Advanced AI and Machine Learning Techniques and Capstone
Instructor: Microsoft
Intermediate Level • 3 weeks to complete at 10 hours a week • Flexible Schedule
Skills You'll Gain
Information Privacy
MLOps (Machine Learning Operations)
Deep Learning
Tensorflow
Scalability
Microsoft Azure
Distributed Computing
Ethical Standards And Conduct
Artificial Intelligence
Data Ethics
Artificial Neural Networks
Machine Learning
Machine Learning Methods
Generative AI
Applied Machine Learning
Artificial Intelligence and Machine Learning (AI/ML)
Shareable Certificate
Earn a shareable certificate to add to your LinkedIn profile
Outcomes
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Learn new concepts from industry experts
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Gain a foundational understanding of a subject or tool
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Develop job-relevant skills with hands-on projects
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Earn a shareable career certificate from Microsoft
There are 4 modules in this course
This advanced module delves into cutting-edge methodologies that enhance the performance, efficiency, and privacy of ML systems.
By the end of this module, you'll have hands-on experience with these advanced techniques, equipping you with the skills to tackle complex ML challenges and contribute to cutting-edge research and development.
This module provides an in-depth exploration of the ethical and human-centric considerations essential to the development and deployment of AI and ML systems. By the end of this module, you'll be equipped to critically assess and address the ethical, human, and organizational challenges posed by AI technologies, ensuring that your work aligns with both technical excellence and societal values.
This module focuses on designing and implementing distributed computing solutions to handle large-scale ML challenges efficiently. This module equips you with the knowledge and skills needed to build and optimize ML systems for high-throughput and scalable environments. By the end of this module, you'll be adept at designing, implementing, and optimizing distributed ML systems that can efficiently tackle large-scale problems, while balancing performance and cost considerations to meet organizational and project needs.
This module provides a comprehensive exploration of the professional and strategic aspects of working as an AI/ML engineer within a corporate environment. It will guide you through the key responsibilities, ethical considerations, and strategic decision-making processes relevant to the field.
By the end of this module, you will be well equipped to navigate your professional responsibilities, implement ethical AI practices, manage cost-performance trade-offs, and communicate effectively with stakeholders, positioning yourself as a valuable contributor in the corporate AI landscape.