AI+ Cloud™
AT-110
Transform Cloud Computing with Cutting-Edge AI integration- Cloud-AI Fusion: Learn to integrate AI into scalable cloud environments
- Advanced Infrastructure: Master CI/CD, cloud AI models, and deployment strategies
- Capstone Project: Gain hands-on experience with real-world applications
- Future-Ready Skills: Prepares professionals to lead AI-powered cloud innovation
Why This Certification Matters
At a Glance: Course + Exam Overview
- Instructor-Led: 5 days (live or virtual)
- Self-Paced: 40 hours of content
Job Roles & Industry Outlook
User Experience Engineer
Design and build engaging, intuitive, and responsive digital interfaces that bring ideas to life and enhance user journeys.
AI Systems Engineer
Design and optimize data pipelines, warehouses, and systems to enable AI-driven analytics and applications.
Industry Growth: AI+ Cloud™
- Leverage AI for Smarter Leadership Decisions: Learn how to harness AI tools to streamline operations, enhance strategic planning, and drive performance.
- Enhance AI Integration Across the Organization: Use AI to accelerate the integration of AI-driven solutions, automating processe.
- Stay Ahead in AI-Driven Innovation: As demand for AI expertise rises, Chief AI Officers with advanced AI knowledge are highly sought after to spearhead AI.
- Boost Strategic Decision-Making with AI Analytics: Master AI models to analyze business data, predict outcomes, and enable more informed, real-time decisions.
- Advance Your Career in AI Leadership: With AI reshaping industries, this certification equips you with the skills needed to lead AI initiatives.
Who Should Enroll?
- Cloud Professionals: Enhance your cloud management skills by integrating AI to optimize cloud performance, improve resource utilization.
- Cloud Architects & Engineers: Learn to leverage AI to design scalable cloud infrastructures, automate cloud provisioning, and enhance security.
- IT Infrastructure Managers: Use AI to optimize cloud deployment, automate system management, and improve cloud security and disaster recovery planning.
- Business Leaders: Drive innovation in your organization by adopting AI in cloud technologies to enhance scalability, reduce costs, and optimize cloud solutions.
- Students & Fresh Graduates: Gain a competitive edge in the cloud computing field by mastering AI tools and techniques that are revolutionizing cloud infrastructure.
What You'll Learn
- Course Introduction Preview
- 1.1 Introduction to AI and Its Application
- 1.2 Overview of Cloud Computing and Its Benefits
- 1.3 Benefits and Challenges of AI-Cloud Integration
- 2.1 Basic Concepts and Principles of AI
- 2.2 Machine Learning and Its Applications
- 2.3 Overview of Common AI Algorithms
- 2.4 Introduction to Python Programming for AI
- 3.1 Cloud Service Models
- 3.2 Cloud Deployment Models
- 3.3 Key Cloud Providers and Offerings (AWS, Azure, Google Cloud)
- 4.1 Integration of AI Services in Cloud Platform
- 4.2 Working with Pre-built Machine Learning Models
- 4.3 Introduction to Cloud-based AI tools
- 5.1 Building and Training Machine Learning Models
- 5.2 Model Optimization and Evaluation
- 5.3 Collaborative AI Development in a Cloud Environment
- 6.1 Setting Up and Configuring Cloud Resources
- 6.2 Scalability and Performance Considerations
- 6.3 Data Storage and Management in the Cloud
- 7.1 Strategies for Deploying AI Models in the Cloud
- 7.2 Integration of AI Solutions with Existing Cloud-Based Applications
- 7.3 API Usage and Considerations
- 8.1 Introduction to Future Trends
- 8.2 AI Trends Impacting Cloud Integration
- 9.1 Applying AI and Cloud Concepts to Solve a Real-world Problem
- 1. Understanding AI Agents
- 2. Case Studies
- 3. Hands-On Practice with AI Agents
Tools You'll Explore
TensorFlow
SHAP (SHapley Additive exPlanations)
Amazon S3
AWS SageMaker
Prerequisites
- Key concepts in both AI, Fundamental understanding of computer science, Familiarity with cloud computing platforms like AWS, Azure, or GCP
Exam Details
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via AI proctored exam platform (flexible scheduling)
Exam Blueprint
- Module 1: Fundamentals of Artificial Intelligence (AI) and Cloud - 10%
- Module 2: Introduction to Artificial Intelligence - 10%
- Module 3: Fundamentals of Cloud Computing - 10%
- Module 4: AI Services in the Cloud - 10%
- Module 5: AI Model Development in the Cloud - 10%
- Module 6: Cloud Infrastructure for AI - 10%
- Module 7: Deployment and Integration - 10%
- Module 8: Future Trends in AI+ Cloud Integration - 10%
- Module 9: Capstone Project - 10%
- Optional Module: AI Agents for Cloud Computing - 10%
Choose the Format That Fits Your Schedule
What's Included (One-Year Subscription + All Updates):
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Access for Tablet & Phone
Frequently Asked Questions
The course includes a mix of theoretical knowledge and practical applications, culminating in an interactive capstone project. This structure ensures that participants gain both conceptual understanding and hands-on experience.
This course is ideal for developers, IT professionals, and anyone with a foundational understanding of AI and cloud computing who wants to enhance their skills in integrating AI with cloud platforms like AWS, Azure, or Google Cloud.
Participants will learn to develop, deploy, and manage AI models on leading cloud platforms. Skills include optimizing AI model performance, ensuring security, meeting compliance standards, and applying AI and cloud concepts to solve real-world problems.
This certification enhances your professional profile by demonstrating proficiency in integrating AI with cloud computing. It equips you with in-demand skills, giving you a competitive edge in the job market and opening doors to lucrative career opportunities.
The certification includes an interactive capstone project where participants apply their knowledge to design and implement AI solutions within cloud environments. This project is designed to simulate real-world scenarios and challenges.