AI-201Data Science, AI & MLIntermediate3 days
Machine Learning and AI Applications
An applied Python course covering the workflow from data preparation through model evaluation, deployment patterns and responsible practice. Every module includes tools and a specific exercise.
Enquire about this courseWhat you will learn
- Prepare and engineer features from real datasets using Python
- Train, evaluate and compare ML models using scikit-learn
- Apply NLP and computer vision techniques to practical problems
- Design a responsible deployment and monitoring plan
Who should attend
Data practitioners and software engineers who want to apply machine learning using Python. AI-101 or equivalent Python experience recommended.
What you will cover
Topics covered
- NumPy, pandas, matplotlib recap
- Data wrangling workflows
- Feature engineering
Tools used
Python, Jupyter Notebookspandas, scikit-learn
Exercise
Clean and engineer features from a provided raw dataset.
Practical learning
Course practical activity
Build and present a Python-based ML prototype with a decision metric, evaluation results, limitations and deployment/monitoring plan.