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AI, ML and Data Science Programme

Transforming business decisions through data analytics, Python, machine learning and generative AI

  • Self-paced learning with top NUS faculty
  • 5 live sessions with NUS faculty and 2 live sessions with industry experts
  • Capstone project
  • 1-day networking event
Work Experience

The programme learning will pause for holidays during Christmas (24 Dec 2025 – 1 Jan 2026) and Chinese New Year (16 Feb – 22 Feb 2026).

Future-Proof Your Career: Invest in Your Success

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Programme Overview

In today’s data-driven world, organisations rely on vast amounts of information to guide every decision, process, and strategy. From data analytics to advanced machine learning (ML) and generative AI (GenAI), the AI, ML and Data Science Programme by NUS School of Computing equips professionals with the essential skills to transform raw data into actionable business insights.

The programme places a strong emphasis on real-world relevance, including live masterclasses, hands-on exercises, capstone projects and emerging tools to ensure you are equipped with market-ready skills. By the end of the journey, you will be able to design, implement and optimise AI-powered systems to enhance decision-making, automate processes and drive competitive advantage.

  This comprehensive programme combines three key pillars:  

  • Data Analytics – Data to Insights: Learn to process, clean, visualise and analyse data using tools such as Power BI, Power Pivot and Orange, building a strong foundation in descriptive statistics, database querying and data mining techniques.

  • Programming with Python: Gain hands-on expertise with NumPy, Pandas, Scikit-Learn, Keras, TensorFlow and more to manipulate, model and deploy data-driven solutions.

  • Machine Learning, AI & GenAI Applications: Explore supervised and unsupervised learning, neural networks, reinforcement learning, deep learning, recommendation systems, Machine Learning Operations and Generative AI with Hugging Face and OpenAI Playground to create scalable and intelligent solutions.

Programme Highlights

PHighlights No prior coding experience

No prior coding experience

Programme designed for professionals without prior coding experience

PHighlights Premium school experience

Premium school experience

Certificate from Asia’s Leading University

PHighlights Flexible mode of delivery

Flexible mode of delivery

300+ Pre-recorded video lectures* from NUS faculty for self-paced learning

PHighlights Live and interactive sessions

Live and interactive sessions

5 live sessions with faculty and 2 with industry experts

PHighlights industry-relevant curriculum

Comprehensive curriculum

30+ modules covering Data Analytics, Python, Machine Learning, Deep Learning and more

PHighlights Networking immersion

Networking immersion

1-day networking opportunity to meet with fellow global leaders and interact with programme faculty/director

PHighlights Capstone project

Capstone project

Demonstrate your newly gained AI, ML and Data Science skills through a capstone project that applies learning from modules to real-world challenges

PHighlights Distinguished faculty

Distinguished faculty

Learn via video lectures from renowned faculty at NUS School of Computing

PHighlights Topics on AI and Gen AI

Topics on AI and Gen AI

AI and Gen AI topics covered through modules and faculty live sessions

PHighlights Practical knowledge

Practical knowledge

Gain hands on learning through tools and weekly assignments

Note: The programme highlights mentioned above are subject to change based on faculty availability and the desired outcomes of the programme.

*This programme is primarily self-paced online with some live sessions conducted by programme faculty. The availability of post-session video recordings is at the discretion of the faculty members, and Emeritus or the institute cannot guarantee their availability. We have a curated panel of distinguished industry practitioners who will conduct weekly live doubt-clearing sessions.

**Assignments will be graded by industry practitioners who are available to support participants in their learning journey, and/or by the Emeritus grading team. The final number of quizzes, assignments, and discussions will be confirmed closer to the start of the programme.\

***Participants are responsible for arranging their own travel and accommodation for the on-campus networking sessions.

***All benefits are subject to change at the discretion of NUS School of Computing.

Programme Goals

  • Data-Driven Decision-Making with Statistical and Analytical Techniques - Gain foundational knowledge in statistics and analytics to extract meaningful insights from raw data and support strategic business decisions.

  • Database Management and Modelling with DB Browser for SQLite, Power BI Desktop and Excel - Build, clean and manipulate data using industry-standard tools. Create relational databases, construct data models and prepare datasets for visualisation and analysis.

  • Python for Data Science: End-to-End Data Workflows - Use Python with core libraries like NumPy, Pandas and Scikit-Learn to automate data collection, cleaning, transformation, analysis and modeling for scalable solutions.

  • Applied Machine Learning: Algorithms and Use Cases - Implement supervised and unsupervised machine learning algorithms including classification, regression, clustering and association rule mining. Understand model evaluation and optimisation for real-world problems.

  • Deep Learning with TensorFlow and Keras - Design, train and optimise deep learning architectures such as neural networks and CNNs. Use TensorFlow and Keras to solve complex tasks like image recognition, sentiment analysis and more.

  • Operationalising AI: Machine Learning Operations and Model Lifecycle Management - Deploy and manage AI models at scale using Machine Learning Operations principles. Leverage tools like MLflow and version control to track experiments, manage reproducibility and streamline model updates and deployment.

  • Recommendation Engines and Reinforcement Learning - Build and evaluate recommendation systems using collaborative filtering, content-based filtering and hybrid approaches. Explore reinforcement learning to develop models that learn from dynamic environments and feedback loops.

  • Generative AI and Natural Language Processing (NLP) - Explore the power of generative AI and NLP with tools such as OpenAI Playground, Hugging Face and Transformer-based models. Apply these technologies to a wide range of language and AI applications.

  • Responsible AI - Explainability, Fairness and Governance - Ensure transparency, fairness and accountability in AI models. Apply responsible AI principles to enhance explainability, mitigate bias and uphold ethical standards in AI deployment.

Who is this Programme For?

The programme is designed for professionals without prior coding experience, from both tech and non-tech domains, who want to:

  • Pivot into a Machine Learning career

  • Acquire Machine Learning concepts and techniques to transition into Machine Learning roles

  • Gain the expertise to lead and solve real-world business problems with data and modelling at the core

The programme is particularly applicable to major industries such as IT products and services, banking and financial services, consulting, education, healthcare and retail.

High-impact Curriculum

Online Live Session by Faculty

AI in Data Analytics 416x310

AI in Data Analytics

Programming with Python 416x310

Programming with Python: Applications, Summary and Doubt Solving

Agentic AI UseCases 416x310

Agentic AI UseCases

Future of AI 416x310

Future of AI: Quantum & Responsible AI

Deep learning 416x310

Deep Learning and Recommended System Applications and Tools

Note - Topics are subject to change depending of faculty expertise and availability.

Case Studies

Marketing Analysis for a Sunglasses Retailer

Marketing Analysis for a Sunglasses Retailer

In this case study, the faculty demonstrates how to use data to provide insights on the potential customers of a sunglasses retailer.

Airlines Delay Data Analyis

In this demonstration, the faculty shows how to transform data on flight delays into a user-friendly interface.

Performance Analysis of Top 10 Tennis Players

In this case study, the faculty demonstrates the application of logical flow in programming using various statements in Python to the study the performance of athletes.

Movie Reviews Analysis

In this case study, the faculty demonstrates several operations on string data to organise and display audience feedback.

Hierarchical Clustering for a Data Set on Celebrities

Hierarchical Clustering for a Data Set on Celebrities

Through a lecture video, the faculty will show how to develop a system to cluster a dataset containing information on celebrities.

Boston Housing Dataset Analysis

In this demonstration, the faculty demonstrates the application of neural network concepts to identify the median value of houses in Boston based on input features.

In-demand Tools

Note:

  • All product and company names mentioned in this material are trademarks or registered trademarks of their respective holders. Their use does not imply any affiliation with or endorsement by them.

  • The tools will be taught by teaching faculty, industry practitioners, or linked to relevant knowledge bases for your reference and self-guided learning.

  • Apart from the tools mentioned above, learners will get to experience other industry related tools.

Programme Faculty

Faculty Member DANNY POO
DANNY POO

Associate Professor

Dr Danny Poo is a tenured Associate Professor at School of Computing (SOC), National University of Singapore (NUS).

Dr. Poo is a member of the School’s Curriculum Committee t...

AMIRHASSAN MONAJEMI

Senior Lecturer (Educator Track)

Dr Amirhassan Monajemi is a Senior Lecturer with the School of Computing, National University of Singapore (NUS).

Before joining the NUS, he was with the Faculty of Computer ...

AI XIN

Lecturer (Educator Track)

Dr. Ai Xin is currently a Lecturer with the School of Computing at the National University of Singapore (NUS).

She has many years of experience teaching Artificial Intelligen...

Past Participant Profiles

Work Experience

NUSSOC-AML Past Participants 460x316 01

Industries

NUSSOC-AMLDS Past Participants 460x316 02

Testimonials

The live sessions were extremely helpful in reinforcing our understanding of the concepts and getting our doubts clarified.
Shyamsunder Haldar
Lead Operations Analyst,
Autodesk
The hands-on approach and step-by-step guidance made it easy to understand, even without any prior knowledge or experience.
Ivan Ten
Credit Risk Lead
DCAP Commercial Sdn Bhd
The live sessions provided an excellent opportunity to ask questions and receive immediate, clear solutions. It greatly enhanced my understanding and learning experience.
Kevin Goh Yu Han
AEM Singapore Pte Ltd
Software Engineer
The programme allowed me to learn new concepts at my own pace, making the experience both flexible and effective.
Martin Huang
MOE
Assistant Year Head
The highlight of this programme is the Data Analytics module featuring Power BI and Neural Networks. It was both exciting and incredibly insightful to learn.
Jeyaganesh N
Kyndryl Pte Ltd
IT Operations Lead

The NUS School of Computing Advantage

#1

in Asia as per QS World University Rankings 2025: Top global universities

#8

in the world as per QS World University Rankings 2025: Top global universities

#2

in Asia as per QS World University Rankings by Subject 2025: Data Science and Artificial Intelligence
Certificate

Certificate

Upon successful completion of the programme, participants will be awarded a verified digital certificate by NUS School of Computing.

Emeritus Career Services

Stepping into a business leadership career requires a variety of job-ready skills. Below given services are provided by Emeritus, our learning collaborator for this program. The primary goal is to give you the skills needed to succeed in your career; however, job placement is not guaranteed.

Emeritus provides the following career preparation services:

  • Resume building videos

  • Interview preparation videos

  • Linkedln profile building videos

  • Glossary of resume templates

Please note:

NUS or Emeritus do not promise or guarantee a job or progression in your current job. Career Services is only offered as a service that empowers you to manage your career proactively. The Career Services mentioned here are offered by Emeritus. NUS is not involved in any way and makes no commitments regarding the Career Services mentioned here

The Learning Experience

What is it like to learn with the learning collaborator, Emeritus?

More than 300,000 professionals globally, across 200 countries, have chosen to advance their skills with Emeritus and its educational learning partners. In fact, 90 percent of the respondents of a recent survey across all our programs said that their learning outcomes were met or exceeded. All the contents of the course would be made available to students at the commencement of the course. However, to ensure the program delivers the desired learning outcomes, the students may appoint Emeritus to manage the delivery of the program in a cohort-based manner during the course period the cost of which is already included in the overall Course fee of the course.

A dedicated program support team is available 7 days a week to answer questions about the learning platform, technical issues, or anything else that may affect your learning experience.

Early registrations are encouraged. Seats fill up quickly!

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