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Course Detail

Python Programming for Teachers


Introduction

Python is ranked the top programming language both in the 2019 IEEE Spectrum annual ranking of the top programming languages, and in the PYPL (PopularitY of Programming Language) Index.  Its popularity is driven partly by the vast number of specialised libraries available for it, and by its simple syntax resulting in high code readability.

 

This course aims to equip teachers, particularly mathematics and physics teachers, with Python programming skills.  Participants will be taught how concepts related to computational thinking using Python, and how to incorporate them into the teaching of mathematics.  Examples related to the simultaneous solution of equations, the Newton-Raphson Method, Cramer’s Rule, etc., will be illustrated using a combination of lectures and tutorials.


Details

Date(s): 20 to 21 April 2020
Time: 9:00AM to 5:00PM
Venue: NTU@one-north campus, Executive Centre (Buona Vista)
Registration
Closing Date:
06 April 2020
Course Fee: Standard: S$1284.00   View more
Registration fees inclusive of:
  • Complimentary lunch
  • Course materials
  • Light refreshments
  • Prevailing GST


Objectives

At the end of the course, participants will be able to:

  • write simple Python programs, and run them using (1) Jupyter Notebooks; Python’s Integrated Development and Learning Environment (IDLE); and (3) the command line
  • understand how to import and use the Python standard and external libraries related to mathematics and statistics
  • visualise 2D data using matplotlib
  • relate computational thinking concepts using Python

 


Outline

Day 1

- Why I chose to teach Python instead of R

- Basic data types in Python: int, float, str and bool

- Python input and output: input(), print() and format()

- Working with numbers

- Using comments

- The Python Standard Library: using the import command

- Generating a random number: randint()

- Using specialised libraries: scipy.stats

- Python relational operators: >, <, ==, !=, >=, <=

- Python logical operators: and, or and not

- Conditional statements

- Iterations using for and while loops

- Working with strings


Day 2

- Iterables: lists, dictionaries, tuples and sets

- Python Membership operators: in, not in

- Iterating through iterables

- Using the Python zip() and enumerate() functions

- Reading and writing files

- Importing data from a CSV file

- Exception handing in Python

- Visualising Data Using Matplotlib

- Where to go from here …

- Getting help

- Python resources

Read more

Trainer(s)

Lee, Chu Keong

Dr Lee is currently the programme director of the MSc (Knowledge Management) programme, and Associate Chair (Students) at the Wee Kim Wee School of Communication and Information. A chemical engineer by training, he furthered his studies in the areas of information science and knowledge management and has been teaching for the past 30 years. His current teaching assignments include courses in knowledge management and information analytics. Dr Lee encouraged his students to learn GeoDjango, Django and PostGIS on their own, and together with them, he created http://sgschools.today/. He is a passionate and excitable teacher and lifelong learner, and believes that everyone – young and old – should learn how to code.



Teachers, mentors, supervisors of Python programming projects as well as coaches for competitions such as hackathons
Standard Course Fee S$1284.00
Course fee payable after SSG funding, if eligible under various schemes

Cat-A SSG Funded Courses1

S$385.20

Enhanced Training Support for SMEs (ETSS) 2

S$145.20

Mid-Career Enhanced Subsidy (MCES)3

S$145.20

Workfare Training Support (WTS)4

S$85.20
Standard Course Fee $1284.00
Course fee payable after funding or subsidy, if eligible under various schemes
Course fee payable after Discount^

Group of 3 pax and above

S$1155.60

NTU/NIE Alumni, Staff & Students

S$1027.20

NTUC Member

S$1155.60
- All fees stated are inclusive of 7% GST
- SkillsFuture Credit can be used to offset course fees payable.
With effect from 1 April 2020, eligible Singaporeans can start using their one-off SkillsFuture Credit top-up (up to S$500 credit), claimable for full range of SkillsFuture Credit-eligible courses offered by PaCE@NTU. For more information, please visit https://www.skillsfuture.sg/credit
1 Cat-A SSG Funded Courses - Eligible Singapore Citizens and PRs may enjoy up to 70% of the course fee. For more information, visit http://www.ssg-wsg.gov.sg
Enhanced Training Support for SMEs (ETSS) - SME-sponsored employees (Singapore Citizens and PRs) may enjoy subsidies up to 90% of the course fee.
For more information, visit http://www.ssg.gov.sg/programmes-and-initiatives/funding/enhanced-training-support-for-smes1.html
3 Mid-Career Enhanced Subsidy (MCES) - Singaporeans aged 40 and above may enjoy subsidies up to 90% of the course fee.
For more information, visit http://www.skillsfuture.sg/enhancedsubsidy

4 Workfare Training Support (WTS) - Singaporeans aged 35 and above (13 years and above for persons with disabilities) and earn not more than S$2,000 per month, may enjoy subsidies up to 95% of the course fee. For more information, visit https://www.workfare.gov.sg/Pages/WTSEmployee.aspx
- The NTUC Training Fund (SEPs) is applicable for courses under the SkillsFuture Series courses. For more information, visit https://www.ntuclearninghub.com/ntuc-training-fund-seps/


^ Discount cannot be used in conjunction with other SSG funding scheme or NTU Alumni Course Credit. Participants are eligible for only ONE of the discount schemes.
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