This bundle brings Python foundations together with a dedicated quantitative-trading build path: data, strategy design, backtesting and optimisation. Access it instantly from Courses On Budget.
A Structured Route from Python to Quant Research
The QuantFactory bundle is split into two course tracks. The first establishes Python, Pandas and simple indicator/backtest work. The second develops a strategy workflow through Backtrader, data preparation, testing and optimisation.
| Course index | 18 folders · 163 files · 1.90 GB |
| Included formats | Video lessons, notebooks, code/text files, datasets and image references |
| Tools in the index | Python, Anaconda, Jupyter, Pandas and Backtrader |
QuantFactory Curriculum
Python Fundamentals for Quant Trading
- Anaconda installation and Jupyter walkthrough.
- Python basics: variables, data types, arithmetic, comparisons, conditions, loops, functions and classes.
- Pandas: loading and manipulating data, rolling functions and datetime indexes.
- Technical indicators, strategy metrics and a strategy-building/backtesting workflow.
Quant Trading Strategies with Python
- Why backtesting matters, testing rules, metrics and out-of-sample testing.
- Backtrader fundamentals: feeds, orders, position size, commissions, analyzers, exits and stops.
- Strategy ideas, technical indicators, additional data and possible machine-learning discussion.
- Feature preparation, data extraction, backtester construction, visualisation and optimisation.
Best For
This bundle fits learners who want both a coding foundation and a clear sequence for transforming a strategy idea into a backtested workflow. The separate foundations track makes the advanced material less abrupt for students who are newer to Python.
Browse the Trading Courses category, compare more programmes on Trading Courses Cheap, or see newly added content on Updates.
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