Transforming business decisions through data analytics, Python, machine learning and generative AI
The programme learning will pause for holidays during Christmas (24 Dec 2025 – 1 Jan 2026) and Chinese New Year (16 Feb – 22 Feb 2026).
Emeritus and NUS School of Computing unite to offer an exclusive opportunity. Enrol before Invalid liquid dataand get Invalid liquid data enrolment benefit. Limited seats available. Reserve your spot today!
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.
No prior coding experience
Programme designed for professionals without prior coding experience
Premium school experience
Certificate from Asia’s Leading University
Flexible mode of delivery
300+ Pre-recorded video lectures* from NUS faculty for self-paced learning
Live and interactive sessions
5 live sessions with faculty and 2 with industry experts
Comprehensive curriculum
30+ modules covering Data Analytics, Python, Machine Learning, Deep Learning and more
Networking immersion
1-day networking opportunity to meet with fellow global leaders and interact with programme faculty/director
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
Distinguished faculty
Learn via video lectures from renowned faculty at NUS School of Computing
Topics on AI and Gen AI
AI and Gen AI topics covered through modules and faculty live sessions
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.
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.
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.
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...
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 ...
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...
Upon successful completion of the programme, participants will be awarded a verified digital certificate by NUS School of Computing.
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
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.
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