Learners will be able to explain core AI concepts, differentiate machine learning techniques, analyze AWS AI services, apply model training workflows, and evaluate end-to-end AI solutions using real-world examples. This course equips participants with a complete understanding of Artificial Intelligence fundamentals while developing practical cloud skills using AWS tools such as SageMaker, Comprehend, Rekognition, Lex, and Polly.
Master AI & AWS Cloud Skills: Analyze, Build, Deploy
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Master AI & AWS Cloud Skills: Analyze, Build, Deploy
This course is part of AI Technologies, Tools & Cloud Certification Specialization Specialization
Instructor: EDUCBA
Included with
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
7 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Explain core AI and machine learning concepts and differentiate common ML techniques.
Use AWS AI services to build, train, and deploy intelligent applications.
Design end-to-end AI solutions and prepare for the AWS Certified AI Practitioner exam.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
January 2026
Assessments
16 assignments
Taught in English
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This course is part of the AI Technologies, Tools & Cloud Certification Specialization Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 4 modules in this course
This module introduces the fundamental principles of Artificial Intelligence and Machine Learning, covering key concepts such as NLP, Computer Vision, learning paradigms, and essential analytical techniques. Learners develop a strong conceptual foundation to support deeper exploration of AI applications and AWS-based ML workflows.
What's included
9 videos4 assignments
This module explores the AWS AI ecosystem, introducing essential cloud-based AI services such as SageMaker, Comprehend, DeepLens, and foundational implementation patterns. Learners gain hands-on understanding of how AWS accelerates AI development through managed services, automation, and real-world case studies.
What's included
9 videos4 assignments
This module focuses on building conversational, vision-based, and multi-service AI solutions using AWS. Learners gain experience integrating Lex, Polly, Rekognition, and other services to design intelligent, end-to-end cloud applications while exploring foundation models and model engineering best practices.
What's included
7 videos4 assignments
This module covers the complete ML lifecycle, including model training, optimization, evaluation, deployment, ethical AI practices, prompt engineering, and continuous improvement strategies. Learners also prepare for certification through exam-focused insights and advanced scenario-based analysis.
What's included
8 videos4 assignments
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
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Frequently asked questions
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
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