Intermediate ML knowledge is recommended.Familiarity with Python, TensorFlow, and ML workflows is helpful.Labs assume you can manipulate ...
Hands-on labs with Vertex AI Feature Store and BigQuery ML.Practice transformations like bucketing, crosses, and scaling.Integrates feature ...
Prepares for ML Engineer or MLOps Engineer roles.Supports Data Scientist positions focusing on production ML.Emphasizes best practices for ...
Covers metadata management and feature versioning.Introduces integration of features into ML pipelines (MLOps).Advanced transformations ...
Total course duration is ~8–8.5 hours.Modules include hands-on labs and practical assignments.Labs may take extra time depending on prior ...
Basic financial or trading knowledge is helpful but not mandatory.The course introduces trading concepts like momentum, pairs trading, and ...
Labs cover building ML models using Python and GCP.Backtesting frameworks allow experimentation with real trading data.RL-based strategy ...
Prepares for roles like Quantitative Analyst, Algorithmic Trader, or ML Engineer.Builds skills for designing ML-driven trading strategies....
Introduces policy/value functions and LSTM applications for time-series.RL labs may be limited in coding exercises.Some RL concepts are ...
Total estimated duration is ~38 hours across modules.Module 2 (ML in trading) is the most time-intensive (~18 hours).RL module takes ~15 ...
