AI and Machine Learning Algorithms and Techniques
Master advanced AI/ML algorithms with Microsoft. Learn supervised, unsupervised, reinforcement & deep learning for real-world applications.
Master advanced AI/ML algorithms with Microsoft. Learn supervised, unsupervised, reinforcement & deep learning for real-world applications.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Microsoft AI & ML Engineering Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Implement, evaluate, and explain supervised, unsupervised, and reinforcement learning algorithms
Apply feature selection and engineering techniques to improve model performance
Describe deep learning models for complex AI tasks
Assess the suitability of various AI & ML techniques for specific business problems
Deploy and repair AI/ML systems in real-world corporate environments
Collaborate effectively within AI/ML development teams
Skills you'll gain
This course includes:
45 Hours PreRecorded video
45 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course covers the core algorithms and techniques used in AI and machine learning, including modern approaches that leverage pre-trained large language models. Students will explore three fundamental learning paradigms: supervised learning (including linear regression, logistic regression, and decision trees), unsupervised learning (focusing on clustering and dimensionality reduction), and reinforcement learning. The course also delves into deep learning neural networks, from basic architectures to advanced implementations using TensorFlow and PyTorch. Throughout the modules, learners gain practical experience implementing these techniques through hands-on activities in Python, learning to select appropriate algorithms for different business problems. The final module bridges theory and practice by examining real-world AI/ML engineering approaches and team dynamics in corporate settings.
Supervised learning
Module 1 · 11 Hours to complete
Unsupervised learning
Module 2 · 7 Hours to complete
Reinforcement learning and other approaches
Module 3 · 7 Hours to complete
Deep learning and neural networks
Module 4 · 9 Hours to complete
The concepts in practice
Module 5 · 8 Hours to complete
Fee Structure
Instructor
Empowering Individuals and Organizations Through Technology
Microsoft's mission is "to empower every person and every organization on the planet to achieve more," reflecting its commitment to leveraging technology for global empowerment. The company aims to drive digital transformation through an integrated cloud approach, creating a robust platform that enhances productivity and accessibility for users worldwide. Its vision statement emphasizes the goal of democratizing artificial intelligence, ensuring that AI technologies are accessible and beneficial for everyone. This focus on empowerment and inclusivity underpins Microsoft's strategies and product development, positioning it as a leader in innovation within the technology sector. The company has consistently pursued excellence by fostering a culture of innovation, diversity, and corporate social responsibility, ultimately aiming to improve quality of life and facilitate progress across various fields, including education, healthcare, and business.
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5 course rating
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Frequently asked questions
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