Course Overview
Learn how to use decision trees, the foundational algorithm for your
understanding of machine learning and artificial intelligence.
What you’ll learn
●Explore advanced data science challenges through sample data sets,
decision trees, random forests, and machine learning models
●Train your model to predict the most effective way to handle a
problem
●Examine machine learning results, recognize data bias in machine
learning, and avoid underfitting or overfitting data
●Build a foundation for the use of Python libraries in machine learning
and artificial intelligence, preparing you for future Python study
●Build on your Python experience, preparing you for a career in
advanced data science
Course description
When deciding on a vacation destination—beach or mountains—the choice is
straightforward. With only two options, your brain can process the decision
quickly. However, when faced with more complex, multi-layered decisions, the
process becomes more challenging. You might create a detailed pro/con list,
prioritizing key factors, but this can be time-consuming. When dealing with vast
amounts of data, both individuals and organizations need a more advanced
approach.
Requirements
- You will need a proper functioning laptop/desktop
- Stable internet connection
- No previous skills are required
- Must be able to understand English
Curriculum
- 1 Section
- 0 Lessons
- 6 Weeks
- Module 1: Introduction to AI & Machine LearningWhat is AI? What is Machine Learning? Real-world applications of AI Types of Machine Learning: Supervised, Unsupervised, Reinforcement Setting up Python for AI (Jupyter, Anaconda, VS Code) Project: Simple AI-powered calculator using Python0
Instructor
admin
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admin
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admin
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