Language: English
Created by: Vivian Aranha
Rate: 4.4 / 26 ratings
Enroll: 6,237Â students
What you’ll learn
- 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.
Requirements
- 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.
Description
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.
Who this course is for:
- Cloud Professionals Seeking to Expand into AI/ML: Cloud engineers, architects, and developers who are familiar with AWS and want to build a foundation in AI and machine learning technologies using AWS services.
- AI and Machine Learning Enthusiasts: Individuals interested in learning the fundamentals of AI and machine learning, and how to apply these technologies in real-world scenarios using AWS.
- Aspiring Data Scientists and ML Engineers: Beginner data scientists and machine learning engineers looking to gain hands-on experience with AWS AI services, such as Amazon SageMaker, and learn how to build, deploy, and manage AI models on the cloud.
- Business Analysts and Decision Makers: Professionals who want to understand the capabilities of AI and ML on AWS in order to make informed decisions, manage AI projects, and leverage AI technologies to solve business problems.
- Students Preparing for AWS AI Certification: Anyone preparing for the AWS Certified AI Practitioner exam who needs structured learning materials, practice labs, and exam preparation resources to ensure success.
- Tech Professionals Looking to Upskill: IT professionals, developers, and cloud practitioners who want to enhance their career prospects by gaining AI and machine learning skills in a cloud environment.
