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For SCORM package pricing and licensing requirements, please contact us.
Email: info@nanforiberica.com , Phones: +34 91 031 66 78 / +34 605 98 51 30, WhatsApp: +34 685 60 05 91 , Our Offices
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Applied Machine Learning course using Python - SCORM
This course is taught online and consists of three units. The approximate length of the course depends on the student's level and whether they repeat the practice between the course content and the collaboration tools. Upon completion, students will receive a certificate.
Course content
Unit 1. Introduction to the course
- Introduction to Python
- Python library for Machine Learning.
- Machine Learning. Introduction.
Unit 2. Supervised learning
- Definition and applications.
- Performance measures.
- Linear models
- Supervised ML models: trees, SVM, neural networks.
- Model Combination. Random Forest.
Unit 3. Unsupervised learning
- Definition and applications.
- Performance measures.
- Clustering. Types
- Biclustering
- Manifolds. Dimensionality Reduction
- Basket analysis.
Final evaluation
Quality Questionnaire.
Prerequisites
No technical prerequisites are required to take this course. However, basic computer skills and knowledge of IT-related environments are recommended.
________________________________________________________________
For SCORM package pricing and licensing requirements, please contact us.
Email: info@nanforiberica.com , Phones: +34 91 031 66 78 / +34 605 98 51 30, WhatsApp: +34 685 60 05 91 , Our Offices
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