Methodology Overview | Applied AI Institute

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Data Science in Action using Dataiku

Introduction

Why this course (0:43)
Course Introduction (7:25)
Class Project (3:19)
Course Outline (4:43)
Instructors Bio (2:26)
Quizzes

Dataiku - Sandbox

Set-up Dataiku Sandbox (3:55)

Data Science Methodology

Methodology Evolution (6:07)
Methodology Overview (4:17)

Step 1: Define Project

Define Project Steps (12:22)
Define Project Example (4:32)
Quizzes

Step 2: Describe Data

Describe Data - Concepts (7:49)
Describe Data - Tasks and Deliverables (7:07)
Describe Data - Example - Load Data Sources (7:27)
Describe Data - Example - Classify Datasets (3:49)
Describe Data - Example - Describe Datasets (5:56)
Describe Data - Example - Verify Data Quality (5:20)
Quizzes

Step 3: Prepare Data

Prepare Data - Reduction (6:59)
Prepare Data - Feature Engineering (6:44)
Prepare Data - Synthesis (4:36)
Prepare Data - Task 1: Select (7:29)
Prepare Data - Task 2:Filter (8:21)
Prepare Data - Task 3: Transform (6:47)
Prepare Data - Task 4:Group (4:42)
Prepare Data - Task 5:Feature Engineering (6:55)
Prepare Data - Task 6: Merge (9:50)
Quizzes

Step 4: Develop Model

Develop Model - Overview (1:47)
Develop Model - Task 1: Classification Setup (7:22)
Develop Model - Task 2: Clustering (9:36)
Develop Model - Task 3: Prediction Setup (8:10)
Develop Model - Task4: Prediction (8:36)
Quizzes

Step 5: Evaluate Model

Step 5 - Prediction Evaluation - Overview (6:50)
Step 5 - Task 1: Prediction Evaluation (4:02)
Quizzes

Step 6: Deploy Model

Step 6 - Deploy Model - Overview (7:50)
Step 6 - Deploy Model - Task 1: Scoring Engine (10:07)
Quizzes

Step 7: Optimize Model

Step 7 - Optimize Model - Overview (5:10)
Quizzes

Summary

Final Review (6:50)
Future Learnings (4:07)
Quizzes

Teach online with

Methodology Overview

DS-A-P-S3-L2 Methodology Overview.pdf

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