Kaggle Training and Certification in Thimphu, Bhutan

This course is designed to introduce learners to Kaggle, a leading platform for data science competitions, datasets, and community learning. Participants will learn how to use Kaggle for practicing data science, exploring datasets, building models, and submitting solutions to real-world problems.

Introduction to Kaggle and Data Exploration

Getting Started with Kaggle

• What is Kaggle and how it works
• Creating an account and setting up a profile
• Overview of the Kaggle interface: Datasets, Competitions, Notebooks, and Discussions
• Earning points, medals, and ranks on Kaggle

Working with Datasets on Kaggle

• Searching and selecting datasets
• Downloading datasets or using Kaggle notebooks directly
• Dataset structure and metadata
• Using data for exploration and analysis

Introduction to Kaggle Notebooks (Kernels)

• Creating and editing notebooks in Kaggle
• Code cells vs Markdown cells
• Installing packages and using GPUs/TPUs
• Saving, publishing, and sharing notebooks

Exploratory Data Analysis (EDA)

• Loading datasets using Pandas
• Descriptive statistics and summaries
• Data cleaning basics
• Visualizing data using Matplotlib and Seaborn

Competitions, Modeling, and Submissions

Understanding Kaggle Competitions

• Types of competitions (Featured, Research, Recruitment, Playground)
• Reading competition rules, evaluation metrics, and deadlines
• Downloading competition data
• Submission format and sample submissions

Building Your First Kaggle Model

• Setting up a notebook for training
• Splitting data into train/test
• Applying simple models (e.g., Logistic Regression, Random Forest)
• Generating predictions for submission

Making and Submitting Predictions

• Creating submission files
• Uploading predictions to the competition page
• Understanding the public vs private leaderboard
• Learning from top solutions and notebooks

Best Practices and Community Engagement

• How to learn from discussions and public notebooks
• Following experts and participating in courses
• Collaborating on Kaggle teams
• Tips to move from beginner to competition contributor

Final Activity and Assessment

• Group discussion: lessons learned, strategies, next steps