Advanced AI and Machine Learning Techniques and Capstone
Master AI & ML with transfer learning, federated learning, and ensembles. Build ethical, scalable systems with a capstone.
Course Cost
Free course
Intermediate
Skill Level
30 Hours
Self-paced lessons
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.
What you'll learn
Implement advanced ML techniques such as ensemble methods and transfer learning
Design and optimize scalable AI systems for high-performance scenarios
Apply ethical frameworks to AI development ensuring responsible implementation
Develop privacy-preserving ML solutions using federated learning and differential privacy
Build and evaluate generative AI models for various applications
Create a comprehensive AI solution addressing real-world business problems
Skills you'll gain
This course includes:
32 Hours PreRecorded video
31 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate

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There are 4 modules in this course
This comprehensive course explores advanced AI and machine learning techniques culminating in a real-world capstone project. Students will master cutting-edge methodologies including transfer learning, federated learning, ensemble methods, and generative AI models. The curriculum covers ethical considerations in AI development, emphasizing responsible implementation practices and explainable AI frameworks. Students learn to design scalable AI/ML systems using distributed computing, data sharding, and parallel processing. The final module addresses professional aspects of AI/ML engineering in corporate environments, including strategic decision-making, cost-performance optimization, and stakeholder communication. Throughout the course, hands-on assignments and practical activities reinforce theoretical concepts, preparing students for advanced roles in AI and machine learning engineering.
Advanced ML techniques
Module 1 · 10 Hours to complete
Ethical considerations in AI/ML
Module 2 · 5 Hours to complete
Scalable AI/ML systems
Module 3 · 7 Hours to complete
AI/ML engineering and advanced techniques: The concepts in practice
Module 4 · 8 Hours to complete
Fee Structure
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.




