Toolbox
LLM Driven Development for Machine Learning
Data Science
8 Stunden
Fortgeschrittene
Kostenfrei
Beschreibung
This course teaches you how to use Large Language Models (LLMs) like Claude.AI to enhance the development, training, and deployment of machine learning models for evaluating customer prospects. Through hands-on coding sessions led by experienced ML engineer Alexei, you’ll learn to analyze customer behavior, predict user actions, and build effective ML pipelines using tools like scikit-learn, XGBoost, and MLflow. The course emphasizes practical skills—model tuning, deployment on AWS, and experiment tracking—while demonstrating how LLMs can streamline workflows, improve productivity, and support every step of the data science process.
Was wirst du lernen?
- Understand how LLMs can assist in developing, training, and deploying machine learning models.
- Use AI tools like Claude.AI and MLflow to enhance productivity in data science workflows.
- Analyze customer behavior, predict user actions, and score leads using scikit-learn and XGBoost.
- Build effective data pipelines with strong foundations in data organization and feature engineering.
- Implement model tuning, validation, and deployment strategies on cloud platforms like AWS.
- Track experiments, automate model training, and apply techniques to prevent overfitting.
- Integrate LLMs into the coding workflow to develop, test, explain, and document data science projects efficiently.
- Gain confidence in using LLM-generated code, understanding its strengths and limitations.
- Explore different AI coding tools beyond Claude.AI, including open-source options and IDE integrations.
- Apply best practices for prompting and leveraging LLMs to solve real-world machine learning problems.
Welche Vorkenntnisse brauchst du?
Basic Data Science Knowledge