Trading Systems, Python and AI for Finance
Practical learning paths for those who want to build concrete skills, develop real strategies and work autonomously with professional tools.
Who it is for
This training is designed for those who want to go beyond theory and turn ideas, data and models into tools that can actually be used in the markets.
Traders and Investors
For those who want to build more robust, measurable and repeatable strategies.
Financial Analysts
For those who want to integrate quantitative analysis, automation and model development.
Technical Professionals
For those who want to combine coding, data and finance within a more advanced workflow.
Our approach
Unlike traditional training, Gandalf Project combines practical application, quantitative thinking and integration across different tools.
Real-world application
Not just concepts: you develop code, logic and models that can be used in practice.
Full integration
Platforms, Python and AI are not separate worlds, but parts of the same ecosystem.
Quantitative mindset
The goal is not to follow the market, but to measure it, model it and interpret it.
Choose your starting point
There is no single path that fits everyone. Some professionals start from trading system platforms, while others choose an open-source infrastructure in Python. The map below helps you find your direction (currently, the ‘EasyLanguage Crash Course’ is the only program available in English).
Two main paths
The choice depends on your goals, the tools you want to use and the level of flexibility you want to achieve.
The most direct path to building trading systems within trading platforms
Designed for those who want to develop strategies on dedicated platforms, automate trading logic and improve control over equity, risk and performance.
When to choose it
- You want an environment already geared toward trading system development
- You want to move more quickly from idea to strategy
- You already work with TradeStation, MultiCharts or similar logic frameworks
- You want to integrate execution and broker connectivity via API
The path to building a more flexible and scalable infrastructure
Designed for those who want to work in open source, develop custom quantitative models, analyze financial data and integrate Machine Learning and AI into their workflows.
When to choose it
- You want maximum flexibility and control over your code
- You want to build proprietary models and data pipelines
- You want to work on quantitative analysis, signals and asset allocation
- You want to develop long-term, future-proof skills
What you gain
Operational skills
- Real, reusable code
- Practical applications for financial markets
- A structured and progressive approach
- An integrated view of strategy, risk and execution
Support and continuity
- Access to the Gandalf Project community
- Interaction with other participants
- Sharing ideas, case studies and strategies
- A path focused on concrete results
Not sure where to start?
We can help you identify the most suitable path based on your current skills, the tools you use and the goals you want to achieve.
