Microsoft
AI and Machine Learning Algorithms and Techniques
Microsoft

AI and Machine Learning Algorithms and Techniques

 Microsoft

Instructor: Microsoft

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

45 hours to complete
3 weeks at 15 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

45 hours to complete
3 weeks at 15 hours a week
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Recently updated!

November 2024

Assessments

45 assignments

Taught in English

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This course is part of the Microsoft AI & ML Engineering Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
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  • Gain a foundational understanding of a subject or tool
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There are 5 modules in this course

In this module, you'll embark on a comprehensive journey through the essentials of supervised ML. This module is designed to equip you with a robust understanding and practical skills in the field, ensuring you're well prepared to tackle real-world data problems. By the end of this module, you'll not only have a strong theoretical foundation but also practical experience in supervised learning, enabling you to confidently develop, evaluate, and optimize predictive models for a variety of applications.

What's included

9 videos30 readings15 assignments

This module is a deep dive into the world of data analysis where the patterns and insights are uncovered without predefined labels. It is tailored to provide a comprehensive understanding and practical skills in unsupervised learning, empowering you to discover hidden structures within your data. By the end of this module, you'll have a solid grasp of unsupervised learning concepts and practical skills in implementing, analyzing, and comparing different algorithms. This knowledge will enable you to unlock valuable insights from complex datasets and make informed decisions based on your analyses.

What's included

4 videos18 readings9 assignments

This module is designed to provide an in-depth exploration of cutting-edge techniques in ML. This module merges foundational reinforcement learning concepts with advanced strategies for enhancing language generation models, offering a well-rounded understanding of these pivotal areas in AI. By the end of this module, you’ll be equipped with theoretical knowledge and practical experience in reinforcement learning and language model enhancement. This comprehensive understanding will enable you to tackle complex problems and contribute to innovative solutions in the rapidly evolving field of AI.

What's included

6 videos11 readings6 assignments

This module is designed to provide a comprehensive introduction to neural networks and their applications in modern AI. It will guide you through the core principles of deep learning, from basic neural network architecture to advanced applications in image and text data, while also exploring the significance of deep learning within the realm of generative AI (GenAI). By the end of this module, you will have a solid grasp of neural network architectures, practical experience with deep learning techniques, and a clear understanding of how these technologies are applied within the broader landscape of GenAI. This knowledge will enable you to leverage deep learning effectively in academic and real-world scenarios.

What's included

5 videos14 readings8 assignments

This module is a focused exploration of the roles, responsibilities, and approaches in the field of AI and ML within a business environment. It is designed to provide a comprehensive understanding of how AI/ML engineers operate, the distinctions between handling in-house developed models versus pretrained models and how they collaborate with other key roles in the corporate ecosystem. By the end of this module, you will have a clear understanding of the various approaches to AI/ML engineering, the specific responsibilities associated with different types of models, and the collaborative dynamics within a corporate setting. This knowledge will empower you to navigate and contribute effectively to AI/ML projects in a business environment.

What's included

5 videos16 readings7 assignments1 peer review

Instructor

 Microsoft
Microsoft
196 Courses1,075,187 learners

Offered by

Microsoft

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