: Build and evaluate multiple ML models, justify design choices, and demonstrate reproducibility
- Part 3: Deployment of your ML models to a major cloud platform
Your submission should include:
- Jupyter notebook
- Python scripts
- Bash scripts
You’ll be assessed on software engineering best practices, reproducibility, documentation, and model experimentation.
Interview & Group Case Study
If you pass the technical assessment, you’ll:
- Present your solution during a technical interview
- Participate in a group case study to assess collaboration and adaptability
Expect to be evaluated on:
- Problem-solving ability
- Communication of technical ideas
- Teamwork in a simulated real-world setting
Here is a great resource to give you a sense of how it feels like to undergo a data science case study:
Skills You Need to Succeed in APA
Getting into the AIAP programme is just the beginning. The training is intense and fast-paced, it assumes you already have a strong foundation in both theory and practice. To keep up, you’ll need to hit the ground running from day one.
Below are the core skill areas you should be comfortable with before starting the programme. These aren’t just nice-to-haves — they’re essential for both the technical assessment and your success during the apprenticeship.
| Core Skill | Why It’s Important |
| Statistics & Data Analytics | Helps you make sense of distributions and perform meaningful EDA |
| Python (Pandas, NumPy, scikit-learn, PyTorch) | Enables effective data manipulation and model building |
| Machine Learning & Evaluation | You need to build and justify multiple models with appropriate metrics |
| Software Engineering & MLOps | Demonstrates reproducibility and code maintainability |
| Deployment Know-How | Many projects require taking models from notebook to production |
These are the same foundations we cover extensively in Heicoders Academy’s AI100, AI200 and AI300 series.
How Heicoders Academy Prepares You for AIAP
Heicoders Academy’s AI Nanodegree is designed to help non-tech professionals build the necessary skills to break into AI:
🧩 AI100: Python Programming & Data Visualization
- Learn Python and data visualisation
- Wrangle datasets and perform EDA — skills crucial for Part 1 of the technical assessment
- Gain confidence working with real-world datasets
⚙️ AI200: Applied Machine Learning
- Master supervised and unsupervised learning
- Learn model selection, build end-to-end machine learning models, perform hyperparameter tuning, and evaluation metrics
- Prepare for Part 2 of the assessment with hands-on model experimentation
🚀 AI300: Deploying Machine Learning Systems to the Cloud
- Learn deployment tools like Docker, CI/CD pipelines, and cloud services
- Learn database management and how to write SQL scripts
- Package notebooks and scripts for production environments using Visual Studio Code
- Demonstrate software engineering (OOP principles) and reproducibility best practices
- Prepare for Part 3 of the assessment with deployment of the models
AIAP is highly competitive, and gaining entry isn’t easy — the assessment is intentionally rigorous to identify candidates with strong foundations in AI and ML.
That said, we’ve seen encouraging outcomes from learners who’ve completed at least AI100 and AI200 with us. While individual results will always depend on each learner’s effort and aptitude, these courses are designed to build the exact competencies that AI Singapore looks for in its selection process.
Tips for a Successful AIAP Application
Based on guidance from Heicoders Academy mentors and past applicants:
✅ Build a strong portfolio: Showcase end-to-end projects on GitHub or Kaggle
✅ Master the fundamentals: Brush up on statistics, Python, and ML concepts — AI100–AI200 will help
✅ Practice EDA & model comparison: Use public datasets to explore and compare models
✅ Use version control: Learn Git and reproducibility tools — a must for AIAP submissions
✅ Prepare for the interview: Be ready to explain your project decisions and work well in teams
✅ Join the community: Many of our learners connect via our Telegram group, where they can ask for advice from past AIAP applicants and graduates. Some students even form their own study groups to prep together — a great way to stay motivated and learn collaboratively.
Conclusion: Turn Your AI Ambitions into Reality
AI Singapore’s AIAP is a rigorous yet deeply rewarding programme for aspiring AI professionals. Its selection process is intentionally challenging — designed to identify candidates with the readiness and resilience to thrive in real-world AI environments.
The good news? With the right preparation, it’s absolutely within reach.
At Heicoders Academy, our AI100–AI300 course pathway has helped many learners build the exact competencies AIAP looks for — from Python, machine learning, to MLOps, and deployment.
While every applicant’s journey is unique and depends on their effort and aptitude, we’ve seen encouraging outcomes among learners who completed at least AI100 and AI200 with us.
If you’re serious about launching a career in AI, now is the time to take that first step. Let us guide you on that journey. If you want to talk to our in-house Career advisor who still works at the senior management level in the tech industry, you can call us at 8801 7933.
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