14 Nov, 15 Nov, 16 Nov 2023 | 9am-5.30pm | Classroom Learning
This intake is part of Professional Certificate in Applied Machine Learning
22 Nov, 23 Nov, 24 Nov 2023 | 9am-5.30pm | Online
This intake is part of Professional Certificate in Machine Learning Using Python
16 Oct, 18 Oct, 23 Oct 2023 | 9am to 5.30pm | Online
Duration: 3 Days
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. 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.
This course is part of:
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
Who Should Attend
Data Analyst, Business Analyst
At least a polytechnic diploma.
(Click their photos to view their short biographies)
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.
- Deutsche Bank
- 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.
Assoc Prof Tan Wee Kek
Assoc Prof Tan Wee Kek is currently an Associate Professor in the Department of Information Systems and Analytics at the School of Computing, National University of Singapore. He is also currently serving as an Assistant Dean (Student Life) in the School of Computing, and a Fellow and EXCO member of the NUS Teaching Academy. He graduated with a Doctor of Philosophy in Information Systems in July 2013 and a Bachelor of Computing in Information Systems (1st Class Honours) in July 2007, both from the National University of Singapore. Prior to this, he attended Singapore Polytechnic and graduated with a Diploma in Computer Information Systems with Merit in July 2001.
His current primary research interests focus on consumer-based information technology (e.g., online decision aids, social computing, virtual worlds and consumer cloud services). Most of his research is based on design science, a well-established problem-solving paradigm that has been widely adopted in information systems research. His current secondary research interests focus on information systems education.
His work has been published or is forthcoming in journals such as Journal of the American Society for Information Science and Technology (JASIST), Decision Support Systems (DSS), Communications of the Association for Information Systems (CAIS), and Journal of Information Systems Education (JISE). His work has also been presented or is forthcoming in conferences such as ACM SIGMIS Computer Personnel Research Conference (SIGMIS-CPR), IFIP Working Group 8.2 Working Conference (IFIP WG8.2), European Conference on Information Systems (ECIS), Americas Conference on Information Systems (AMCIS), and International Conference on Human-Computer Interaction (ICHCI).
He has won the faculty level Research Achievement Award in 2013 and was a nominee for the ACM SIGMIS 2009 Magid Igbaria Outstanding Conference Paper of the Year.
His current teaching interests include imparting senior undergraduate students with knowledge and skills to develop enterprise information systems as well as teaching them principles of information security management, and concepts of mobile and ubiquitous commerce.
He has won the University level Annual Teaching Excellence Award for AY 2009 to 2012. In addition to this, he has also won the Faculty Teaching Excellence Award for AY 2008 to 2011 as well as the Faculty Best Teaching Assistant Award for AY 2007/2008. For his sustained commitment to teaching excellence, he has been placed on the Faculty Teaching Excellence Award Honour Roll for AY 2010/2011 and University level Annual Teaching Excellence Award Honour Roll for AY 2012/2013.
He is presently the lead faculty mentor of the NUS BiZiT Society, a student special interest group on business and information technology.
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.
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.
This course is eligible for Union Training Assistance Programme (UTAP). NTUC members can enjoy up to 50% funding (capped at $250 per year) under UTAP. NTUC members aged 40 and above can enjoy higher funding support up to $500 per individual each year, capped at 50% of unfunded course fees, for courses attended between 1 July 2020 to 31 December 2025. Please click here for more information.
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TGS-2022011018 (Classroom Learning)
TGS-2022011046 (Synchronous e-learning)
Course Fee Breakdown
Singapore Citizens39 years old or younger
Singapore Citizen40 years old or older