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Course Outline
Introduction
- Kaggle overview
- Kaggle categories and performance tiers
Kaggle Competitions
- Kaggle competitions overview
- Competition formats
- Joining a Kaggle competition
- Forming a team
Kaggle Datasets
- Types of datasets on Kaggle
- Searching and creating datasets
- Organizing and collaborating on datasets
Kaggle Kernels
- Types of kernels on Kaggle
- Searching for kernels
- Kernel editor and data sources
- Collaborating on kernels
Kaggle Public API
- Installation and authentication
- Using Kaggle API with competitions
- Using Kaggle API with datasets
- Creating and maintaining datasets
- Using Kaggle API with kernels
- Pushing and pulling a kernel
- Checking the status and output of a kernel
- Creating and running a new kernel
- Kaggle configurations
Summary and Next Steps
Requirements
- Proficiency in Python programming
- Familiarity with machine learning concepts
- Understanding of statistical principles
Audience
- Data scientists
- Developers
- Individuals interested in learning Data Science via Kaggle
14 Hours
