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Course Outline
Introduction to Machine Learning and Google Colab
- Overview of machine learning
- Setting up Google Colab
- Python refresher
Supervised Learning with Scikit-learn
- Regression models
- Classification models
- Model evaluation and optimization
Unsupervised Learning Techniques
- Clustering algorithms
- Dimensionality reduction
- Association rule learning
Advanced Machine Learning Concepts
- Neural networks and deep learning
- Support vector machines
- Ensemble methods
Special Topics in Machine Learning
- Feature engineering
- Hyperparameter tuning
- Model interpretability
Machine Learning Project Workflow
- Data preprocessing
- Model selection
- Model deployment
Capstone Project
- Defining the problem statement
- Data collection and cleaning
- Model training and evaluation
Summary and Next Steps
Requirements
- An understanding of basic programming concepts
- Experience with Python programming
- Familiarity with basic statistical concepts
Audience
- Data scientists
- Software developers
14 Hours
Testimonials (2)
I really liked the end where we took the time to play around with CHAT GPT. The room was not set up the best for this- instead of one large table a couple of small ones so we could get into small groups and brainstorm would have helped
Nola - Laramie County Community College
Course - Artificial Intelligence (AI) Overview
Working from first principles in a focused way, and moving to applying case studies within the same day
