Week 1 - Identify DataSet and UseCase-Introduction
Capstone Introduction
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A warm welcome
Week 1 - Identify DataSet and UseCase-Architecturel Methodologies for DataScience
Overview of Architectural Methodologies for DataScience
Lightweight IBM Cloud Garage Method for Data Science
Week 1 - Identify DataSet and UseCase-Step 1: Exploring Data Sources and Use Cases
Data Sources and Use Cases
Initial Data Exploration
Week 1 - Identify DataSet and UseCase-Step 2: Documenting your work (Everything Should Be Made as Simple as Possible, But Not Simpler - Einstein)
Architectural Decisions Document (ADD)
Process Model Guidelines
Week 2 - ETL and Feature Creation-Step 4: ETL (Extract Transform Load)
Extract Transform Load (ETL)
Week 2 - ETL and Feature Creation-Step 5: Feature Creation
Data Cleansing
Feature Engineering
Week 3 - Model Definition and Training-Step 6: Model Definition
Model Definition
Week 3 - Model Definition and Training-Step 7: Model Training
Model Training
Model Evaluation, Tuning, Deployment and Documentation-Step 8: Model Evaluation
Model Evaluation
Model Evaluation, Tuning, Deployment and Documentation-Step 9: Model Deployment and Data Product
Model Deployment
Data Product (optional)
Model Evaluation, Tuning, Deployment and Documentation-Step 10: Create Final Deliverables
Create ADD - Architectural Decisions Document
Create a Video of your final presentation