Mastering AI on AWS: Training AWS Certified AI Practitioner
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This comprehensive course, “Mastering AI on AWS: Training AWS Certified AI Practitioner” is designed to equip you with the knowledge and skills to excel in AI and machine learning using AWS services. Whether you’re a cloud professional, developer, or AI enthusiast, this course will guide you through the fundamentals of AI and machine learning while providing hands-on experience with cutting-edge AWS AI services like Amazon SageMaker, Rekognition, Comprehend, Polly, and more.
Starting with foundational concepts of AI and machine learning, you’ll progress through practical labs, working with real-world applications such as image and video recognition, natural language processing, and recommendation systems. The course will also cover security best practices, responsible AI, and preparing for the AWS Certified AI Practitioner exam. By the end, you’ll be ready to build, deploy, and monitor AI applications on AWS and confidently pass the certification exam.
Through engaging lessons, hands-on projects, and practical exercises, this course ensures you develop both theoretical knowledge and practical skills to succeed in the growing field of AI and machine learning.
What you’ll learn:
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Fundamental concepts of AI, machine learning, and AWS AI services.
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How to build and deploy AI applications using Amazon SageMaker, Rekognition, Comprehend, Polly, and more.
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Best practices for securing AI and machine learning workflows on AWS.
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How to prepare for and pass the AWS Certified AI Practitioner exam.
Who this course is for:
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Cloud professionals wanting to expand into AI/ML.
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AI/ML enthusiasts looking to gain practical skills using AWS services.
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Aspiring data scientists and developers seeking to implement real-world AI solutions.
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Students and professionals preparing for the AWS Certified AI Practitioner exam.
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1What will we CoverVideo lesson
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2Overview of AWS AI and ML ServicesVideo lesson
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3Importance of AI in Cloud ComputingVideo lesson
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4Introduction to AWS Certified AI Practitioner ExamVideo lesson
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5Key Concepts: AI, Machine Learning, and Deep LearningVideo lesson
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6Prerequisites and Exam Preparation StrategyVideo lesson
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7What will we coverVideo lesson
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8Supervised vs Unsupervised LearningVideo lesson
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9Key Machine Learning AlgorithmsVideo lesson
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10Training vs Inference in Machine LearningVideo lesson
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11Introduction to Model Evaluation and PerformanceVideo lesson
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12Hands-On Lab: Training a Simple Machine Learning ModelVideo lesson
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13What will we coverVideo lesson
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14Amazon SageMaker OverviewVideo lesson
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15AWS AI Services for Vision, Speech, Language, and RecommendationsVideo lesson
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16Introduction to AWS AI Service Use CasesVideo lesson
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17AI and ML Decision-Making Process on AWSVideo lesson
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18Hands-On Lab: Exploring AWS AI ServicesVideo lesson
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19What will we coverVideo lesson
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20Overview of NLP and its ApplicationsVideo lesson
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21Amazon Comprehend: Sentiment Analysis, Entity Recognition, & Language DetectionVideo lesson
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22Amazon Transcribe: Speech-to-Text TranscriptionVideo lesson
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23Amazon Translate: Real-Time Language TranslationVideo lesson
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24Hands-On Lab: Analyzing Text Data with Amazon ComprehendVideo lesson
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35What will we coverVideo lesson
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36Security and Compliance in AWS AI ServicesVideo lesson
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37Data Encryption and Security in Machine Learning WorkflowsVideo lesson
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38Monitoring and Logging in SageMaker and AWS AI ServicesVideo lesson
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39Hands-On Lab: Implementing Security Best Practices for AI ServicesVideo lesson
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45What will we coverVideo lesson
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46AI in Healthcare, Finance, Retail, and ManufacturingVideo lesson
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47Real-World Examples of AWS AI Services in ProductionVideo lesson
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48Case Studies: Successful AI and ML Projects on AWSVideo lesson
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49Group Discussion: Best Practices for AI DeploymentVideo lesson

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