Ementorhub

Skills you'll gain

Deep Learning

Tensorflow

Generative AI

Information Privacy

Data Ethics

Machine Learning Methods

Artificial Intelligence

Ethical Standards And Conduct

Artificial Neural Networks

Machine Learning

Scalability

Microsoft Azure

Applied Machine Learning

MLOps (Machine Learning Operations)

Artificial Intelligence and Machine Learning (AI/ML)

Distributed Computing

There are 4 modules in this course

By the end of this course, you will be able to: 1. Implement advanced ML techniques such as ensemble methods and transfer learning. 2. Analyze ethical implications and develop strategies for responsible AI. 3. Design scalable AI & ML systems for high-performance scenarios. 4. Develop and present a comprehensive AI & ML solution addressing a real-world problem. To be successful in this course, you should have intermediate programming knowledge of Python, plus experience with AI & ML infrastructure, core AI & ML algorithms and techniques, the design and implementation of intelligent troubleshooting agents, and Microsoft Azure’s AI & ML services. Familiarity with statistics is also recommended.

Ethical considerations in AI/ML

Scalable AI/ML systems

AI/ML engineering and advanced techniques: The concepts in practice