AI with Cloud Computing and Azure

Categories: AI Courses
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About Course

Course Description

This program introduces learners to Artificial Intelligence (AI) concepts and how they are implemented in the Microsoft Azure Cloud environment. Participants will explore AI fundamentals, Azure services for AI/ML, data handling, and real-world applications such as vision, language, and predictive analytics. Through hands-on labs, they will build intelligent solutions on Azure, making this course suitable for students, professionals, and educators preparing to integrate AI + Cloud Computing into their careers or classrooms.

Learning Objectives

By the end of this program, learners will:

  • Understand AI concepts: machine learning, deep learning, NLP, computer vision.
  • Explore cloud computing basics and how Azure supports AI workloads.
  • Get hands-on with Azure AI Services: Vision, Language, Speech, and Decision APIs.
  • Work with Azure Machine Learning Studio for no-code ML experiments.
  • Understand data handling and responsible AI in the cloud.
  • Build and deploy simple AI-driven cloud applications.
  • Identify career and teaching pathways in AI + Cloud.

Target Audience

  • School Students (Grades 9–12): Exposure to AI and cloud for STEM careers.
  • College Students / Freshers: Hands-on skills to build projects for jobs and internships.
  • Working Professionals: Upskilling in AI/ML and cloud computing.
  • Educators: Tools and methods for teaching AI + Cloud in classrooms.
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Course Content

Module 1: Introduction to AI & Cloud Computing
Content to be covered: What is AI? Narrow AI vs General AI, Basics of Cloud Computing (IaaS, PaaS, SaaS), Azure Overview – Regions, Resource Groups, Portal, Hands-on: Create a free Azure account and explore the portal.

  • Online Live Class: 2 Hours
  • Practice/ Doubt: 30 Minutes

Module 2: AI Fundamentals & Azure AI Services Overview
Content to be covered: AI domains: Vision, Language, Speech, Decision, Machine Learning vs Deep Learning vs Generative AI, Azure Cognitive Services overview, Hands-on: Call a Cognitive Services API using the portal.

Module 3: Azure Vision Services
Content to be shared: Image recognition, object detection, facial recognition basics, Use cases in security, healthcare, retail, Hands-on: Build an image classifier with Azure Vision API.

Module 4: Azure Language & Speech Services
Content to be covered: Text analytics, sentiment analysis, summarization, Speech-to-text and text-to-speech services, Hands-on: Analyze customer reviews with Text Analytics API, Hands-on: Build a simple speech-to-text app.

Module 5: Azure Decision & Conversational AI
Content to be covered: Decision services: Personalizer & anomaly detection, Conversational AI basics with Azure Bot Service, Hands-on: Build a chatbot using Azure Bot Framework + Language Studio.

Module 6: Azure Machine Learning Studio
Content to be covered: Introduction to ML workflows (data → model → evaluation → deployment), No-code ML experiments with Azure ML Studio, Build and deploy a predictive ML model (student marks prediction / sales forecast).

Module 7: Responsible AI & Security in the Cloud
Content to be covered: Microsoft’s Responsible AI Principles, Ethical use of AI, bias, and fairness, Data privacy, compliance, and governance in Azure, Case study: AI in education & healthcare.

Module 8: Projects, Presentations & Career Pathways
Content to be covered: Capstone Project: Build a real-world AI solution using Azure (options: chatbot, image classifier, sentiment analyzer), Group project presentations & demos, Career guidance: Jobs, certifications (AI-900, DP-900, AZ-900), Educator module: Teaching AI + Cloud concepts to students.

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+91 9818199613

3/11, Professors Colony, Dhola Bhata Colony, Ajmer, Rajasthan 305001

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