AWS Certified Cloud Practitioner
Validate overall understanding of the AWS Cloud, independent of specific technical roles.
Exam Topics
Cloud concepts
Security and compliance
Core AWS services
Economics of the AWS Cloud
Prerequisites
No formal prerequisites are required. This certification is suitable for beginners with basic IT knowledge.
Our Preparation Approach
Structured Curriculum
Aligned with latest exam objectives and updated for current exam patterns
Hands-On Labs
Practical exercises using real cloud environments and enterprise scenarios
Practice Exams
Mock exams modeled on real questions with detailed answer explanations
Expert Guidance
Learn from a trainer with 16+ active certifications and 98% student pass rate
Frequently Asked Questions
What is the CLF-C02 AWS Certified Cloud Practitioner certification?
Validate overall understanding of the AWS Cloud, independent of specific technical roles.
How long is the CLF-C02 exam?
The CLF-C02 exam duration is 90 minutes. The passing score is 700/1000. The exam fee is $100 USD.
What topics does the CLF-C02 exam cover?
The CLF-C02 exam covers: Cloud concepts; Security and compliance; Core AWS services; Economics of the AWS Cloud.
What are the prerequisites for CLF-C02?
There are no formal prerequisites for this certification. However, foundational knowledge in the domain is recommended.
How long is the CLF-C02 certification valid?
The CLF-C02 certification is valid for 3 years.
Does Gennoor Tech offer CLF-C02 preparation training?
Yes, we offer expert-led CLF-C02 preparation with hands-on labs, practice exams, and personalized guidance. Our trainer holds 16+ active certifications with a 98% student pass rate across all exams.
Other AWS Certifications
AWS Certified AI Practitioner
Validate knowledge of AI, machine learning, and generative AI concepts and use cases on AWS.
AWS Certified Machine Learning Engineer - Associate
Build, deploy, and maintain machine learning solutions in the AWS Cloud for business problems.
AWS Certified Machine Learning - Specialty
Design, implement, deploy, and maintain machine learning solutions for given business problems.
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