Zero to Agile Data Science

🌟 Course Title: Zero to Agile Data Science

Headline: Dive into Mastering Agile Data Science Techniques for Classification Problems with Real-World Projects!

Course Description:

Embark on a transformative journey through the dynamic world of Agile Data Science with our comprehensive course, where you'll master iterative development techniques and apply them to tackle Classification problems. 🚀

What You Will Learn:

• Hands-On Experience: Engage with 3 practical projects: Predicting Credit Card Fraud, Predicting Customer Churn, and Predicting Financial Distress.
• Iterative Development: Progress through 5 iterations for each project, evolving from a basic Random Forest Classifier to an advanced ensemble of classifiers.
• Skill Enhancement: Perfect your intermediate skills with Agile Data Science by learning automated data quality checks, custom metrics, resampling techniques, feature engineering and reduction, memory optimization, and much more!

Course Breakdown:

• Day 1 (Iteration 1): Uncover the secrets of detecting bad columns in raw data and craft your own metric for imbalanced datasets.

  • Automated detection of bad columns
  • Custom metric creation for imbalanced datasets

• Day 2 (Iteration 2): Master four resampling techniques and effective handling of Nulls.

  • Four Data Resampling methods
  • Handling Nulls in your dataset

• Day 3 (Iteration 3): Discover two innovative Feature Engineering techniques and four Feature Reduction methods to streamline your models. Additionally, learn how to reduce the memory footprint of your Data Science projects.

  • Two Feature Engineering techniques
  • Four Feature Reduction techniques
  • Memory footprint reduction strategies

• Day 4 (Iteration 4): Customize your model selection process by setting a custom scoring function inside the GridSearchCV.

  • Setting a custom scoring function in GridSearchCV

• Day 5 (Iteration 5): Optimize your XGBoost models by changing default scoring metrics and explore building meta-models.

  • Customizing XGBoost scoring settings
  • Meta-model building

Course Resources:

• Comprehensive Jupyter notebooks with source code for each project.
• A library of reusable functions to support your own Data Science endeavors.

With this course, you're not just learning Agile Data Science—you're preparing to be a part of the future of data modeling, where speed, efficiency, and precision are key. 📊💡

Who Should Take This Course:

This course is tailored for intermediate Data Scientists who wish to:

• Sharpen their skills with advanced Agile Data Science techniques.
• Apply these techniques to real-world Classification problems.
• Enhance their iterative development process for better model performance and efficiency.

Join Shreesha Jagadeesh, an expert in the field, as he guides you through this transformative learning experience. 🧠✨

Enroll now and accelerate your career in Data Science! 🚀🎓