Do I really need Python experience for this course?

Yes. AI300 is an advanced course designed for those who are already comfortable with Python programming and have completed AI200 or equivalent machine learning training. This course focuses on deploying ML models, not building them.

What kind of project will I build in the capstone?

You'll deploy a machine learning model for a real-world fintech problem. This includes building a Flask web app, containerizing with Docker, deploying on AWS, and setting up CI/CD pipelines. The capstone is a production-level portfolio piece that demonstrates your MLOps skills to employers.

How is AI300 different from other online ML courses?

AI300 focuses on production ML, not model building. You'll learn the software engineering and cloud computing skills that employers are desperately looking for: database management, version control, containerization, and CI/CD. Taught by senior engineers from Google, GIC, and QuantumBlack.

Can this course help me get a job as a Data Scientist or ML Engineer?

Yes. AI300 provides the production-level skills and cloud experience needed for MLOps and ML Engineering roles. Combined with AI100 and AI200, you'll earn the AI Nanodegree, a complete career pathway certificate for data science and ML engineering positions.

MLOps (Machine Learning Operations) is the practice of deploying, managing, and scaling ML models in production. In AI300, you'll learn the complete MLOps lifecycle: database management, version control, containerization, cloud deployment, CI/CD, and A/B testing.

How much subsidy can I get for AI300?

Eligible Singaporeans and PRs can get up to 70% SSG subsidy. Singaporeans aged 40+ pay $936 after subsidy. Singaporeans below 40 and PRs pay $1,416. Stack SkillsFuture Credits, PSEA, and UTAP to reduce fees further.

Can I take AI300 part-time?

Yes. AI300 offers flexible schedules with full-day and part-time options. All sessions are recorded for catch-up. You can choose online or in-person classes whilst working full-time.

What tools and platforms will I learn?

You'll master AWS (cloud deployment), Docker (containerization), Flask (web apps), Git & GitHub (version control), SQL (databases), and CI/CD pipelines. All tools are industry-standard and used by top tech companies.

AI Nanodegree

Deploy Machine Learning Models to Production

Go from model builder to production engineer. This advanced course teaches you to deploy, manage, and scale real-world ML systems on the cloud using AWS, Docker, and CI/CD.

Apply NowSee Upcoming Schedule

Train Your TeamGet A Quote

Beginner-friendlyZero-Coding Skills Needed

20,000+Skilled Professionals

Industry PractitionersNot just theorists

Up to 70% OffWith SSG, SFC, PSEA & UTAP

3,000+5-star reviews

Skills That Pay Off

From Model to Production

Master MLOps

Learn the end-to-end process of taking a machine learning model from your laptop to a live, production environment.

Deploy on the Cloud

Get hands-on experience with AWS, Azure, and Google Cloud Platform — the leading cloud platforms for MLOps.

Become a Senior AI/ML Engineer

This course equips you with the advanced skills needed to move into a senior or lead machine learning role.

Future-Proof Your Career

As AI becomes more integrated into business, MLOps will become an essential skill for all software engineers and data scientists.

54%of employers consider AI fluency a key hiring qualification

3 in 4workers in Singapore now use AI tools at work

85%of AI users report gains in productivity & work quality

2 in 3AI-adopting firms are redesigning jobs to integrate AI

Source: IMDA Digital Economy Report 2025

Is This Course For You?

The AI200 Graduate

You have mastered building and training models in AI200. Now you are ready to learn how to put them into production and complete your journey to earning the full AI Nanodegree.

The Data Scientist

You can build powerful predictive models but rely on others to deploy them. Gain the independence to manage the end-to-end ML lifecycle and increase your value exponentially.

The Aspiring ML Engineer

You want a career in MLOps or Machine Learning Engineering. This course provides the exact production-level skills and cloud experience needed to land these high-demand roles.

The Software Engineer Adding ML Skills

You're an experienced backend or full-stack engineer who wants to expand into AI. AI300 bridges the gap — giving you the MLOps and deployment patterns to own end-to-end ML systems.

Skills You'll Gain

AWS Deployment

Docker

CI/CD Pipelines

MLOps

Flask Web Apps

API Development

SQL Databases

Git & GitHub

Object-Oriented Programming

A/B Testing

Real People. Real Skills. Real Change.

These aren't polished case studies — they're honest accounts from working professionals who decided to learn something new and discovered what they were capable of.

Explore Learners Projects

What You Will Actually Build

AI300 is the final, crucial step in our AI Nanodegree program. This advanced course moves beyond model creation and into the world of production machine learning. You will learn the entire software engineering stack required to deploy robust, scalable ML systems on the cloud.

Course Modules

The course culminates in a capstone project where you will deploy a model for a real-world fintech problem, giving you the production-level portfolio piece that sets you apart.

Software Engineering Foundations

Master the building blocks of production code. Use SQL for database management, Git for version control, and the principles of Object-Oriented Programming (OOP).

Building ML Web Applications

Learn to wrap your machine learning model in a web application using Flask and expose its functionality to the world through an API.

Deployment & Cloud Operations

Take your application to the cloud. Learn to containerise your app with Docker and deploy it on Amazon Web Services (AWS) for live, scalable access.

Production Best Practices

Automate your workflow with CI/CD pipelines for continuous integration and deployment, and learn how to conduct A/B testing to evaluate model performance in a live environment.

Pre-class Preparation

Access all course materials and assignments through our dedicated online e-learning portal.
Utilize onboarding resources to familiarize yourself with prerequisite concepts and tools before the course begins.
Receive personalized guidance and support from our instructors and teaching assistants to resolve any issues.
Join our Telegram channel to network with fellow students, alumni, and tech hiring managers.

Lesson 1: Introduction to Database Management with SQL (Part I)

Lesson 2: Database Management with SQL (Part II)

Lesson 3: IDEs, Git and GitHub

Lesson 4: Object-Oriented Programming (OOP)

Lesson 5: Building Web Application with Flask

Lesson 6: Application Programming Interfaces (APIs)

Lesson 7: Deployment with Docker and AWS

Lesson 8: CI/CD and A/B Testing

Course Fees & Subsidies

We believe upskilling should be accessible. Eligible learners can tap on IBF-STS funding, SkillsFuture Credits and UTAP to reduce course fees.

User Group

Course price
before subsidy

Course price
after IBF

Course price after IBF
+ Stack your $500 SFC

Singaporeans aged 40 and above

IBF 70%SFCUTAP

Course Fees (incl. GST)

$2,616.00 (incl. GST)

After IBF subsidy

$936.00save $1,680.00 (64%)

Stack additional $500 SFC

$436.00save $2,180.00

Singaporeans aged 16-39 & PRs aged 16+

IBF 50%SFCUTAP

Course Fees (incl. GST)

$2,616.00 (incl. GST)

After IBF subsidy

$1,416.00save $1,200.00 (46%)

Stack additional $500 SFC

$916.00save $1,700.00

Foreign nationals, non-PRs

No Subsidies

Course Fees (incl. GST)

$2,616.00 (incl. GST)

After IBF subsidy

$2,616.00

Stack additional $500 SFC

—

* You may pay even less by stacking with PSEA and UTAP. Use our Subsidy Calculator to find out the exact amount you'll pay.

IBF Funding IBF-STS funding available for eligible finance professionals

Find out how

SkillsFuture Credits Use to offset fees for Singaporeans aged 25+

Find out how

UTAP for NTUC Members Claim up to 50% of remaining fees (max $500/year)

Find out how

SkillsFuture Enterprise Credit (SFEC) Employer-sponsored credit for enterprise-supported training

Find out how

Select preferred slot:

Saturday Classes

9 May → 27 Jun 2026Every Saturday

9.00am → 12.00pm

Online (Zoom)

Sat9May

Sat16May

Sat23May

Sat30May

Sat6Jun

Sat13Jun

Sat20Jun

Sat27Jun

Suitable for learners, part-timers

Taught by Industry Practitioners. Trusted by Employers.

At Heicoders, you learn from the real deal: engineers, data scientists and AI specialists from top companies. They bring insider knowledge, real-world strategies and the mindset employers look for. You don't just learn what to do. You learn how the best in the field do it.

That's how you'll gain the confidence to solve problems, speak the language of tech and stand out at work. So when you learn with Heicoders, you're not just preparing for the job. You're learning from people already doing it and rooting for you to join them.

Our Instructors

Beh Min Yan

CEO & Principal Instructor

Masters of Informations System, Carnegie Mellon University

Kong Yu Ning

Chief of Growth & Principal Instructor

Masters of Management Science & Engineering, Columbia University

Chan Yu Siang

Chief of Training & Standards & Principal Instructor

Masters of Computing, Singapore Management University

Beh Wei Chen

Chief Technology Officer & Principal Instructor

MSc, Georgia Institute of Technology

Darryl Wang

Senior Data Science Manager, LINE MAN

MSc Analytics, Georgia Institute of Technology

From Individuals to Organisations, Real Results Happen Here

Huang Zhiwhei

★★★★★

"Instructors are not only technically excellent but also very approachable and great at delivery — unlike most educational institutes."

Huang Zhiwhei completed AI100, AI200, and AI300, plus a stocks investing course. He praised instructors Ryan and Shauna (AI100) and Min Yan (AI200, AI300) for their clarity and approachability, contrasting favourably with university-style teaching.

AI100AI200AI300

Carlos

★★★★★

"AI300 covered the necessary aspects of deploying models on a cloud platform — directly relevant to the real working world."

Carlos found AI300 engaging and practical, with instructor Min Yan making lessons livelier by weaving in real work stories. He appreciated the course's focus on cloud deployment and MLOps.

AI300

Kelly Lee

★★★★★

"Instructors were very knowledgeable and patient. The Telegram group ensures questions are answered promptly even after class."

Kelly attended SE100, AI200, and AI300 at Heicoders. She found the course notes clear and easy to follow, and also benefited from career support — using the resume template to land several interviews.

SE100AI200AI300

FAQs on Deploying Machine Learning Systems Course

Is AI200 really a mandatory prerequisite?

Yes, absolutely. AI300 builds directly on the models and concepts taught in AI200. This is an advanced course, and a solid understanding of building and training ML models is required for you to succeed.

What is MLOps and will I learn it in this course?

How is this different from AI200?

What do I get for completing the AI Nanodegree?

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We reply within 24 hours

Find the right course for you and your team

Our experts will help match you to a learning path tailored to your goals.

Drop us an email

Tell us a little about yourself and we'll be in touch.

Deploy Machine Learning Models to Production

From Model to Production

Master MLOps

Deploy on the Cloud

Become a Senior AI/ML Engineer

Future-Proof Your Career

Is This Course For You?

The AI200 Graduate

The Data Scientist

The Aspiring ML Engineer

The Software Engineer Adding ML Skills

Skills You'll Gain

Real People. Real Skills. Real Change.

What You Will Actually Build

Course Modules

Software Engineering Foundations

Building ML Web Applications

Deployment & Cloud Operations

Production Best Practices

Stack This Course Into A Nanodegree

Course Fees & Subsidies

Pay less than $436.00 for this course!

Select preferred slot:

Saturday Classes

Taught by Industry Practitioners. Trusted by Employers.

Our Instructors

Beh Min Yan

Kong Yu Ning

Chan Yu Siang

Beh Wei Chen

Darryl Wang

From Individuals to Organisations, Real Results Happen Here

FAQs on Deploying Machine Learning Systems Course

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