AI for Industry (AI4I) is open for registration

Rolling admissions starts now! Register at any time and begin learning

AI for Industry (AI4I)®

AI for Industry (AI4I) is a fully online programme to help learners PLUS-skill themselves and learn data science, machine learning, artificial intelligence and visualization in Python. The programme is hosted on the AI Makerspace online platform.  DataCamp  is used as a resource to support the learning required to complete the programme. Register any time and start learning!

Programme Structure

This programme consist of 2 parts:
1. Literacy in AI
2. Foundation in AI

Upon completion of each part, you will receive a certificate of completion.

AI4I – Literacy in AI

Literacy in AI is a 5-hour course which introduces modern AI technologies and applications so that you can be savvy consumers of AI products and services. You will learn how to identify opportunities and potential use cases in your work and daily lives, and build a simple AI model with online tools.
**AI4I – Literacy in AI is a prerequisite of AI4I – Foundations in AI. A learner will have to complete this module before you can start with AI4I – Foundations in AI.

AI4I – Foundations in AI

Foundation in AI is a 140 hours course which introduces to the technically inclined individuals to understand and use AI appropriately and be able to program basic AI and data applications in Python.


Programme Objectives

This programme aims to introduce AI to the learners and impart programming skills to allow learners to build basic AI models and applications.

Programme Flow


Literacy in AI

AI4I – Literacy in AI consists of a series of basic lessons consisting primarily of short videos, quizzes and examples for an introduction to AI.

List of Lessons

Lesson 1: What is AI? (Part 1)
Lesson 2: What is AI? (Part 2)
Lesson 3: Why AI now?
Lesson 4: Getting to AI (Part 1)
Lesson 5: Getting to AI (Part 2)
Lesson 6: What AI cannot do
Lesson 7: Build an AI System
Lesson 8: AI, Jobs and You
Lesson 9: Modern AI Apps
Lesson 10: Are You Ready for AI?
Lesson 11: AI4I-Basic Practice
Lesson 12: AI4I-Basic Additional Practice

Foundations in AI

The python programming language is one of the most popular languages that data professionals use to do data analytics and AI. In this section, you will practice Python basics which act as a foundation for the rest of the sections in this course.

List of Lessons
Lesson 1: Introduction to Python (DataCamp)
Lesson 2: Python Data Science Toolbox (Part 1) (DataCamp)
Lesson 3: Python Data Science Toolbox (Part 2) (DataCamp)

What makes Python so powerful is that people like yourselves have written ‘libraries’ or toolkits that condense and optimize complicated programming methods to simple commands for us to use quickly and easily. Learning how to use libraries is a key skill in becoming a proficient data professional.

List of Lessons
Lesson 4: Intermediate Python (DataCamp)
Lesson 5: Cleaning Data in Python (DataCamp)
Lesson 6: pandas Foundations (DataCamp)
Lesson 7: Manipulating DataFrames with pandas (DataCamp)
Lesson 8: Merging DataFrames with pandas (DataCamp)

The first order of business whenever you get a new dataset is to explore it. In this section, we will learn the best practices for exploring and visualizing data.

List of Lessons
Lesson 9: Introduction to Data Visualisation in Python (DataCamp)
Lesson 10: Preprocessing for Machine Learning in Python (New – DataCamp)
Lesson 11:  Feature Engineering for Machine Learning in Python (New – DataCamp)
Lesson 12: Feature Engineering for NLP in Python (New – DataCamp)

To understand your data and find out the hidden properties you need to account for, a grounding in basic statistical thinking is required. This is the core foundation to reliable machine learning models.

List of Lessons
Lesson 13: Statistical Thinking in Python (Part 1) (DataCamp)
Lesson 14: Statistical Thinking in Python (Part 2) (DataCamp)
Lesson 15: Dimensionality Reduction in Python (New – DataCamp)

“Tell the machine that something is a cat over and over again, and it will start to learn the properties that separate cat pictures from other pictures”. Supervised learning is a machine learning task to learn a function that maps a given input to a given output (X -> Y). It is one of the most common and basic types of machine learning used in data science and AI.

List of Lessons
Lesson 16: Supervised Learning with scikit-learn (DataCamp)
Lesson 17: Regression (Part 2) (New – AI Makerspace)
Lesson 18: Classification (Part 2) (New – AI Makerspace)
Lesson 19: Machine Learning with Tree-based Models in Python (DataCamp)
Lesson 20: Model Validation in Python (New – DataCamp)

Challenge Yourself

  • XGBoost Gradient Boosting (New)
  • Machine Learning for Time Series in Python (New)

Unsupervised learning is a type of machine learning algorithm used to draw inferences from datasets consisting of input data without labeled responses. It is slightly more complex than supervised learning, as it requires human interpretation, but is still a key pillar of machine learning techniques used by data professionals.

List of Lessons
Lesson 21: Unsupervised Learning in Python (DataCamp)
Lesson 22: Clustering Methods in SciPy (New – DataCamp)
Lesson 23: Unsupervised Learning (Part 2) (New – AI Makerspace)

Deep learning is a sub-type of machine learning where the algorithms used are inspired by biology. It is responsible for many of the breakthroughs in recent times, but is more complex and requires more computational power.

List of Lessons
Lesson 24: Deep Learning in Python (DataCamp)
Lesson 25: Introduction to Tensorflow (New – DataCamp)
Lesson 26: Introduction to Keras (New – DataCamp)
Lesson 27: Deep Learning (Part 2) (New – AI Makerspace)

Challenge Yourself

  • Advanced Deep Learning with Keras (New)
  • Image Processing in Python (New)
  • Image Processing with Keras in Python (New)

Now that you have mastered the theoretical foundations of statistical learning and AI, how do you put it into practice in the real world?

List of Lessons
Lesson 28: Data Science and AI Project Lifecycle (New – AI Makerspace)
Lesson 29: Set up your own AI System using an AI Makerspace ‘brick’ (New – AI Makerspace)

Machine learning and AI do not just stop at Python and Deep learning. There are many other software tools, concepts and languages that good data professionals will need to be conversant with as they progress in their career. A well balanced data professional will be equally skilled at software engineering and AI engineering.

List of Lessons
Lesson 30: Introduction to SQL (DataCamp)
Lesson 31: Joining Data in SQL (DataCamp)
Lesson 32: Introduction to Shell (DataCamp)
Lesson 33: Conda Essentials 
Lesson 34: Hyperparameter Tuning in Python (New – DataCamp)
Lesson 35: Setting up your Environment (New – DataCamp)

Progressing beyond AI4I

Learners who completed AI4I modules are encouraged to progress by enrolling and completing “Becoming An AI Apprentice” course which is available FREE at AI Makerspace

Completion and mastery of the learning modules in “Becoming An AI Apprentice” course will allow the learner to attempt the technical test in the AI Certification Programme for the credentials of AI Certified Engineer Associate.  For more information, please refer to this page.


AI4I® is open for registration

Frequently Asked Questions

About the Course

Is the COVID-19 special price still available?

No, the COVID-19 special price has been fully redeemed.

Who is this programme for and what are the outcomes upon completion?

AI4I® is a fully online programme meant to provide technical executives, managers and developers a learning experience in building data and AI application using Python. Upon completion, you will be able to build basic data/AI applications.

I am currently working. May I know what is the commitment expected for the course?

When you sign up for the programme, the programme period is 12 months.  This is a fully online programme where you set your own learning pace. You are required to complete all the compulsory modules in order to receive the ‘Foundations in AI’ certificate.

Do I have to give up my current job to join the training programme?

No. This course is designed to enable professionals to continue to learn and up-skill at their own pace.

Will I get a certificate at the end of the course?

Yes, upon completion of the course, you will be awarded the Foundations in AI Certificate issued by AI Singapore.

What are the pre-requisites for the programme?

There are no pre-requisites to register for the programme.

After completing this programme, will I be able to find a job as an AI Engineer/Developer?

This programme is the entry point to becoming an AI Engineer / Developer. The goal is to build foundational skills to start your AI learning journey. 

What if I decide to drop out of the course?

Once you register for the course, you are not allowed to drop out / withdraw from the course. You may choose not to complete any of the learning.

Course Requirements

Do I need to be a Singaporean/ Singaporean PR to apply?

No. We welcome all to apply for the programme. 

What is the criteria for successful completion of the course?

You will have to achieve 100% score for all 9 quizzes from AI4I – Literacy in AI and 9 quizzes from AI4I – Foundations in AI

DataCamp has 2 types of paid subscription for individuals. Which DataCamp plan will I be receiving?

Participants of AI for Industry will receive the ‘Premium’ plan which provides access to all courses and career tracks on DataCamp. For more information on the features available on DataCamp, you may visit here

Cost and Funding

What are the fees to join this training programme?

For a Singapore Citizen/PR, it is SGD224.70 (GST incl.). For the ‘Others’ category, it is SGD845.30 (GST incl.).

Are there subsidies available like SkillsFuture Credits?

AI4I is not eligible for SkillsFuture Credits.

However, AISG funding is already incorporated into the AI4I programme fee for Singapore Citizen / Singapore Permanent Resident. Please refer to the pricing table.

Will AI Singapore issue an invoice to the sponsoring company for their sponsored employee(s)?

Yes, this is applicable for bulk registration of more than 25 registrants ONLY.          Please have your company’s coordinator contact us at

For companies with a group size of less than 25 registrants, please proceed to have the participant enrol via the online registration. He/she can pay via:

  • Corporate credit/debit card; or
  • Personal credit/debit card and arrange for reimbursement with the sponsoring company

The above options are subject to the company’s discretion.


If I have an existing DataCamp subscription, do I have to cancel my subscription?

You can activate your new DataCamp subscription after your current subscription has expired.

I am a participant of AI4I® Batch 4. I noticed that DataCamp has updated the 'Data Scientist with Python' career track. Should I update to the new track?

No. In order to qualify for CITREP+ claim, you are required to complete the previous version of the career track. For the full list of modules to be completed, you may visit here

If you have already updated to the new version of the career track, you can complete the list of modules (see above) individually, without the use of the career track. You will receive the ‘Foundations in AI’ certificate issued by AI Singapore. Please note that you will not receive the certificate issued by DataCamp.

What is the difference between the old 'Data Scientist with Python' career track and the current version that was updated in March 2020?

Click here to view the difference in the content between the 2 DataCamp career tracks. 

I have updated to the new 'Data Scientist with Python' career track on DataCamp. Can I switch back to the old track?

The change is not reversible after 24 hours from the time of change. 

Please indicate your interest here

Mailing List Sign Up

Supported By

Content Partners