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.
Master AI & ML with transfer learning, federated learning, and ensembles. Build ethical, scalable systems with a capstone.
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.
Instructors:
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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
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
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
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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Frequently asked questions
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