AI Cloud Engineer (For All)

"Turn AI Ideas into Cloud-Powered Solutions. "

The AI SCHOOL and STTAR invite you to join ONE WEEK Online Certificate program on AI Cloud Engineer

AI Cloud Engineer for Beginners and Experts to Lead in the Age of AI

Online Mode

Skill Level

Duration

Certificate

Learn through live instructor-led sessions where you set up cloud environments, deploy real AI models, and build production-ready infrastructure with hands-on expert guidance.

Perfect for anyone – students, IT professionals, developers, and business owners – who wants to understand and use cloud platforms to host and scale AI-powered systems.

120 hours of learning covering cloud fundamentals, compute, storage, networking, AI deployment, containers, security, CI/CD, and cost optimisation

Get a certificate to show your skills in architect, deploy, and manage AI workloads on leading cloud platforms like AWS, Azure, and GCP.

Transform Ideas into AI Solutions with AI Cloud Engineer

Chatbot Foundations & Conversational AII
Module 1

Understand the difference between rule-based and AI chatbots and when to use each one.
Learn how AI understands human language – intent recognition, entity extraction, and dialog management.
Map real user conversations and design flows that feel natural, helpful, and easy to follow.

Dialogflow & Microsoft Bot Framework
Module 2

Build smart chatbots in Dialogflow using intents, entities, contexts, and fulfillment webhooks.
Use Microsoft Bot Composer to design adaptive dialogs and generate dynamic language responses.
Connect your bots to live channels and test them with real user inputs from day one.

Rasa Open Source AI Chatbots
Module 3

Train a custom Rasa NLU model to understand your users’ language accurately and reliably.
Build conversation flows using stories, rules, actions, and slots for complex multi-turn dialogs.
Run and test your own fully local AI chatbot that you own, control, and can customise completely.

LangChain & RAG Chatbots
Module 4

Use LangChain conversation chains and memory types to build bots that remember user context.
Upload your own documents and connect a vector store so your chatbot answers from your data.
Build a RAG chatbot that retrieves the right information and delivers accurate, grounded responses.

Smart Conversations Sentiment, Personalisation & Repair
Module 5

Detect user emotions in real time and adapt your bot’s tone and responses automatically.
Build user profiles so your chatbot personalises responses based on history and preferences.
Handle errors and misunderstandings gracefully so conversations always stay on track.

Deploy, Optimise & Scale
Module 6

Launch your chatbot on WhatsApp Business, Telegram, Slack, Teams, and your own website.
Track conversation metrics, user feedback, and run A/B tests to improve performance continuously.
Apply ethics and safety rules – detect bias, moderate content, and protect user privacy at scale.

Tools You Master

Meet Your Mentors

Key Outcomes

Deploy and manage cloud infrastructure across AWS, Azure, and GCP with confidence.
Host and scale AI models in production using managed ML services and containerised workloads.
Secure cloud environments using IAM, VPCs, encryption, and compliance frameworks.
Automate deployments with CI/CD pipelines and monitor systems using cloud-native observability tools.

Still wondering if this AI Cloud Engineer for you?

If you want to build, deploy, and scale AI systems in the cloud without needing years of DevOps experience, this course is built for you.

Get Certified by the Best in AI Skilling and Teacher Training

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Frequently Asked Questions (FAQs)

1. Do I need prior cloud or coding experience to join this course?

No prior experience is needed. The course starts from the basics and builds up step-by-step so you can follow along even if you have never used a cloud platform before.

2. Which cloud platforms will I be working with?

You will get hands-on exposure to AWS, Microsoft Azure, and Google Cloud Platform through guided labs covering compute, storage, networking, and AI deployment on each.

3. Will I actually deploy a real AI model during the course?

Yes. You will deploy trained AI models as live endpoints using SageMaker and Azure ML so real applications can call them via API not just theory, but production-ready deployments

4. What is the difference between this course and a general cloud certification prep?

This course focuses specifically on AI workloads in the cloud deploying models, building pipelines, and integrating cloud services around AI use cases. It is practical and role-specific, not just exam-focused.

5. Who is this course best suited for?

Anyone who wants to go from cloud beginner to someone who can independently deploy AI systems in production students, professionals, developers, and entrepreneurs all benefit equally from this course.

India's only school where startup Leaders teach AI skills.