Undergraduate Certificate in Machine Learning Semi-Supervised Learning
-- viewing nowThe Undergraduate Certificate in Machine Learning: Semi-Supervised Learning is a career-enhancing course designed to equip learners with essential skills in machine learning. This certificate program focuses on semi-supervised learning, a powerful approach that combines both unsupervised and supervised learning techniques, enabling machines to learn from limited labeled data.
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Course Details
• Introduction to Machine Learning · Overview of supervised, unsupervised, and
semi-supervised learning, common algorithms, and applications.
• Data Preprocessing · Data cleaning, normalization, and feature engineering.
• Semi-Supervised Learning Fundamentals · Introduction to SSL techniques,
advantages, and limitations.
• Self-training · Pseudo-labeling, entropy-based methods, and confidence
thresholding.
• Multi-view Training · Co-training, multi-view bootstrapping, and
tri-training.
• Graph-based Semi-Supervised Learning · Graph construction, label
propagation, and graph-based SSL algorithms.
• Deep Semi-Supervised Learning · Semi-supervised deep learning models,
generative adversarial networks (GANs), and deep belief networks (DBNs).
• Evaluation Metrics for Semi-Supervised Learning · Accuracy, precision,
recall, F1 score, and area under the curve (AUC).
• Real-World Applications of Semi-Supervised Learning · Case studies
highlighting the use of SSL in industries such as healthcare, finance, and
marketing.
Career Path
Entry Requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course Status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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