Overview
At the end of the course, learners will be able to:
Analyse and manipulate data effectively using Python and SQL
Create and manage databases for data storage and retrieval
Conduct exploratory data analysis to extract meaningful insights
Visualise data to communicate findings and trends
Apply data science techniques to solve practical problems
Deploy an ML model version via API or web app for inference or serving
Course Description & Learning Outcomes
Foundations of Data Science:
Python and SQL Learners will understand database basics, SQL, and Python libraries for data science, including data modeling, advanced SQL, data transformation with Numpy and Pandas, exploratory data analysis, and data visualisation.
Scalable Data Solutions: Big Data Engineering Essentials
Learners will build and manage large-scale data pipelines and systems, covering data extraction, transformation, loading, data warehousing, architecture, and distributed data processing.
Building Intelligent Systems: Machine Learning and Generative AI
This module focuses on developing and deploying machine learning models, covering paradigms, training, testing, deployment, and generative AI for unstructured data like image and text classification.
Certified AI Practitioner:
Learners will explore AI, ML, and generative AI concepts and applications, including foundation model design, model training, fine-tuning, and prompt engineering, with real-world use cases across industries.
Transforming Business with GPT: Hands-On Generative AI Applications
This module teaches creating applications using GPT API technology to improve business outcomes. Learners will understand GPT API at a team or organizational level, including working with, fine-tuning, deploying, and integrating GPT models in the cloud.
Full Stack Programming and Deployment of AI Solutions:
Learners will develop and deploy full-stack web applications, covering front-end and back-end development, database management, API programming, cloud deployment, project management, and Web3 technologies, gaining hands-on experience with modern technologies.
Recommended Prerequisites
A background in IT is not necessary but preferable. This course is designed to cater to the intricacies of data science, data engineering and AI. Hence, individuals with a background in these disciplines bring valuable prior knowledge that will enhance their learning experience and understanding of the curriculum.
Pre-course instructions
Applicants will be required to undergo a shortlisting process where they must share their résumé and complete a pre-course assessment. Our instructors and career consultants will review applicants to assess their suitability before deciding whether to shortlist them for the course.
Schedule
End Date: 01 Aug 2025, Friday
Weekdays: 10:00AM to 5:00PM (Full-Time) Venue: Virtual (Online), NTU e-Learning Platform & NTU@one-north Registration Closing Date: 11 Apr 2025
Location: 11 Slim Barracks Rise, Singapore, 138664 and OnlinePricing
Course fees: Standard Course Fee: S$32,264
Skills Covered
PROFICIENCY LEVEL GUIDE
Beginner: Introduce the subject matter without the need to have any prerequisites.
Proficient: Requires learners to have prior knowledge of the subject.
Expert: Involves advanced and more complex understanding of the subject.
- Data Modeling (Proficiency level: Beginner)
- Structured Query Language (SQL) (Proficiency level: Beginner)
- Python (Proficiency level: Beginner)
- Data Engineering (Proficiency level: Beginner)
- Data Analytics (Proficiency level: Beginner)
- Numpy (Proficiency level: Beginner)
Speakers
Trainer's Profile:
Dr Teoh Teik Toe, Trainer, Academy for Professional and Continuing Education (NTU PACE)
Dr Teoh has published 4 books and more than 100 publications. Additionally, he has more than three decades of research experience in the areas of Big Data, Deep Learning, Cybersecurity, AI, Machine Learning and Software Development. He also possesses more than 25 years of teaching experience in AI, Data Science and Analytics, Statistics, Business, Finance, Accounting and Law. Dr Teoh obtained his PhD in Computer Engineering from NTU, Doctor of Business Administration and Master of Business Administration from University of Newcastle, Master of Law from the National University of Singapore, and Bachelor of Laws and Master of Laws from University of London. He completed his post doctorate at Singapore University of Technology and Design. Dr Teoh is a chartered holder of CFA, ACCA, CIMA, CA Singapore, Chartered Tax Practitioner, Associate Chartered Valuer and Appraiser and CPA Australia. Additionally, he is a member of Mensa International.
Trainer's Profile:
Zane Lim, Trainer, Academy for Professional and Continuing Education (NTU PACE)
Zane is a seasoned data scientist and startup co-founder. Boasting a dynamic career with industry leaders like Gojek and Alibaba, along with commendable academic and teaching experiences at the National University of Singapore and General Assembly, Zane brings valuable insights to the table. His innovative contributions to NLP and AI platforms ensure a practical, industry-relevant learning experience.
Trainer's Profile:
Patrick Fong, Trainer, Academy for Professional and Continuing Education (NTU PACE)
He delivers namely cloud computing courses from Amazon Web Services (AWS) and is an expert in VMware products. He has attained many certifications such as AWS Certified Solutions Architect, DevOps Engineering and Machine Learning. Besides AWS products, Patrick is also certified in Servicenow and VMware products. He was a mentor instructor to qualify new instructors onboarding for VMware and Dell EMC’s training team. With his vast experience from IT infrastructure products such as servers, enterprise storages and virtualisation coupled with years of consulting and project management experience, his trainings are unique and beneficial to students due to his real-life experiences in the field. In his 25 years of teaching and consultancy roles, he has delivered a myriad of courses and projects in Asia, Europe and South America. Besides being a qualified instructor for AWS, VMware and ServiceNow products, he holds an MBA from Heriot Watt University, Edinburgh Business School UK.
Trainer's Profile:
Mohamed Jawad, Trainer, Academy for Professional and Continuing Education (NTU PACE)
Jawad is an accomplished technology leader with more than a decade of experience spanning artificial intelligence, machine learning, and data science. Jawad has held several leadership positions at Gojek, where he served as Head of Data for Gojek Mobility, leading the company's marketplace platform across engineering, product and data functions. He also drove significant technological innovations, including the development of pooled dispatch systems for food delivery and the successful transition from Google Maps to internal tools, substantially improving the unit economics of fulfillment services. As Head of Data for Gojek Marketplace, he led a team of 30 data scientists and analysts to implement sophisticated machine learning solutions for pricing optimisation, demand modeling, and supply positioning.
Trainer's Profile:
Akanksha Tiwari, Trainer, Academy for Professional and Continuing Education (NTU PACE)
Akanksha is a data scientist and entrepreneur with a robust background in data-driven insights. Currently, she serves as the Co-Founder of Novela, a pioneering simulation platform for professional learning. Under her leadership, Novela has successfully partnered with prestigious institutions such as Columbia Business School, Imperial College London, and University College Dublin. Prior to her role at Novela, Akanksha held significant positions at renowned companies such as Twitter, Spotify, Rakuten and Adobe in various roles in data science, machine learning, predictive modelling and software engineering. Akanksha has also worked as a data science researcher at the National University of Singapore (NUS) and published a paper on machine learning, data mining and natural language processing on social media data.
Trainer's Profile:
Germayne Ng, Trainer, Academy for Professional and Continuing Education (NTU PACE)
Germayne is a seasoned data scientist with extensive experience in data science, machine learning systems and mapping technologies. Germayne has held several leadership positions at GoTo Group, where he currently serves as Head of Data Science and is responsible for building the company’s mapping data platform. Germayne drove significant technological innovations, including the development of sophisticated location search systems, routing optimisation, real-time Estimated Time of Arrival prediction systems and sustainable maps platform. Germayne has filed a patent for machine learning and publishes articles on data science on Medium and participates in Kaggle data science competitions in his free time.
