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دسته بندی دوره ها

AWS Certified AI Practitioner (AIF-C01) – 2025

سرفصل های دوره

01 Everything You Need to Know about the AWS Certified AI Practitioner Exam
  • 001 Everything You Need to Know about the AWS Certified AI Practitioner Exam

  • 02 Introducing Basic AI and ML Concepts
  • 001 Introducing Basic AI and ML Concepts
  • 001 Introducing Basic AI and ML Concepts - Slides.pdf
  • 002 How Do Machines Learn
  • 003 Different Ways Machines Learn
  • 004 Types of Data in AI Models
  • 005 Exam Tips

  • 03 The Machine Learning Pipeline
  • 001 Exploring the Machine Learning Pipeline
  • 001 The Machine Learning Pipeline - Slides.pdf
  • 002 What Is Feature Engineering
  • 003 Hyperparameters vs. Parameters
  • 004 Metrics for Classification Models
  • 005 Metrics for Regression Models
  • 006 Fundamentals of ML Operations
  • 007 Exam Tips

  • 04 AWS Managed AIML Services and Applications
  • 001 AWS Managed AIML Services and Applications - Slides.pdf
  • 001 Introducing AWS AIML Services
  • 002 Vision Amazon Rekognition
  • 003 Vision Amazon Textract
  • 004 Language Amazon Comprehend
  • 005 Speech Amazon Polly
  • 006 Speech Amazon Transcribe
  • 007 Chatbots Amazon Lex
  • 008 Forecasting Amazon Forecast
  • 009 Personal Assistants Amazon Kendra
  • 010 Recommendations Amazon Personalize
  • 011 Exam Tips

  • 05 Unpacking Amazon SageMaker
  • 001 Introducing Amazon SageMaker
  • 001 Unpacking Amazon SageMaker - Slides.pdf
  • 002 Amazon SageMaker Data Wrangler
  • 003 Amazon SageMaker Feature Store
  • 004 Demo Amazon SageMaker Console Walkthrough
  • 005 Amazon SageMaker Deployments
  • 006 Exam Tips

  • 06 Exam Question Review
  • 001 Basic AI Concepts and Terminologies
  • 001 Exam Question Review - Slides.pdf
  • 002 The Machine Learning Pipeline
  • 003 AWS Managed AIML Services and Applications
  • 004 Unpacking Amazon SageMaker

  • 07 Generative AI Concepts
  • 001 Generative AI Concepts - Slides.pdf
  • 001 Tokens and Chunking
  • 002 Embeddings and Vectors
  • 003 Transformer-based LLMs
  • 004 Different Generative AI Models
  • 005 Prompt Engineering
  • 006 Foundation Model Lifecycle
  • 007 Generative AI Concepts Review

  • 08 Use Cases for Generative AI
  • 001 Generative AI Use Cases
  • 001 Use Cases for Generative AI - Slides.pdf
  • 002 Advantages of Generative AI
  • 003 Limitations and Challenges
  • 004 Model Selection Factors
  • 005 Business Metrics and Value
  • 006 Generative AI Use Cases Exam Tips

  • 09 Generative AI in AWS
  • 001 Generative AI in AWS
  • 001 Generative AI in AWS - Slides.pdf
  • 002 Advantages of AWS Generative AI Services
  • 003 Cost Tradeoffs of AWS Generative AI Services
  • 004 AWS Generative AI Services Review

  • 10 Exam Question Review
  • 001 Exam Question Review - Slides.pdf
  • 001 Generative AI Concepts
  • 002 Disadvantages of Generative AI
  • 003 AWS Generative AI Services
  • 004 Cost Tradeoffs in AWS Generative AI Services

  • 11 Design Considerations for Foundation Model Applications
  • 001 Design Considerations for Foundation Model Applications - Slides.pdf
  • 001 Selecting Foundation Models
  • 002 Inference Parameters
  • 003 Retrieval-augmented Generation (RAG)
  • 004 Vector Storage Solutions on AWS
  • 005 Cost Tradeoffs for Customization
  • 006 Agents for Multi-step Tasks
  • 007 Exam Tips

  • 12 Prompt Engineering Techniques
  • 001 Fundamentals of Prompt Engineering
  • 001 Prompt Engineering Techniques - Slides.pdf
  • 002 Prompt Engineering Techniques
  • 003 Benefits and Best Practices
  • 004 Risks and Limitations of Prompt Engineering
  • 005 Exam Tips

  • 13 Training and Fine-tuning Foundation Models
  • 001 Key Elements of Training Foundation Models
  • 001 Training and Fine-tuning Foundation Models - Slides.pdf
  • 002 Methods for Fine-tuning Foundation Models
  • 003 Preparing Data to Fine-tune a Foundation Model
  • 004 Exam Tips
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    شناسه: 44789
    حجم: 4060 مگابایت
    مدت زمان: 232 دقیقه
    تاریخ انتشار: ۱۳ دی ۱۴۰۴
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