Course Schedule Overview

Detailed timing and session planning for our comprehensive algorithmic trading programs starting August 2025

Machine Learning Foundations

12 Weeks
Start Date
August 15, 2025
Weekly Schedule
Tuesdays & Thursdays
Session Time
7:00 PM - 9:30 PM
Format
Live Online Sessions

This foundational course covers statistical analysis, data preprocessing, and basic machine learning algorithms. Students learn Python programming essentials and work through practical exercises using real market data. Each session includes interactive workshops where participants build their own predictive models.

Advanced Trading Algorithms

16 Weeks
Start Date
September 10, 2025
Weekly Schedule
Saturdays
Session Time
9:00 AM - 1:00 PM
Format
Intensive Workshops

Weekend intensive sessions focus on complex algorithmic strategies and portfolio optimization techniques. Students develop comprehensive trading systems while learning risk management principles. The program includes guest lectures from industry professionals and hands-on projects using professional trading platforms.

Quantitative Risk Management

8 Weeks
Start Date
October 20, 2025
Weekly Schedule
Mondays & Wednesdays
Session Time
6:30 PM - 8:30 PM
Format
Case Study Sessions

Evening sessions concentrate on mathematical modeling for risk assessment and portfolio protection strategies. Participants analyze historical market crashes and develop robust risk monitoring systems. The curriculum emphasizes practical application through real-world case studies and simulation exercises.

Enrollment Information

Our structured learning approach allows students to progress at their own pace while maintaining consistent engagement with instructors and fellow participants.

Flexible Scheduling

Multiple session times accommodate working professionals with evening and weekend options available throughout the program.

Online Learning Platform

Interactive virtual classrooms with recorded sessions, discussion forums, and collaborative project spaces for continuous learning.

Personalized Support

Small class sizes ensure individual attention with one-on-one mentoring sessions and personalized feedback on projects.

Contact for Program Details