Fundamentals of Machine Learning for Software Engineers
Explore machine learning's essentials for software engineers, delve into supervised learning, neural networks, and deep learning, and gain skills to tackle real-world data challenges effectively.
4.6
93 Lessons
15h
Updated 4 weeks ago
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Machine learning is the future for the next generation of software professionals.
This course serves as a guide to machine learning for software engineers. You’ll be introduced to three of the most relevant components of the AI/ML discipline; supervised learning, neural networks, and deep learning. You’ll grasp the differences between traditional programming and machine learning by hands-on development in supervised learning before building out complex distributed applications with neural networks. You’ll go even further by layering networks to create deep learning systems. You’ll work with complex real-world datasets to explore machine behavior from scratch at each phase.
By the end of this course, you’ll have a working knowledge of modern machine learning techniques. Using software engineering, you’ll be prepared to build complex neural networks and wrangle real-world data challenges.
Machine learning is the future for the next generation of software professionals.
This course serves as a guide to machine lear...Show More
WHAT YOU'LL LEARN
Working knowledge of modern machine learning techniques
A strong understanding of neural networks
The ability to program behavior rather than processes in supervised learning systems
Familiarity with complex artificial intelligence and deep learning
The experience of managing real-world datasets with machine learning
Working knowledge of modern machine learning techniques
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TAKEAWAY SKILLS
Learning Roadmap
Certificate of Completion
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