To reduce the environmental impact and contribute to sustainability efforts, ISCA will contribute our part by eliminating the printing of course materials for selected courses with effect from 2023.
Tips: To make your paperless learning experience more enjoyable, you may bring along a digital device such as a Windows based laptops or tablets to read your online materials during the class. QR code will be provided in the class for you to download the materials in PDF.
Join us and be a Difference Maker!
Programme Objective
Designed to provide finance professionals with a straightforward introduction to the basics of Python for analytics and financial modelling purposes, this course will prepare you to pull insights from financial data for decision analysis.
The Python language is an easy programming language to learn for beginners as its code is relatively easy to read, resembling everyday English we speak. Python can be used to power up financial modelling and solve accounting problems more effectively and efficiently.
Through a mix of short presentations and carefully crafted fun exercises, participants begin by learning the basics of Python by completing short hands-on coding exercises related to financial analysis, then they apply these basic skills in building financial models in the analysis of datasets related to companies’ financials. Visualisation of data will also be covered.
Programme Outline
Day 1
- Introduction to Python programming and coding style
- Working with an Integrated Development Environment (Jupyter Notebook for Python) to manage code and share results
- Perform financial calculations with variables and operations with booleans and strings
- Store, access and manipulate financial data in lists, dictionaries and sets
- Wrangle data using functions, control flows and Numpy package
- Introduction to the Pandas dataframes for structuring and manipulating data
- Perform a case study involving financial analysis by calculating and comparing price-earning ratios of S&P companies
Day 2
- Introduction to Numpy Financial package to determine financial metrics such as Present Value, Future Value, NPV and IRR
- Use financial metrics to perform financial analysis on projects with different cash flows
- Perform case studies by applying acquired knowledge and skills of Numpy, Series, Pandas and Data Frames and the financial metrics
- Build Sensitive Forecast Models to aid in financial forecasting
- Use iteration, loops and conditionals statements with Python functions to perform gap analysis of different forecasts in case studies
- Perform simple data exploration on time-series financial data
Training Methodology
This hands-on and highly participative course is specially designed for classroom learning. Participants will be given opportunities to write simple codes using Python before moving on to create progressively more complex codes and visualisation from financial data sets.
Closing Date for Registration
1 week before programme or until full enrolment
Intended For
Any finance professionals who wish to gain fundamental knowledge on Python and financial modelling. Other participants who have attended DGT053 : Get Started with Fundamentals of Python for Finance and wish to explore the application of Python in financial modelling will also benefit from the course.
Competency Mapping
Category 5 = 14.00 Hours
Schedule & Fees
Date & Time
26 Oct 2023 (9:00 AM - 5:00 PM)
27 Oct 2023 (9:00 AM - 5:00 PM)
Fee (inclusive of GST)
For Members:
$ 884.52
For Non-Members:
$ 1,053.00
Programme Facilitator(s)
Ong Kia Meng
Jeffrey Ong
Venue
60 Cecil Street
ISCA House
Singapore 049709
Testimonial
Funding
No funding Available!
Programme Facilitator(s)
Ong Kia Meng
Kia Meng is a training solutionist, and technology evangelist in the data analytics space, possessing more than ten years' experience from financial business partnering. His ability to harness technology enables him to deliver impactful data-driven outcomes. Kia Meng founded Databuilder PL to focus on helping clients adopt data-driven learning design and offer training on data science and business analytics topics. He has created digital instructional media and conducted various business skills training for corporate clients, with participants spanning various nationalities.
A Chartered Accountant of Singapore, Kia Meng graduated with an Accountancy degree from the Nanyang Technological University. He holds an Advanced Certificate in Training & Assessment (ACTA) and a Diploma in Design and Development of Learning for Performance (DDDLP) from the Institute for Adult Learning (IAL) Singapore, and he is a certified Data Science Practitioner-Instructor by IBM. As a qualified employment intermediary in Singapore, Kia Meng is also very passionate about helping individuals match their talents to career objectives.
Jeffrey Ong
Jeffrey Ong is a certified curriculum and assessment designer, as well as a trainer for adult learning. He specialises in the design of data science content in both online and classroom training settings. After teaching in schools, Jeffrey transitioned into the education publication industry where he has crafted and conducted product training for clients and staff. His burgeoning interest in Data Science coincided with the opportunity to join Databuilder PL. Jeffrey’s passion lies in Big Data technology and the visualization of data.
Jeffrey holds a Diploma in Adult and Continuing Education (DACE) and Advanced Certificate in Training and Assessment (ACTA) from the Institute for Adult Learning (IAL) Singapore. He is also a certified Data Science Practitioner-Instructor by IBM. Jeffrey graduated with an Honours degree in Real Estate from the National University of Singapore, BSc in Mathematics and Economics (Honours) from University of London (Singapore) and a Post Graduate Diploma in Education from the National Institute of Education (Singapore).
To reduce the environmental impact and contribute to sustainability efforts, ISCA will contribute our part by eliminating the printing of course materials for selected courses with effect from 2023.
Tips: To make your paperless learning experience more enjoyable, you may bring along a digital device such as a Windows based laptops or tablets to read your online materials during the class. QR code will be provided in the class for you to download the materials in PDF.
Join us and be a Difference Maker!
Programme Objective
Designed to provide finance professionals with a straightforward introduction to the basics of Python for analytics and financial modelling purposes, this course will prepare you to pull insights from financial data for decision analysis.
The Python language is an easy programming language to learn for beginners as its code is relatively easy to read, resembling everyday English we speak. Python can be used to power up financial modelling and solve accounting problems more effectively and efficiently.
Through a mix of short presentations and carefully crafted fun exercises, participants begin by learning the basics of Python by completing short hands-on coding exercises related to financial analysis, then they apply these basic skills in building financial models in the analysis of datasets related to companies’ financials. Visualisation of data will also be covered.
Programme Outline
Day 1
- Introduction to Python programming and coding style
- Working with an Integrated Development Environment (Jupyter Notebook for Python) to manage code and share results
- Perform financial calculations with variables and operations with booleans and strings
- Store, access and manipulate financial data in lists, dictionaries and sets
- Wrangle data using functions, control flows and Numpy package
- Introduction to the Pandas dataframes for structuring and manipulating data
- Perform a case study involving financial analysis by calculating and comparing price-earning ratios of S&P companies
Day 2
- Introduction to Numpy Financial package to determine financial metrics such as Present Value, Future Value, NPV and IRR
- Use financial metrics to perform financial analysis on projects with different cash flows
- Perform case studies by applying acquired knowledge and skills of Numpy, Series, Pandas and Data Frames and the financial metrics
- Build Sensitive Forecast Models to aid in financial forecasting
- Use iteration, loops and conditionals statements with Python functions to perform gap analysis of different forecasts in case studies
- Perform simple data exploration on time-series financial data
Training Methodology
This hands-on and highly participative course is specially designed for classroom learning. Participants will be given opportunities to write simple codes using Python before moving on to create progressively more complex codes and visualisation from financial data sets.
Closing Date for Registration
1 week before programme or until full enrolment
Intended For
Any finance professionals who wish to gain fundamental knowledge on Python and financial modelling. Other participants who have attended DGT053 : Get Started with Fundamentals of Python for Finance and wish to explore the application of Python in financial modelling will also benefit from the course.
Competency Mapping
Category 5 = 14.00 Hours
Programme Facilitator(s)
Ong Kia Meng
Kia Meng is a training solutionist, and technology evangelist in the data analytics space, possessing more than ten years' experience from financial business partnering. His ability to harness technology enables him to deliver impactful data-driven outcomes. Kia Meng founded Databuilder PL to focus on helping clients adopt data-driven learning design and offer training on data science and business analytics topics. He has created digital instructional media and conducted various business skills training for corporate clients, with participants spanning various nationalities.
A Chartered Accountant of Singapore, Kia Meng graduated with an Accountancy degree from the Nanyang Technological University. He holds an Advanced Certificate in Training & Assessment (ACTA) and a Diploma in Design and Development of Learning for Performance (DDDLP) from the Institute for Adult Learning (IAL) Singapore, and he is a certified Data Science Practitioner-Instructor by IBM. As a qualified employment intermediary in Singapore, Kia Meng is also very passionate about helping individuals match their talents to career objectives.
Jeffrey Ong
Jeffrey Ong is a certified curriculum and assessment designer, as well as a trainer for adult learning. He specialises in the design of data science content in both online and classroom training settings. After teaching in schools, Jeffrey transitioned into the education publication industry where he has crafted and conducted product training for clients and staff. His burgeoning interest in Data Science coincided with the opportunity to join Databuilder PL. Jeffrey’s passion lies in Big Data technology and the visualization of data.
Jeffrey holds a Diploma in Adult and Continuing Education (DACE) and Advanced Certificate in Training and Assessment (ACTA) from the Institute for Adult Learning (IAL) Singapore. He is also a certified Data Science Practitioner-Instructor by IBM. Jeffrey graduated with an Honours degree in Real Estate from the National University of Singapore, BSc in Mathematics and Economics (Honours) from University of London (Singapore) and a Post Graduate Diploma in Education from the National Institute of Education (Singapore).