Data Science Master

Data Science Master Program

This program has been designed especially for regular users of Data Science and expose them to advanced methods of deep learning and ensemble models.



CLASS SCHEDULE

DAY I

SESSION TOPIC:
Time Series Forecasting I (R)

SESSION CONTENT:
ARIMA / SARIMA Models

SESSION TOPIC:
Time Series Forecasting II (R)

SESSION CONTENT:
ARIMA / SARIMA Models

SESSION TOPIC:
Time Series Forecasting III (R)

SESSION CONTENT:
ARCH / GARCH Models

SESSION TOPIC:
Time Series Forecasting IV (R)

SESSION CONTENT:
ARCH / GARCH Models

DAY II

SESSION TOPIC:
Deep Learning I (Python - Keras)

SESSION CONTENT:
Regression: Linear / Logistic

SESSION TOPIC:
Deep Learning II

SESSION CONTENT:
Perceptron: Single / Multilayer

SESSION TOPIC:
Deep Learning III

SESSION CONTENT:
Convolutional Neural Network (CNN)

SESSION TOPIC:
Deep Learning IV

SESSION CONTENT:
Convolutional Neural Network (CNN)

DAY III

SESSION TOPIC:
Deep Learning V

SESSION CONTENT:
Recurrent Neural Network (RNN)

SESSION TOPIC:
Deep Learning VI

SESSION CONTENT:
Recurrent Neural Network (RNN)

SESSION TOPIC:
Ensemble Models I (R)Ensemble Models I (R)

SESSION CONTENT:
Bootstrap / Bagging

SESSION TOPIC:
Ensemble Models II (R)

SESSION CONTENT:
SMOTE

DAY IV

SESSION TOPIC:
Ensemble Models III (R)

SESSION CONTENT:
AdaBoost

SESSION TOPIC:
Ensemble Models IV (R)

SESSION CONTENT:
AdaBoost

SESSION TOPIC:
Ensemble Models V (R)

SESSION CONTENT:
XGBoost

SESSION TOPIC:
Ensemble Models VI (R)

SESSION CONTENT:
XGBoost