Build a strong foundation in machine learning with Duke Universityβs beginner-friendly course. Perfect for students and young professionals starting their AI journey. Learn at your own pace with hands-on Python projects.

16 Weeks
IvySchool.ai + Duke University Partner
Online + Live
Transform your career with industry's most comprehensive LLMOps specialization
This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction. In addition, we have designed practice exercises that will give you hands-on experience implementing these data science models on data sets. These practice exercises will teach you how to implement machine learning algorithms with PyTorch, open source libraries used by leading tech companies in the machine learning field (e.g., Google, NVIDIA, CocaCola, eBay, Snapchat, Uber and many more).
Perfect for professionals ready to lead AI transformation in their organizations
Build foundational AI skills for future academic pursuits
Enhance your CS curriculum with practical ML experience
Start your AI career with industry-relevant skills
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By the end of this course, youβll have a solid foundation in machine learning concepts and practical experience implementing ML algorithms with Python and PyTorch.
Learn supervised and unsupervised learning, classification, regression, and clustering
Apply key algorithms like linear regression, decision trees, and neural networks using Python
Use metrics such as accuracy, precision, recall, and F1-score to assess models
Preprocess, clean, and analyze datasets for effective machine learning applications
Understand bias, fairness, and ethical considerations in machine learning models
6 sections, 69 lessons, 16 weeks of foundational machine learning education
Join hundreds of students who are already building their future in AI
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