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Professional Certificate

Professional Certificate in Machine Learning Using Python

Programme Structure


Programme NameProgramme ScheduleMode of DeliveryProgramme Code
Python Programming24 Jul, 25 Jul, 26 Jul 2024 (PC in Machine Learning Using Python)Classroom LearningTGS-2022011018
Machine Learning in Python5 Aug, 6 Aug, 7 Aug 2024 | 9am-5.30pmClassroom LearningTGS-2022011025
Duration 6 days

Programme Overview

The Professional Certificate in Machine Learning Using Python offers a thorough curriculum that provides learners with vital skills in Python programming and Machine Learning. The Python Programming section covers essential Python features, data structures, and programming constructs, alongside an exploration of the robust Numpy and pandas libraries for data analysis. In the Machine Learning portion, participants are introduced to key concepts of supervised (e.g., Linear Regression, Logistic Regression) and unsupervised (e.g., K-Means, Hierarchical Clustering) learning techniques. The programme enables participants to develop Machine Learning applications using Python. This certificate is designed to prepare mid-career professionals for positions such as data analysts, business analysts, and data engineers, with a focus on practical implementation in business environments.

Programme Objectives

This PC will equip learners with the following competencies:

  • Learn the various Machine Learning methods in data analysis
  • Have the necessary knowledge and strong foundation to appreciate the proper application of advanced analytics methods in business applications
  • Learn data structures and programming constructs in Python and have a strong foundation in Python programming
  • Learn and apply the Python programming language for creating Machine Learning applications

Job Role Readiness

This programme is designed for mid-career PMETs and to meet the needs of:
Professionals who plan to be a Data Analyst/Business Analyst that is capable of integrating Business, Customer and Technology to produce digital products that the market needs.

It will prepare learners for the following job roles to perform their responsibilities more effectively:

  • Business Analyst
  • Data Analyst
  • Data Engineer

Prerequisites

At least a polytechnic diploma (or equivalent) with 3 years working experience, preferably in the IT industry.

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Instructors


A/Prof Danny Poo

A/Prof Danny Poo

A/Prof Danny Poo brings with him 35 years of Software Engineering and Information Technology and Management experience. A graduate from the University of Manchester Institute of Science and Technology (UMIST), England, Dr Poo is currently an Associate Professor at the Department of Information Systems and Analytics, National University of Singapore. Prior to joining the University, Dr Poo was with the System Operations at DBSBank, Singapore. A Steering Committee member of the Asia-Pacific Software Engineering Conference, Dr Poo is actively involved in Information Management and Healthcare Analytics research. A well-known speaker in seminars, Dr Poo has conducted numerous in-house training and consultancy for organizations, both locally and regionally. Dr Poo is the author of five books on Object-Oriented Software Engineering, Java Programming language and Enterprise JavaBeans.

Dr Poo notable teaching credentials include:

  • Data Strategy
  • Data StoryTelling
  • Data Visualisation
  • Data Analytics
  • Machine Learning
  • Data Management
  • Data Governance
  • Data Architecture
  • Capstone Projects for Business Analytics
  • Software Engineering
  • Server-side Systems Design and Development
  • Information Technology Project Management
  • Health Informatics
  • Healthcare Analytics
  • Health Informatics Leadership.
Industry Credentials
  • Deutsche Bank
  • Gemplus
  • Micron
  • NCR
  • PIL
  • PSA
  • Rhode-Schwarz
  • Standard Chartered Bank
  • ST Electronic
  • Monetary Authority of Singapore
  • Infocomm Development Authority
  • National Library Board
  • Ministry of Manpower
  • Nanyang Technological University
  • Nanyang Polytechnic
  • National University Hospital.

Dr Ai Xin

Dr Ai Xin

Dr Ai Xin is currently a Lecturer with the School of Computing at the National University of Singapore (NUS). She has many years’ experience teaching Artificial Intelligence and Data Science courses such as machine learning, deep learning and data mining. She graduated from NUS with a PhD degree in Electrical and Computer Engineering. Her research focused on Game Theoretical Modelling, Optimization Methods, Algorithm Design and Wireless Networks. She worked at BHP Billiton Marketing Asia for eight years, gaining extensive industry experience in various functions such as risk management, supply chain management, and sales and marketing planning.

Dr Yeo Wee Kiang

Dr Yeo Wee Kiang

Dr Yeo Wee Kiang is a Senior Lecturer at the Department of Information Systems and Analytics in the NUS School of Computing, where he is dedicated to researching the use of technologies like Adaptive Learning and Large Language Models (LLMs) to create personalized and engaging computing education experiences. With a PhD from NUS focused on machine learning and data mining for pharmaceutical drug discovery, Dr Yeo brings practical industry experience as the former Director of Data Science at a food tech startup, where he led a team applying AI and machine learning to enhance nutritional value. His diverse background includes being an Adjunct Lecturer in the Department of Economics at NUS Faculty of Arts and Social Sciences, helming the Big Data Analytics module in the Master of Economics programme from 2019 to 2023, and teaching Python programming and data analytics at Nanyang Business School. Prior to his academic appointments, Dr Yeo was the Lead Instructor for Data Science at a New York-based commercial Continuing Education and Training (CET) provider, teaching aspiring adult learners in Hong Kong, Sydney, and Singapore. He also holds the WSQ Advanced Certificate in Training and Assessment (ACTA) from the Institute for Adult Learning Singapore. As part of the NUS ACE (Advanced Computing for Executives) teaching team, Dr Yeo specializes in technical training and practical computing education focused on data analytics, machine learning, and Python, aiming to equip professionals with in-demand Data Science skills.

Programme Fees


Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
39 years old or younger 40 years old or older
S$1,765.80 S$685.80 S$1,765.80 S$685.80 S$5,886.00
  1. Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
  2. Participants must fulfill at least 75% attendance and pass all assessment components for all short courses within a professional certificate in order to be eligible for SSG funding.
  3. GST shall apply at prevailing rates.

Connect with us

11 Research Link
COM 3, #B1-07
Singapore 119391
Telephone: +65 6516 5523
Email: soc-ace@nus.edu.sg

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