Course Overview
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:
Fundamental concepts of AI, machine learning, and AWS AI services.
How to build and deploy AI applications using Amazon SageMaker, Rekognition, Comprehend, Polly, and more.
Best practices for securing AI and machine learning workflows on AWS.
How to prepare for and pass the AWS Certified AI Practitioner exam.
Who this course is for:
Cloud professionals wanting to expand into AI/ML.
AI/ML enthusiasts looking to gain practical skills using AWS services.
Aspiring data scientists and developers seeking to implement real-world AI solutions.
Students and professionals preparing for the AWS Certified AI Practitioner exam.
FAQ
FAQ area empty
Course curriculum
-
Certificate of Completion
29 Xem trước -
What will we Cover
75 Xem trước -
Overview of AWS AI and ML Services
222 Xem trước -
Importance of AI in Cloud Computing
167 Xem trước -
Introduction to AWS Certified AI Practitioner Exam
152 Xem trước -
Key Concepts: AI, Machine Learning, and Deep Learning
166 Xem trước -
Prerequisites and Exam Preparation Strategy
165
-
What will we cover
73 -
Overview of NLP and its Applications
141 -
Amazon Comprehend: Sentiment Analysis, Entity Recognition, & Language Detection
205 -
Amazon Transcribe: Speech-to-Text Transcription
172 -
Amazon Translate: Real-Time Language Translation
138 -
Hands-On Lab: Analyzing Text Data with Amazon Comprehend
293 -
Designing an NLP Workflow with AWS AI Services
0
-
What will we cover
66 -
Introduction to Computer Vision on AWS
142 -
Amazon Rekognition: Image and Video Analysis
225 -
Amazon Textract: Extracting Text from Documents
187 -
Hands-On Lab: Image and Video Processing with Amazon Rekognition
436 -
Pitching an Automated Visual Inspection Workflow using Amazon Rekognition
0
-
What will we cover
53 -
Amazon Polly: Text-to-Speech Conversion
207 -
Amazon Transcribe: Automatic Speech Recognition
223 -
Building Real-Time Speech Interfaces on AWS
201 -
Hands-On Lab: Building a Voice Interface with Amazon Polly
256 -
Designing a Voice-Powered Customer Service Interface with Amazon Transcribe and Polly
0
-
What will we cover
66 -
Security and Compliance in AWS AI Services
190 -
Data Encryption and Security in Machine Learning Workflows
193 -
Monitoring and Logging in SageMaker and AWS AI Services
198 -
Hands-On Lab: Implementing Security Best Practices for AI Services
887 -
Securing AI Workflows: A SageMaker Deployment Audit
0
Requirment
-
Basic Knowledge of Cloud Computing: Students should have a general understanding of cloud computing concepts and experience using AWS services, such as EC2, S3, or RDS
-
Familiarity with Programming: A basic understanding of programming languages, especially Python, is recommended, as some hands-on labs will involve coding for machine learning and AI tasks.
-
Understanding of Machine Learning Fundamentals (Optional but Beneficial): While the course will cover the basics of machine learning, having prior knowledge of key ML concepts (like algorithms, training, and model evaluation) will be helpful.
-
AWS Account: Students will need an active AWS account to perform hands-on labs and practice with AWS AI and ML services.
Outcomes
-
Understand Key Concepts of AI and Machine Learning on AWS
-
Master AWS AI and Machine Learning Services
-
Build and Deploy AI-Powered Applications on AWS
-
Prepare for the AWS Certified AI Practitioner Exam
0 Student
2 Courses
0 review