4 Topics Available
Data Science Pipelines
Master Data Science Pipelines from core theoretical foundations to practical industry applications.
1Module 1: End-to-End Data Processing Workflows
Core modules and technical concepts for Data Science Pipelines.
Topic 1.1: Feature Engineering and Pipeline Design
Foundational and applied principles of Feature Engineering and Pipeline Design.
Categorical Encoding, Scaling, and Imputation Pipelines
Comprehensive technical guide and practical walkthrough of Categorical Encoding, Scaling, and Imputation Pipelines.
Feature Selection and Dimensionality Techniques
Comprehensive technical guide and practical walkthrough of Feature Selection and Dimensionality Techniques.
Topic 1.2: Model Tracking and Deployment
Foundational and applied principles of Model Tracking and Deployment.
Experiment Tracking with MLflow
Comprehensive technical guide and practical walkthrough of Experiment Tracking with MLflow.
Packaging and Serving Machine Learning Models via REST APIs
Comprehensive technical guide and practical walkthrough of Packaging and Serving Machine Learning Models via REST APIs.