{"id":3996,"date":"2025-04-06T22:26:17","date_gmt":"2025-04-07T02:26:17","guid":{"rendered":"https:\/\/engineering.jhu.edu\/ExecEd\/?post_type=course&p=3996"},"modified":"2025-09-10T14:40:17","modified_gmt":"2025-09-10T18:40:17","slug":"foundations-machine-learning","status":"publish","type":"course","link":"https:\/\/engineering.jhu.edu\/ExecEd\/course\/foundations-machine-learning\/","title":{"rendered":"Theoretical Foundations of Machine Learning-Techniques and Applications"},"content":{"rendered":"\n
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Theoretical Foundations of Machine Learning-Techniques and Applications<\/h1>\n\n\n
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Start anytime. Learn at your own pace.<\/p>\n\n\n

Build essential skills in data preparation, model training, and results evaluation.<\/p>\n\n\n

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Start Now<\/a><\/div>\n<\/div>\n\n\n\n
Request Info<\/a>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n
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<\/rect><\/g><\/path><\/g><\/polygon><\/polygon><\/polygon><\/g><\/svg><\/span>Artificial Intelligence<\/span><\/span><\/p>\n\n\n\n

<\/title><\/path><\/path><\/path><\/circle><\/svg><\/span>Online Self-Paced<\/span><\/span><\/p>\n<\/div>\n\n\n\n
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Instructor: Dr. Erhan Guven<\/a><\/p>\n\n<\/div><\/div>\n<\/div>\n\n\n

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<\/path><\/svg><\/span>Curriculum designed and delivered by Johns Hopkins faculty<\/a><\/span><\/p>\n\n\n\n

<\/path><\/svg><\/span>LIVE monthly seminars and office hours<\/a> <\/span><\/p>\n\n\n\n

<\/path><\/svg><\/span>Engaging learning including video walkthroughs and hands-on activities<\/a><\/span><\/p>\n\n\n\n

<\/path><\/svg><\/span>Satisfaction guaranteed<\/a>. Explore the course with no risk.<\/strong><\/span><\/p>\n<\/div>\n\n<\/div><\/div>\n\n<\/div>\n\n

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In machine learning, even simple models with well-prepared data can outperform complex algorithms trained on poorly processed inputs. Mastering the fundamentals is essential.

With step-by-step video guidance from instructor Dr. Erhan Guven<\/a>, the first course in the Certificate in Theoretical Foundations of Machine Learning<\/a><\/a> puts you straight into building working classification systems while ensuring you have the essential knowledge of data preparation and feature engineering\u2014the keys to ML success. The videos are complemented by projects,<\/a> insightful readings and quizzes to test your comprehension.

Dr. Guven’s Jupyter notebooks will keep you on the right track, helping you understand the machine learning workflow while challenging you to implement key components yourself. You’ll develop practical coding skills (and confidence) as you progress from data preparation through model training to evaluation and refinement.

With scikit-learn, pandas, and real-world datasets you’ll implement your first Support Vector Machines, Naive Bayes classifiers and text categorizing systems<\/a>. Then you’ll make them more accurate and more predictive.

By the conclusion of this course, you’ll be able to implement the complete machine learning workflow and have an excellent foundation to build upon.<\/p>\n<\/div>\n\n\n\n

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Prerequisites <\/h2>\n\n\n\n

You should have basic Python programming skills and comfort with high school-level math. The focus is on practical implementation rather than mathematical theory. If you can write simple Python functions and aren’t intimidated by working with data in tables, you’re ready to go. <\/p>\n<\/div>\n\n\n\n

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No Risk: Satisfaction Guaranteed<\/h2>\n\n\n\n

Feel confident in your learning journey! If the course content is too advanced, not advanced enough<\/em>, or simply doesn\u2019t meet your expectations, we\u2019ve got you covered with our money-back guarantee. Just contact our team within 7 days from purchase to receive a full refund\u2014no questions asked.<\/strong> <\/p>\n<\/div>\n\n\n\n

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Meet Your Instructor<\/h2>\n\n\n\n

Dr. Erhan Guven<\/h3>\n\n\n\n

Johns Hopkins University, Johns Hopkins Applied Physics Laboratory<\/em><\/p>\n<\/div>\n\n\n\n

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Dr. Guven is an AI scientist at Johns Hopkins University Applied Physics Laboratory and assistant program manager in Johns Hopkins Engineering’s #1 ranked online master’s programs in AI and data science. His research spans a broad spectrum of machine learning applications, including large language models, financial systems cybersecurity, NLP, and bioinformatics. In his spare time, he enjoys gardening, beekeeping, building computers and playing Defense of the Ancients. <\/p>\n<\/div>\n\n\n\n

Dr. Guven is Here to Help!<\/strong><\/h4>\n\n\n\n

Questions about course content? Looking compare model results or get feedback? Stop by monthly Zoom office hours<\/strong> to talk with Erhan and fellow students.<\/p>\n<\/div>\n\n\n\n

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Projects You’ll Build (With Expert Guidance)<\/h2>\n\n\n\n

With ready-to-use Jupyter notebooks and working code examples, Dr. Guven will walk you through creating…<\/p>\n\n\n\n