Sooner or later, every Data Scientist meets with financial tasks in general and with automation of trading on a stock exchange – in particular. But not every Data Scientist knows how to apply Deep Reinforcement Learning to these assignments effectively. This course is designed to teach you just that – with real examples.
- Jupyter Notebook
Level of complexity of course
- Math: linear algebra, optimization theory, calculus.
- Hands-on Data Science, Machine Learning, and Deep Learning.
- Basic Reinforcement Learning and Deep Reinforcement Learning.
- Understanding of basic trading concepts like futures, tickers, bid, ask, volume, order book, limited and market orders, etc.
Dr. Oleksandr Gurbych
Software Solution Architect in blackthorn.ai
Oleksandr is a C/C++ developer, NET/C# developer, Java developer, Python developer, frontend developer, backend engineer, Data Scientist, Machine Learning Engineer, NLP Engineer, Computer Vision Engineer, BigData Engineer, DevOps/MLOps, QA/QC Engineer, Business Analyst, BI Lead, scientist, lawyer, Sales Development Representative (SDR), marketing manager, project manager, team leader, software architect, UI/UX designer, HR manager, PR manager, SEO, copywriter, partnerships manager, outreach manager, client success manager, account executive, events manager, content writer, YouTube video blogger, Medium blogger, sportsman, lecturer at National University “Lviv Polytechnic”, conference manager, conference speaker, and a happy father of two kiddos with more than 30 years of hands-on experience.
Fields of interests