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HRD Corp Approved Training Provider Malaysia - Industrial 4.0 Certification Training and Education

Vibe Coding for Algorithmic Trading and Value Investment

Vibe Coding for Algorithmic Trading and Value Investment is a hands-on, project-based course designed to empower participants to build intelligent trading and investment systems using a modern rapid-development workflow known as Vibe Coding. In the first part of the course, learners will explore the foundations of algorithmic trading, including strategy design, backtesting techniques, and key performance metrics such as Sharpe ratio and drawdown analysis. Participants will apply Vibe Coding best practices to efficiently prototype, test, and refine trading algorithms, and ultimately deploy a cloud-based web application for strategy testing. By the end of this module, learners will have built their own cloud-hosted algorithmic trading strategy platform.

The second part of the course focuses on value investing enhanced by automation and intelligent screening. Participants will learn core principles of value investment, perform company screening, detect financial anomalies, and generate structured summary reports using automated workflows. Leveraging Vibe Coding methodologies, learners will design and deploy a cloud-based value investment platform capable of analyzing financial data and supporting informed investment decisions. This course bridges finance and practical AI-driven development, enabling participants to turn investment ideas into fully functional, scalable applications.

Certificate

All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

Funding and Grant

HRD Corp Claimable Course for Employers Registered with HRD Corp

HRDF claimable

Course Code: M586

Fee

MYR1,000.00

Course Date

Course Time

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Disclaimer:

The course dates displayed on our website are tentative and subject to trainer availability. We will confirm the final date after checking with the trainer. You are also welcome to email us your preferred date at sales@tertiarycourses.com.my, and we will do our best to coordinate with the trainer's schedule.

Post-Course Support

We may provide consultation related to the subject matter after the course. Please email your queries to sales@tertiarycourses.com.my and we will forward your queries to the subject matter experts and get back to you asap.

Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.


Course Details

Topic 1: Algorithmic Trading with Vibe Coding

  • Overview of Algorithmic Trading
  • Algorithmic Trading Strategies and Backtesting
  • Performance Index for Algorithmic Trading Strategies
  • Introduction to Vibe Coding
  • Best Practices for Vibe Coding Workflow 
  • Deploy the Web App on the Cloud
  • Create a Cloud-based Algorithm Trading Strategy Testing Platform using Vibe Coding

Topic 2: Value Investment with Vibe Coding

  • Overview of Value Investment
  • Company Screening, Anomaly Detection and Summary Report
  • Create a Cloud-based Value Investment Platform using Vibe Coding

Course Info

Prerequisite:

Nil

Software Requirement:

HRDF Funding

Please refer to this video https://youtu.be/Kzpd-V1F9Xs

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Job Roles

  • Algorithmic Trading Developer
  • Quantitative Analyst
  • Financial Software Engineer
  • Trading Systems Architect
  • Fintech Application Developer
  • Investment Technology Analyst
  • Portfolio Automation Specialist
  • Quantitative Trading Strategist
  • Cloud Platform Engineer (Fintech)
  • Financial Data Analyst
  • Value Investment Analyst
  • Trading Strategy Researcher
  • Full Stack Fintech Developer
  • Risk Analytics Developer
  • Automated Trading Systems Engineer
  • Financial AI Developer
  • Wealth Management Technology Specialist
  • Backtesting Engineer
  • Investment Platform Developer
  • Financial Applications Architect

Trainers

Ghazaleh Babanejad: Ghazaleh Babanejad has received her Ph.D from University Putra Malaysia in Faculty of Computer ‎Science and Information Technology. She is working on recommender systems in the ‎ the field of skyline queries over Dynamic and Incomplete databases for her Ph.D. thesis. She is also working ‎on Data Science field as a trainer and Data Scientist. She worked on Machine Learning and Process ‎ Mining projects. She also has several international certificates in Practical Machine Learning (John ‎ Hopkins University) Mining Massive Datasets (Stanford University), Process Mining (Eindhoven ‎ University), Hadoop (University of San Diego), MongoDB for DBAs (MongoDB Inc) and some other ‎ certificates. She has more than 5 years of experience as a lecturer and database administrator.

Ghoncheh Babanejad: Ghoncheh Babanejad is a PhD student at Faculty of Computer Science & Information Technology at Universiti Putra Malaysia. She is working on recommender systems in the field of Skyline evaluation for a group of mobile users for her Ph.D. thesis. She is also working on PHP, HTML, Adobe Photoshop, Cpanel, Rational Rose, MS Visio, Microsoft Project, MySQL, Dream Weaver, Word Press. She received several certificates in Web Site Preliminary Design(Jihad Daneshgahi), Client-Side Web Programming(Jihad Daneshgahi) and MongoDB for DBAs (MongoDB Inc). She has more than 5 years experience in IT Department And Project Control Department of ACP (Amin Chemical Processes) company

Dr. Nouar AlDahoul: Dr. Nouar AlDahoul is an AI researcher and developer with a PHD degree from IIUM Malaysia. She has +7 years of hands-on experience in machine learning including deep and reinforcement learning. She has been working as a researcher in many research centers such as UM, IIUM, MMU universities. She has published many papers in different journals and conferences. She has conducted more than 30 classes in Tertiary Malaysia Courses. Her research interests are: Deep learning, Reinforcement learning, computer vision, NLP, Data visualization and analysis, and IOT.

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