No-Code AI Web Development (For All)

The AI SCHOOL and STTAR invite you to join ONE WEEK Online Certificate program on No-Code AI Web Development

No-Code AI Web Development for Beginners and Experts to Lead in the Age of AI

Online Mode

Skill Level

Duration

Certificate

Learn through live sessions where you design and launch real websites and web apps using no-code tools guided by industry experts.

Ideal for beginners, designers, entrepreneurs, and anyone who wants to build professional websites and AI-powered web apps without coding.

Receive a certificate that validates your skills in no-code web development and AI-powered application building.

Receive a Certificate of Completion to recognize your achievement and boost your academic, professional, or teaching credentials.

Cloud Computing Fundamentals & Platform Overview
Module 1

Understand core cloud concepts including IaaS, PaaS, and SaaS and when to use each model.
Compare AWS, Azure, and GCP across pricing, services, global regions, and availability zones.
Set up cloud accounts, navigate consoles, configure billing alerts, and apply free-tier best practices.

Compute Services & Scalable Infrastructure
Module 2

Launch and configure EC2 instances and Azure Virtual Machines with the right instance types for your workload.
Implement auto-scaling policies and load balancers to handle traffic spikes without downtime.
Deploy serverless functions using AWS Lambda and Azure Functions with event-driven triggers and API Gateway integration.

Cloud Storage & Database Solutions
Module 3

Store and manage files at scale using S3 and Azure Blob Storage with lifecycle policies and access controls.
Set up relational databases (RDS, Azure SQL) and NoSQL options (DynamoDB, Cosmos DB) for different data needs.
Design backup strategies, enable point-in-time recovery, and implement multi-region data replication

Cloud Networking & Security Fundamentals
Module 4

Design Virtual Private Clouds (VPCs) with subnets, route tables, internet gateways, and NAT configurations.
Configure security groups, network ACLs, and IP addressing schemes to control traffic flow securely.
Implement IAM roles, policies, and encryption standards to meet compliance and cloud security best practices.

Deploying AI Models on Cloud Platforms
Module 5

Use SageMaker and Azure Machine Learning to host, version, and serve trained AI models as live endpoints.
Configure inference pipelines, auto-scaling for model serving, and real-time monitoring of model performance.
Integrate deployed model APIs into web apps, chatbots, and business workflows using REST and SDK calls.

Containerisation, Kubernetes & CI/CD Pipelines
Module 6

Set up CloudWatch and Azure Monitor dashboards, log streams, and automated alerts for your cloud resources.
Analyse logs to detect anomalies, trace performance bottlenecks, and ensure uptime for AI workloads.
Reduce spend using resource tagging, reserved and spot instances, right-sizing, and cloud cost monitoring tools.