What you will learn
- Apply common operations (pre-processing, plotting, etc.) to datasets using Python.
- Explain the concept of supervised, semi-supervised, unsupervised machine learning and reinforcement learning.
- Explain how various supervised learning models work and recognize their limitations.
- Analyze which factors impact the performance of learning algorithms.
- Apply learning algorithms to datasets using Python and Scikit-learn and evaluate their performance.
- Optimize a machine learning pipeline using Python and Scikit-learn.
- Describe the main classes of clustering techniques.
- Implement k-means and hierarchical clustering.
- Motivate the need and choice of dimensionality reduction techniques.
- Implement Principal Component Analysis (PCA) for feature extraction.
- Explain how deep neural networks work and their advantages.
- Train deep neural networks for classification and regression tasks.
- Explain the basic concepts and techniques of reinforcement learning.
- Describe how reinforcement learning could be applied in real world applications.
Program Overview
Expert instruction
2 skill-building courses
2 months
6 - 8 hours per week
Discounted price: $268.20
Pre-discounted price: $298USD
For the full program experience
Courses in this program
DelftX's AI Skills: Basic and Advanced Techniques in Machine Learning Professional Certificate
- AI skills for Engineers: Supervised Machine Learning
- AI skills: Introduction to Unsupervised, Deep and Reinforcement Learning
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Discounted price: $268.20
Pre-discounted price: $298USD
2 courses in 2 months
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