Dates:
19 May, 22 May, 24 May 2023 | 9am-5.30pm | Online (Professional Certificate in Applied Machine Learning)
17 Jul, 19 Jul, 21 Jul 2023 | 9am-5.30pm | Online (Professional Certificate in Machine Learning Using Python)
Duration: 3 Days
Course Overview
Python Programming teaches the fundamentals of Python. It introduces the highly popular programming language with simplicity but brings forth the power and clear syntax of Python. It teaches the core features of Python and participants will be able to create software applications using Python. Besides, it teaches the Numpy and pandas packages that prepare participants to produce Data Analytics software applications.
This module is part of:
Course Objectives
This course will equip learners with the following competencies:
- Learn and apply data structures in Python
- Learn and apply programming constructs in Python
- Learn to create and use files and produce outputs in Python
- Build a strong foundation in the fundamentals in Python programming
- Learn and use libraries (e.g. Numpy and pandas) in Python API
- Learn and apply Python programming language to create simple software applications
Topics
Topics covered include:
- The Python programming environment: Learn to install and use the Anaconda programming environment to get the best out of Python.
- The Python variables and types: Learn the fundamental elements that define a programming language.
- Data structures including list, tuple, set, dictionary and string: Learn the building blocks that make up a Python program.
- Operators: Learn how to use the components in constructing statements to express yourself in Python.
- Program flow controls: Learn how to provide dynamism in programming.
- Functions: Learn how to express yourself more fluently with statements. • Inputs and outputs: Learn how to create interactivity in Python.
- File handling: Learn how to read from and store data to secondary storage.
- Numpy: Learn how to use the popular package for managing numbers.
- pandas: Learn how to use extended data structures, Series and DataFrame, for efficient management of data variables.
- Create data analytics software applications using the data structures and functions in Python.
Who Should Attend
Data Analyst, Business Analyst
Prerequisites
At least a polytechnic diploma.
Course Conveners
(Click their photos to view their short biographies)
Assoc Prof Danny Poo
Assoc Prof Danny Poo
Assoc 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 5 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 on teaching Artificial Intelligence and Data Science courses, e.g. machine learning, deep learning, data mining and etc.
She graduated from NUS with a PhD degree on Electrical and Computer Engineering. Her research focused on Game Theoretical Modelling, Optimization Methods, Algorithm Design and Wireless Networks.
She worked in BHP Billiton Marketing Asia for eight years and gained a lot of industry experience through different functions, e.g. risk management, supply chain management, sales and marketing planning and etc.
Course Fees
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Code:
TGS-2022011018
TGS-2022011046 (Synchronous e-learning)
Select Short Course / Modular Course -> Apply for Myself -> Browse Academic Modules / Short Courses-> Module/Course Category -> Short Courses -> Browse Courses-> Advanced Computing for Exe (Faculty/Department / Unit)
Please download the user guide for NUS Online Application Portal after you click ‘Apply for Myself’ if you need assistance.
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or older
