AI+ Cloud Computing Course Online | Certification
Length
5 days / 5 weeks
Price
$3499
Days
Mon - Fri
Why Choose This Course
An AI+ Cloud Computing Course trains you to design, deploy, and manage AI solutions using cloud platforms such as AWS, Microsoft Azure, and Google Cloud. It focuses on blending artificial intelligence with cloud computing to build scalable, efficient applications while developing practical skills that are relevant for real‑world projects and professional certification. There is strong demand for skills that combine cloud infrastructure knowledge with practical AI model development and deployment capabilities.
This AI and cloud computing course focuses on the integration of AI technologies with major cloud platforms, covering how machine learning models are built, trained, deployed, and managed in cloud environments. Learners explore the core principles of artificial intelligence, cloud service models, and cloud-native architectures, then progress into applying AI services within cloud ecosystems. The course places emphasis on real-world use cases, helping participants understand how AI workloads are designed to scale, remain secure, and operate efficiently in production.
The AI+ Cloud course from Training Courses Now supports learners who want exam‑focused content and practical skills instead of only theory. It is ideal for professionals looking to upgrade their technical capabilities to match changing industry needs, while staying flexible without locking into a single cloud provider. A course completion certificate is included.
Prerequisites
- A foundational understanding of artificial intelligence concepts
- Basic knowledge of computer science, including programming fundamentals
- Familiarity with cloud computing platforms such as AWS, Microsoft Azure, or Google Cloud
- Basic understanding of mathematics relevant to machine learning
Exam
Candidates can achieve this certification by passing the following exam(s).
This course helps you get ready for the related certification exam, which is included as part of the course. The assessment is taken online and monitored through an AI‑based proctoring system.
- AI+ Cloud Certification Exam (Exam Code: AT-110)
- The exam duration is 90 minutes.
- It includes 50 multiple‑choice and multiple‑response questions.
- You need to score 35 out of 50 (70%) to pass.
Lab guides are available for Azure, AWS, and Google Cloud, so you can choose the platform you prefer. Learners who choose Azure get direct access to Azure labs, while those selecting AWS or GCP can use free accounts to complete the hands‑on labs.
Books
Flexible Delivery Options
- Live virtual online training attend in real-time from anywhere
Skills Gained
- Understanding core artificial intelligence concepts and terminology
- Knowledge of cloud computing service models and architectures
- Ability to design cloud-based AI solutions
- Machine learning model development in cloud environments
- Data preparation and preprocessing for AI workloads
- Using cloud AI services for training and inference
- Deploying AI models using cloud-native tools
- Integrating AI solutions into existing systems
- Managing AI model lifecycle in the cloud
- Applying CI/CD concepts to AI deployments
- Optimising AI workloads for performance and cost
- Understanding cloud infrastructure requirements for AI
- Applying security and compliance considerations to AI systems
- Working with multiple cloud platforms for AI solutions
Who Should Attend?
- Cloud engineers and cloud architects
- Software developers working with AI or data-driven applications
- IT professionals responsible for cloud infrastructure
- Data professionals seeking cloud-based AI skills
- Technical leads involved in AI and cloud solution design
Course Schedule & Pricing
Choose the schedule that fits your life — all options include full course materials & certification support
Full-time immersion for rapid certification readiness.
Balance your career while you upgrade your skills.
Maximum flexibility for busy working professionals.
Outline
- Introduction to artificial intelligence and cloud convergence
- Overview of AI use cases in cloud environments
- Fundamentals of artificial intelligence
- Machine learning concepts and workflows
- Fundamentals of cloud computing
- Cloud service models and deployment models
- Data management for cloud-based AI
- AI services available in cloud platforms
- Building machine learning models in the cloud
- Training and evaluating AI models
- Cloud infrastructure for AI workloads
- Scalable storage and compute for AI
- AI model deployment strategies
- Model versioning and lifecycle management
- CI/CD pipelines for AI applications
- Integrating AI solutions into enterprise systems
- Monitoring and optimising AI workloads
- Security considerations for AI in the cloud
- Governance and compliance in cloud AI
- Cost optimisation for AI solutions
- Future trends in AI and cloud integration
- Capstone-style applied learning and review
Terms & Conditions
Frequently Asked Questions (FAQ's)
What is the AI+ Cloud course about?
Is this course suitable for beginners in AI?
Does this course prepare me for a certification exam?
Yes, the course includes exam-aligned content designed to help learners prepare for the AI+ Cloud certification exam, alongside practical learning.
Does Meta use cloud for AI training?
Yes, Meta uses cloud‑based infrastructure along with its own large data centers to train AI models. Cloud systems help handle massive data, powerful computing needs, and fast experimentation during AI development.
Why is the cloud essential for training large AI models?
The cloud is essential because large AI models need huge computing power, storage, and speed. Cloud platforms provide this on demand, making it easier to train models faster without building expensive physical infrastructure.
How can the cloud support scalable training models in AI?
Cloud platforms allow you to scale up or down whenever needed. You can add more computing resources during training and reduce them afterward, which makes AI training flexible, efficient, and cost‑effective.
How to design hybrid cloud storage for high‑throughput AI training?
Hybrid cloud storage is designed by combining on‑premise storage for sensitive or frequently used data with cloud storage for large datasets. This setup improves speed, balances costs, and ensures smooth data access during high‑performance AI training.
Our Partnership
Reliable certification testing is vital for validating professional skills in today’s tech-driven world. As a Pearson VUE Authorised Centre, we provide a secure environment for globally recognised IT exams. This partnership ensures convenient access to certifications with the highest standards of integrity and accuracy.
Our Accreditations
