Empower Your Trading Skills

About SZEL

Welcome to SZEL, where the art and science of quantitative trading meet practical application. Our mission is to empower aspiring and experienced traders to harness the power of data science and machine learning to revolutionize their trading strategies.

Unlike traditional educational platforms, SZEL is built by practitioners for practitioners, equipping learners with actionable, real-world trading strategies that drive measurable success.

Our courses go beyond textbook examples to dive deep into the real-world challenges of quantitative and algorithmic trading, such as developing scalable trading systems, optimizing strategies for dynamic markets, and handling noisy data from financial APIs. From setting up your first trading bot to mastering advanced machine learning techniques for Forex trading, we provide a complete, end-to-end learning experience, such as building a trading system that collects and processes live market data, implements predictive models, and automates trade execution.

Our curriculum emphasizes practicality, efficiency, and the nuances of trading that only seasoned professionals understand.

Whether you’re just starting out or looking to sharpen your expertise, SZEL has something for you.

CASE STUDIES

Alex, a data scientist with a budding interest in algorithmic trading, enrolled in our “Reinforcement Learning for Algorithmic Trading” course. With step-by-step guidance, Alex learned how to preprocess financial data, design an environment for training an RL agent, and feed candlestick chart images as inputs to a convolutional neural network. By following the detailed code examples and leveraging cloud GPUs, Alex trained a reinforcement learning agent to identify profitable trading opportunities.
Within weeks, Alex had a functional trading bot capable of making real-time decisions based on image inputs. By applying what they learned to live Forex markets, Alex achieved a 15% return on their investment within the first three months, far outperforming traditional benchmarks.
Alex B.
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Emma, a software engineer with no prior trading experience, started with our beginner courses before progressing to advanced topics like “Machine Learning for Trading.” Through our end-to-end tutorials, Emma learned to set up a trading environment, integrate APIs for data collection, and apply machine learning models to predict market movements.
Emma’s breakthrough came when they combined LSTM neural networks with Forex time series data to predict price trends. Armed with these predictions, Emma developed a strategy that not only minimized risks but also capitalized on small, consistent gains. Over six months, Emma’s algorithmic trading portfolio grew by 20%, a testament to the power of practical, practitioner-driven education.
Emma R.
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Dedicated Professionals Behind SZEL

Our team consists of skilled professionals passionate about quantitative trading.

John Smith
Founder & CEO
Emily Davis
Head of Data Science
Michael Chang
Lead Forex Strategist