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Advanced Machine Learning Course
Boost your Business Intelligence know-how with our Advanced Machine Learning Course. Dig deep into data exploration methods, become a master at predictive analysis, and learn how to understand model predictions properly. Get expert knowledge in time series forecasting using ARIMA, Prophet, and LSTM models. Improve your skills in model training, checking performance, and fine-tuning settings. This course gives you practical, top-quality stuff designed to give you the tools you need for making smart decisions based on data.
- Master data exploration: Find valuable information using EDA and picture-making tools.
- Predictive analysis skills: Understand and report model predictions clearly.
- Time series expertise: Learn ARIMA, Prophet, and LSTM models for making forecasts.
- Model evaluation techniques: Use cross-validation and performance scores to check models.
- Hyperparameter tuning: Make models work best by using grid search and Bayesian methods.

flexible workload from 4 to 360h
certificate recognized by MEC
What will I learn?
Boost your Business Intelligence know-how with our Advanced Machine Learning Course. Dig deep into data exploration methods, become a master at predictive analysis, and learn how to understand model predictions properly. Get expert knowledge in time series forecasting using ARIMA, Prophet, and LSTM models. Improve your skills in model training, checking performance, and fine-tuning settings. This course gives you practical, top-quality stuff designed to give you the tools you need for making smart decisions based on data.
Elevify advantages
Develop skills
- Master data exploration: Find valuable information using EDA and picture-making tools.
- Predictive analysis skills: Understand and report model predictions clearly.
- Time series expertise: Learn ARIMA, Prophet, and LSTM models for making forecasts.
- Model evaluation techniques: Use cross-validation and performance scores to check models.
- Hyperparameter tuning: Make models work best by using grid search and Bayesian methods.
Suggested summary
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