Professional Certificate in Machine Learning
-- ViewingNowThe Professional Certificate in Machine Learning is a comprehensive course designed to equip learners with essential skills for career advancement in the data science industry. This program covers key concepts, including machine learning algorithms, data mining, and predictive analytics.
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⢠Introduction to Machine Learning (Primary Keyword): Overview of machine learning, its applications, and key concepts.
⢠Data Preprocessing: Techniques for data cleaning, transformation, and normalization.
⢠Supervised Learning: Theory and algorithms of supervised learning, including linear regression, logistic regression, and support vector machines.
⢠Unsupervised Learning: Theory and algorithms of unsupervised learning, including clustering and dimensionality reduction.
⢠Neural Networks and Deep Learning: Introduction to artificial neural networks, backpropagation, and deep learning techniques.
⢠Reinforcement Learning: Overview of reinforcement learning, Q-learning, and policy gradients.
⢠Evaluation Metrics: Techniques for evaluating and comparing machine learning models.
⢠Ethics in Machine Learning: Discussion of ethical considerations in machine learning, including bias, fairness, and privacy.
⢠Deployment and Maintenance: Best practices for deploying and maintaining machine learning models in production environments.
Note: The above list assumes a beginner to intermediate level of knowledge in machine learning. The specific units and topics may vary depending on the course provider and the intended audience.
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