August 2026 Fintech Fundamental: Deep Learning with Python for Financial Time Series Prediction

Live Sessions:

• Week 1 – Python and Market Data Foundations: environment setup, retrieving price history with yfinance, and handling time series in pandas 

• Week 2 – Preparing Financial Data for Learning: returns and stationarity, lag features and scaling, and splitting data without look-ahead bias 

• Week 3 – Building a Neural Forecasting Model: tensors and autograd in PyTorch, an LSTM for sequential price prediction, and reading the training loss curve 

• Week 4 – Evaluation and Final Mini Project: RMSE and directional accuracy, walk-forward validation, and why high accuracy does not guarantee profit

Who Suits the Programme

• Pre-university students (IGCSE A Level, STPM, Matriculation, UEC) 

• Form 4/ Form 5 students

The 1-to-1 programme is targeted to learners without prior programming experience.

Benefits:

Upon successful completion of the courses, you will be awarded a digital certificate of completion. This certificate comes with a unique credential ID for easy verification and can be proudly shared on LinkedIn or other professional platforms to showcase your achievement.

Registration Deadline: One day before the first class begins

Our Instructors Background:

AI engineer and machine learning researcher whose focus is getting models out of notebooks and into working systems. Part of MIT CSAIL's Mantis Rising Scholars Program, a one level reached by roughly hundred contributors program-wide, with over forty merged pull requests and eight accepted technical specifications on knowledge graphs and learning analytics. He has five published and accepted machine learning papers in 2026, covering graph neural networks for cancer staging, medical image classification, and model stability under distribution shift. His engineering work includes a multi-agent orchestration platform built on LangGraph with durable state and human approval gates, a clinical intelligence platform serving over one hundred medical reviewers in Indonesia, and a geospatial health access model covering thirty-eight provinces. He works in Python with PyTorch, FastAPI, and cloud deployment on Google Cloud and Azure, and teaches AI and robotics professionally

Linkedin: www.linkedin.com/in/muhammad-abrar-rayhan/

For more assistance, kindly contact FINTLAS at [email protected] .

For more upcoming events, kindly follow FINTLAS at Linkedin: www.linkedin.com/company/fintlas-applied-fintech-learning/ or Instagram: @fintlas.learning

Download Ticket PDF

1. Upon successful registration, you are expected to receive a Ticket Purchase Confirmation email auto-generated by ticket2u. We kindly advise you download the ticket PDF which would contain the zoom meeting link.

2. If you have lost the Ticket Purchase Confirmation email, we kindly advise you to come to our event page, click the Retrieve Ticket button and key in your email address. You are expected to receive the Ticket Purchase Confirmation email again. 

 Withdrawal & Refund Policy:

1. The programme fee is non-refundable upon the registration. We kindly advise you to check your commitment for the full programme before making payment.

2. Sessions run at fixed dates and times. If students withdraw midway or fail to attend some classes due to the change of timings, partial refunds will be made to the respective students upon the requests. Successful partial refunds will be made after checking the attendance data.

3. No refund would be made if you have lost the tickets (which contains the meeting link). 

Additional Fee

1. An additional fee of RM5 will be applied for each request to issue a digital certificate with a credential ID, unless the error was made by FINTLAS. We kindly advise you to ensure that the correct name is submitted for printing on the digital certificate.