Data Science Advanced

Data Science Advanced Program

This program has been designed especially for executives and managers on Data Science and expose them to various statistical methods, predictive modeling techniques, machine learning approaches and tools used for the same. The program shall also focus on data presentation through visualization.



CLASS SCHEDULE

DAY I

SESSION TOPIC:
Classification I ( using R / Python)

SESSION CONTENT:
Supervised Learning: CART

SESSION TOPIC:
Classification II

SESSION CONTENT:
Supervised Learning: CART

SESSION TOPIC:
Classification III

SESSION CONTENT:
Supervised Learning: Naïve Bayes

SESSION TOPIC:
Classification IV

SESSION CONTENT:
Supervised Learning: Naïve Bayes

DAY II

SESSION TOPIC:
Classification V

SESSION CONTENT:
Supervised Learning: K Nearest Neighbors

SESSION TOPIC:
Classification VI

SESSION CONTENT:
Supervised Learning: K Nearest Neighbors Plots

SESSION TOPIC:
Unsupervised Learning

SESSION CONTENT:
Clustering

SESSION TOPIC:
Unsupervised Learning

SESSION CONTENT:
Clustering

DAY III

SESSION TOPIC:
Classification VII (Python)

SESSION CONTENT:
Random Forest

SESSION TOPIC:
Classification VIII (P)

SESSION CONTENT:
Random Forest

SESSION TOPIC:
Visualization (Tableau) I

SESSION CONTENT:
Data Prep / Data Dimensions

SESSION TOPIC:
Visualization (T) II

SESSION CONTENT:
Tableau – Connecting to Multiple Sources

DAY IV

SESSION TOPIC:
Visualization (Tableau) III

SESSION CONTENT:
Data Prep – Joins / Unions / Conversions

SESSION TOPIC:
Visualization (T) IV

SESSION CONTENT:
Chart Types – Scatter / Bubble / Heat Maps

SESSION TOPIC:
Visualization (T) V

SESSION CONTENT:
Data Exploration – Trends / Outliers / relationships

SESSION TOPIC:
Visualization (T) VI

SESSION CONTENT:
Dash Boards