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Course Outline
Introduction
- Kaggle platform overview
- Kaggle categories and performance tiers
Kaggle Competitions
- Kaggle competition overview
- Competition formats
- Participating in a Kaggle competition
- Team formation
Kaggle Datasets
- Types of datasets available on Kaggle
- Searching and creating datasets
- Organization and collaboration techniques
Kaggle Kernels
- Types of kernels on Kaggle
- Searching for kernels
- Kernel editor and data sources
- Collaborative kernel development
Kaggle Public API
- Installation and authentication
- Utilizing Kaggle API for competitions
- Utilizing Kaggle API for datasets
- Creating and maintaining datasets
- Utilizing Kaggle API for kernels
- Pushing and pulling kernels
- Monitoring kernel status and outputs
- Creating and executing new kernels
- Kaggle configuration settings
Summary and Next Steps
Requirements
- Proficiency in Python programming
- Foundational knowledge of machine learning
- Understanding of statistical concepts
Target Audience
- Data scientists
- Developers
- Individuals interested in learning Data Science through Kaggle
14 Hours
