After completing the AWS Machine Learning path you’ll have the core skills that you’ll need to design and deploy machine learning solutions on AWS. You’ll start by learning the basics of how AWS works, what its foundational services are and how they fit together. From there you’ll begin to specialise by gaining a fundamental understanding of how machine learning works as well as, Python, the programming language that you’ll primarily be using. Next, you’ll build the skills to build and manage the underlying infrastructure and environment that your machine learning workloads will run on, culminating in sitting one of the most valuable AWS certification exams, the Certified Solutions Architect - Associate. You’ll crown it off by going deeper into machine learning tools like Jupyter Notebooks and by preparing for the Machine Learning Specialty certification. These paths are flexible so you can skip what you know and start at the appropriate level, whether you’re a total novice or looking to take your skills to the next level. And as with all ACG learning, there is a major focus on practical learning through hands-on labs. This path includes six certifications: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect - Associate, AWS Certified Machine Learning - Specialty, AWS Certified Database - Specialty, AWS Certified Solutions Architect - Professional, AWS Certified Data Analytics - Specialty
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