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Every course includes exam-aligned domain topics, hands-on lab sheets, practice quizzes, and dedicated instructor support. Click any course to view its full syllabus.

Showing 21 Courses

AWS Certified Cloud Practitioner (CLF-C02)

Build a strong foundational understanding of the AWS Cloud platform, global infrastructure, and security controls.

Duration: 15 Hours
Target: Business executives, sales managers, project leads, student beginners, and those new to cloud computing.
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AWS Certified AI Practitioner (AIF-C01)

Master foundational concepts of Artificial Intelligence, Machine Learning, and Generative AI on the AWS Cloud.

Duration: 20 Hours
Target: Business professionals, software developers, project managers, and beginners targeting cloud AI certifications.
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AWS Certified Solutions Architect - Associate (SAA-C03)

Design resilient, high-performing, secure, and cost-optimized architectures on Amazon Web Services.

Duration: 40 Hours
Target: IT professionals, systems administrators, developers, and aspiring solutions architects.
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AWS Certified Solutions Architect - Professional (SAP-C02)

Deliver advanced solutions architecture engineering for complex, enterprise-scale migrations and workloads on AWS.

Duration: 45 Hours
Target: Senior solutions architects, cloud consultants, and lead infrastructure engineers.
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AWS Certified Developer - Associate (DVA-C02)

Write, deploy, debug, and optimize applications built on Amazon Web Services serverless and container systems.

Duration: 35 Hours
Target: Software developers, engineers, and DevOps practitioners aiming to design code for AWS environments.
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AWS Certified DevOps Engineer - Professional (DOP-C02)

Automate delivery, orchestrate cloud builds, monitor operations, and secure deployment pipelines on AWS.

Duration: 40 Hours
Target: DevOps engineers, systems administrators, and release managers.
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AWS Certified Data Engineer - Associate (DEA-C01)

Design, build, monitor, and optimize scalable data pipelines, data warehouses, and analytics storage on AWS.

Duration: 30 Hours
Target: Data engineers, database administrators, and analytics professionals looking to specialize in AWS big data solutions.
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AWS Certified Machine Learning Engineer - Associate (MLA-C01)

Build, train, deploy, and scale machine learning models and ML pipelines using Amazon SageMaker and AI services.

Duration: 32 Hours
Target: ML engineers, data scientists, and developers wanting to deploy enterprise-grade AI models on AWS.
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AWS Certified Security - Specialty (SCS-C02)

Master advanced data protection, incident response, network security, and access authorization on AWS.

Duration: 30 Hours
Target: Security engineers, security architects, systems engineers, and cloud security analysts.
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AI Fundamentals

Learn core concepts of Artificial Intelligence, Machine Learning types, Neural Networks, and modern use cases.

Duration: 10 Hours
Target: Business professionals, product managers, and beginners wanting to understand the AI revolution.
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Generative AI for Cloud Professionals

Integrate LLMs, prompt pipelines, vector databases, and Retrieval-Augmented Generation (RAG) into cloud applications.

Duration: 18 Hours
Target: Developers, cloud engineers, and technical leads looking to build software powered by generative AI.
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Amazon Bedrock Basics

Explore serverless AWS AI models, security compliance, custom models, and agent workflows using Bedrock.

Duration: 12 Hours
Target: Solutions architects, cloud developers, and IT directors evaluating AWS AI capabilities.
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AI for Cloud Professionals

Leverage cloud AI APIs and serverless workflows to construct intelligent automations and chatbots.

Duration: 15 Hours
Target: Cloud engineers, systems developers, and operations architects looking to embed AI inside cloud infrastructure workflows.
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Kubernetes and DevOpsBeginner to Intermediate

Kubernetes Fundamentals

Deploy, manage, and scale containerized applications on Kubernetes clusters using pods, deployments, and services.

Duration: 20 Hours
Target: Systems administrators, developers, and DevOps engineers new to container orchestrators.
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DevOps with CI/CD

Automate code compilation, testing, security scans, and cloud deployment pipelines using Git and Jenkins/GitHub Actions.

Duration: 25 Hours
Target: Software developers, systems operators, and QA engineers wanting to learn modern pipeline automation.
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Containers and Cloud Deployment

Package software code with dependencies inside Docker containers and run them on modern cloud environments.

Duration: 15 Hours
Target: Web developers, backend developers, and systems operators.
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Infrastructure as Code Basics

Write, automate, and manage cloud assets using code configuration structures in Terraform and CloudFormation.

Duration: 18 Hours
Target: Systems administrators, software engineers, and cloud beginners who want to automate cloud provisioning.
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GitHub Actions for CI/CD

Build automatic code validation, testing, and continuous cloud deployment pipelines with GitHub workflows.

Duration: 20 Hours
Target: Frontend & backend developers, automation engineers, and release specialists.
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Full StackBeginner

Full Stack Web Development Basics

Create interactive web applications from scratch using HTML5, CSS3, modern JavaScript, and server interfaces.

Duration: 30 Hours
Target: Complete beginners wanting to learn coding, web designers, and aspiring developers.
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Full StackIntermediate

React and Node.js Fundamentals

Build modular web UIs with React 19 and robust backend servers with Express.js and databases.

Duration: 35 Hours
Target: Junior developers and programmers looking to transition to modern React/Node engineering.
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Full StackIntermediate

Cloud Deployment for Web Apps

Secure, monitor, deploy, and scale web applications in the cloud using S3, CloudFront, EC2, and Amplify.

Duration: 20 Hours
Target: Full stack developers wanting to run their applications securely in cloud infrastructures.
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AWS Certification Training

Master Amazon Web Services from foundational practitioner up to professional solutions architect and specialty security domains.

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AI and GenAI Training

Build cutting-edge Artificial Intelligence, Large Language Models, RAG pipelines, and Bedrock applications.

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Kubernetes and DevOps

Master container orchestration, CI/CD pipelines, Terraform Infrastructure as Code, and GitHub Actions.

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Full Stack

Build modern web applications using React, Node.js, Express, MongoDB, and cloud deployment pipelines.

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