Cloud Computing With Applied AI
Unlock the power of Cloud Computing and Applied AI with our comprehensive online program. Learn how to design scalable cloud systems, integrate AI models, and deploy intelligent solutions across industries like healthcare, finance, and e-commerce. Through hands-on projects, live case studies, and practical tool training, you’ll master both cloud platforms and AI applications. This course takes you from the fundamentals of cloud to advanced AI-driven architectures, preparing you to stand out in the fastest-growing tech field.
6 Month
.Duration
Virtual Live
Classes
100% Job
Assurance
Languages
English | Hindi
Get Certifications From
Course Highlights
Live Expert-Led Training
Learn directly from cloud & AI professionals
Hands-On Projects
Work on AWS, Azure & Google Cloud with real datasets
Cloud + AI Fusion
Build & deploy intelligent applications on the cloud
Career Support
Resume building, mock interviews & placement guidance
Master these Tools
Skills Covered
Cloud Security & Compliance
.
Serverless Computing & Microservices
.
API Integration & Cloud Automation
.
Containerization & Orchestration
.
AI Model Deployment on Cloud
.
Cloud Infrastructure Management
.
Course Curriculum
The Cloud Computing with Applied AI Mastery Course covers everything from cloud platforms and virtualization to AI-powered services, big data, and serverless computing. You’ll master Docker, Kubernetes, and MLOps for deploying AI at scale. With hands-on projects and real-world case studies, you’ll gain the skills to design and manage intelligent cloud solutions for a successful career in Cloud & AI.
Module 1: Foundations of Cloud Computing
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- Cloud computing basics: IaaS, PaaS, SaaS
- Public, private & hybrid cloud models
- Cloud service providers overview (AWS, Azure, GCP)
- Cloud data centers & architecture
- Cloud billing & cost optimization basics
Module 2: Introduction to Artificial Intelligence & Machine Learning
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- AI, ML, and DL: key differences
- Types of machine learning (supervised, unsupervised, reinforcement)
- Core ML algorithms: regression, classification, clustering
- Deep learning basics (ANN, CNN, RNN)
- Popular frameworks: TensorFlow, PyTorch, Scikit-learn
Module 3: Cloud Infrastructure & Virtualization
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- Virtual machines & cloud instances
- Networking & storage fundamentals in cloud
- Load balancing & auto-scaling
- Virtualization vs containerization
- Docker fundamentals (images, containers, volumes)
- Kubernetes orchestration basics
Module 4: Data Engineering & Big Data on Cloud
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- Data lakes & warehouses
- Hadoop ecosystem (HDFS, MapReduce, Hive)
- Apache Spark for big data processing
- Cloud storage options (S3, Blob, BigQuery)
- ETL pipelines on cloud platforms
- Stream processing with Kafka
Module 5: Cloud-Native AI Services
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- AWS SageMaker, Azure ML Studio, GCP AI Platform
- Using pre-trained AI APIs (Vision, Speech, NLP)
- Model training & hyperparameter tuning on cloud
- Deploying ML models via endpoints
- AI model monitoring in cloud
Module 6: Serverless Computing & Automation
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- Serverless architecture overview
- AWS Lambda, Azure Functions, GCP Functions
- Event-driven workflows with serverless triggers
- Backend-as-a-Service (Firebase, AWS Amplify)
- Serverless with containers (Knative, Fargate)
Module 7: MLOps & Continuous Deployment
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MLOps pipeline lifecycle
- CI/CD for ML projects
- Model versioning & model registry
- Continuous monitoring & retraining
- Tools: MLflow, Kubeflow, TFX
Module 8: Cloud Security & Compliance
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- Shared responsibility model in cloud security
- Identity & Access Management (IAM) policies
- Network security: Firewalls, VPNs, WAF
- Encryption at rest & in transit
- Compliance frameworks (GDPR, HIPAA, SOC 2)
- Securing AI pipelines & data in cloud
Module 9: Cloud Automation & DevOps Tools
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- Infrastructure as Code (Terraform, Ansible, CloudFormation)
- Monitoring & observability tools (CloudWatch, Prometheus, Grafana)
- CI/CD with Jenkins & GitHub Actions
- Automated testing & logging
- Cloud cost optimization with automation
Module 10: Applied AI on Cloud Use-Cases
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- Healthcare: AI-driven diagnosis
- Finance: fraud detection & credit scoring
- Retail: recommendation systems, demand forecasting
- E-commerce: AI-powered chatbots, personalization
- Manufacturing: predictive maintenance
Module 11: Advanced Cloud Architectures
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- Multi-cloud vs hybrid cloud strategies
- Microservices & containerized architecture
- Cloud cost optimization techniques
- Edge computing & AI at the edge
- Disaster recovery strategies
Module 12: Capstone Project
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- End-to-end cloud + AI solution design
- Real-world datasets & cloud deployment
- ML pipeline with MLOps integration
- Project presentation & demo
- Portfolio showcase
Module 13: Job-Ready Interview Preparation
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- Resume building for Cloud & AI roles
- Mock interviews (Technical + HR)
- Certification prep (AWS, Azure, GCP)
- Top 100 interview questions & answers
- Career guidance & networking strategies
About Cloud Computing With Applied AI Course
Our Cloud Computing with AI Integration Program is designed to equip you with the skills needed to design, deploy, and scale intelligent cloud solutions. You’ll master cloud platforms (AWS, Azure, GCP), virtualization, containerization, big data processing, and AI-powered cloud services—empowering you to build real-world applications, accelerate your career, or launch your freelancing journey.
✅ Practical, Project-Based Learning
Through hands-on labs, live projects, and real-world case studies, you’ll gain practical experience in cloud deployment, serverless computing, and MLOps. You’ll graduate with a strong portfolio demonstrating your ability to build and manage AI-driven cloud systems, making you job-ready for high-demand roles.
✅ Expert Mentorship & Career Support
Learn directly from industry experts, get personalized career guidance, prepare for certifications (AWS, Azure, GCP), and ace technical interviews. Plus, earn a recognized certification to stand out to employers and clients in the competitive Cloud & AI space.
✅ For Everyone Ready to Master Cloud + AI
Whether you’re a student, IT professional, or entrepreneur, this program will help you master cloud infrastructure, AI services, automation, and scalable deployments—preparing you for the future of intelligent cloud solutions.
👥 Who Should Enroll?
✔ Students & graduates aiming to start a career in Cloud, DevOps, or AI-driven roles
✔ Working professionals looking to upskill or switch to Cloud + AI careers
✔ Entrepreneurs & tech founders wanting to integrate AI into cloud-based products & servicesv
Career Opportunities After the Course
List potential roles students can pursue after completing the course, such as
- Cloud Engineer
- MLOps Engineer
- Cloud Solutions Architect
- DevOps Engineer (Cloud & AI
- Cloud Security Specialist
- Freelance Cloud & AI Consultant
- AI/ML Cloud Engineer
With 100% job assurance, our course prepares you for a lucrative career in Cloud Computing and AI Integration.
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Live Virtual Classes
₹17999
EMI Options Available
Batch Timings
📅 Weekdays: 7 PM – 9 PM
📅 Weekends: 10 AM – 12 PM.
⭐ Intensive interview preparation.
⭐ Real-life interview case study.
Total Course Duration : 6 Months
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