Course Information

  • Sessions 2 days
  • Duration 15 hrs
  • Level Intermediate
  • Assessment NA

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

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Certification

  • Certificate of Completion from Tertiary Infotech - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Infotech.

Additional Information

Duration

2 months (Full Time)

Assessment

3 hours online assessment after each module

Class (No of teacher : student): 1:20

Intake

  • 3 Nov 2025 to 29 Sep 2026
  • 4 May 2026 to 26 June 2026
  • 2 Jan 2026 to 2 Mar 2026
  • 2 Mar 2026 to 27 Apr 2026

Enrolment Requirement

  • Age: 21 years old and above
  • Language Proficiency: At least C6 for GCE "O" Level English
  • Academic: At least C6 for GCE "O" Level in any 3 subjects

Graduation Requirement

  • Attendance: 75%
  • Assessment: Passed

Algorithmic Trading Fundamentals with Python

Course Code: C728

What's This Course About

Embark on a journey into the dynamic world of Algorithmic Trading with our comprehensive course, Algorithmic Trading Fundamentals with Python, exclusively at Tertiary Courses. Designed for financial enthusiasts and professionals alike, this course delves deep into the realm of automated trading, leveraging the powerful capabilities of Python to deliver hands-on knowledge on crafting effective trading strategies. From understanding the intricacies of backtesting to the nuanced use of Bollinger Bands and RSI, participants are set to gain a competitive edge in the evolving landscape of modern trading.

Our seasoned instructors will guide attendees through the processes of optimizing the Cross Over Moving Average Strategy, implementing advanced strategies using tools like Mean Reversion, and familiarizing with renowned Algorithm Trading Platforms. One of the standout modules is the creation of an automated trading bot, ensuring participants can practically apply their newfound knowledge. By the culmination of the course, you'll be well-equipped to navigate the financial markets using Python-powered algorithmic strategies, ensuring optimal returns and minimal risks.

WSQ Funding

Full Fee $600.00 Before GST
GST $54.00 9% of fee
Baseline Nett $354.00 SG/PR age 21+ · 50% funded
MCES / SME Nett $234.00 SG age 40+ · 70% funded
Funding and Grant Applications

No funding is available for this course

For IBF funding, please checkout the details at Machine Learning 101 for Financial Trading (IBF Funded)

Course Fee

$600.00 (GST-exclusive)
$654.00 (GST-inclusive)

Course Date

Course Time

* Required Fields

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Cancellation & Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
  • Note the venue of the training is subject to changes due to availability of the classroom.

Course Details

Course Details

What You'll Learn

Topic 1 Overview of Algorithmic Trading

Introduction to Algorithmic Trading

Overview of Technical Indicators

Backtesting Algorithmic Trading Strategies

Evaluate Algorithmic Trading Strategies

Topic 2 Algorithmic Trading Strategies

Simple Moving Average Long Only Strategy

Moving Average Crossover Momentum Strategy

Bollinger Bands Mean Reversion Strategy

Object Oriented Approach to Backtesting

Optimisation of Moving Average Crossover Strategy

Topic 3. Setup a Automated Trading Bot

Trading Platforms

Sign up a Paper Trading Account

Create a Automated Trading Bot with API

Course Info

Prerequisite

This is an intermediate level course. The following prerequisite is assumed

Software Requirement

Please download and install the following software prior to the class

Job Roles

Job Roles

  • Data Scientists
  • Financial Analyst
  • Algorithmic Traders

Trainers

Trainers

Ken Yuen: Ken Yuen is a ACTA certified trainer. He has more than 10 years of experience working as an instructor, Application Development Engineer, Technical Consultant and Project Manager. He is an MOE-Registered Instructor teaching STEM programs for past 3 years such as Arduino, Micro:bits and robotics to schools and libraries based on the smart nation initiative roadmap. He completed his Diploma in Electronic Engineering at Singapore Polytechnic and graduated with Bachelor of Electrical and Electronics Engineering from Nanyang Technological University and certified PMP (Project Management Professional). Terence Ee: Terence Ee is a ACTA certified trainr that has delivered IT training in Singapore and Myanmar. He has also facilitated faith formation courses for Christians in Singapore and Myanmar. As a trainer, his mission is to co-create insightful and actionable learning experiences with his learners.His current areas of focus include project management, information security management, quality management and office productivity applications. Terence has more than 25 years of corporate IT experience. He has held senior management roles in the public and private sectors. He holds a Master of Science in Technology Management, a Bachelor of Science in Computer and Information Sciences, a Diploma in Family Education, and the Advanced Certificate in Training and Assessment (ACTA). Part of his spare time goes towards tutoring his children in their studies (while learning a thing or two along the way). He is also imparting to them the essential skills for thriving in a digital world. Dr Alvin Ang: Dr Alvin Ang is a ACTA certified trainer. Alvin Ang did his Ph.D., Masters and Bachelors from NTU, Singapore. Previously he was a Principal Consultant (Data Science) as well as an Assistant Professor. He was also 8 years SUSS adjunct lecturer. His focus and interest is in the area of real world data science. Though an operational researcher by study, his passion for practical applications outweigh his academic background. He owns a startup externally Shahul H. Maricar: Shahul H. Maricar is a ACTA certified trainer. Shahul H. Maricar has been a content developer and  webmaster, building educational websites and applications with HTML, CSS and JavaScript. He then served as an IT analyst, writing programs for automating custom workflows as well as data extraction and analysis in the healthcare field.   He is currently a freelance educator and is actively involved with development projects in game programming,  computer-aided design and computer graphics. Noel Lou: Noel Lou is a ACTA certified trainer. Experienced Mentor with a demonstrated history of working in the education management industry. Skilled in IOS, Unity3D, Python, Microsoft Excel, Customer Service, and Microsoft Word. Strong professional with a Bachelor’s Degree focused in Marine offshore engineering from Newcastle University. Bernard Peh: Bernard Peh is a Business Development Director and ACTA certified trainer with over 20 years of experience in the financial services industry. He has held key leadership roles and integrated technology, digital marketing, and data science to drive growth in sales, recruitment, and financial planning. As a mentor, Bernard has developed many successful financial professionals who have achieved top industry accolades like TOT, COT, and MDRT. With deep expertise in data science, Bernard has advised firms and designed training programs for institutions like NTUC Learning Hub. He continues to apply data science to collective funds, achieving exceptional results such as a 400% increase in assets under management, while empowering financial professionals with technology-driven solutions.

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