- Call: +91-8601686504
- Email: hr@hypertechglobaltechnologies.com
Login /
Instructor: Team HyperTech
Here’s your 9-Month Structured Program version of the course content you provided, clearly broken down month-wise to reflect a comprehensive and progressive learning path:
From zero to job-ready, this 9-month intensive program is designed with a project-driven and hands-on approach to ensure real-world exposure. You’ll master Cloud Platforms (AWS & Azure), DevSecOps tools, Machine Learning with Python, and crack interviews with DSA and problem-solving mastery.
Core Services: EC2, S3, IAM, RDS, EBS
Networking: VPC, Load Balancer, Route 53
Hands-on: Launch and manage services using AWS Console and CLI
Serverless: Lambda, API Gateway, DynamoDB
Monitoring & DevOps Tools: CloudWatch, CodePipeline, CodeDeploy
Project: Host a scalable web app
Certification Prep: AWS Cloud Practitioner / Architect Associate
DevOps Lifecycle Overview
Version Control: Git, GitHub
CI/CD Setup: Jenkins, Maven
Project Management: Jira
Code Quality & Security: SonarQube, SAST/DAST
Containerization & IaC: Docker, Kubernetes, Terraform, Ansible
Real-Time Project: Secure CI/CD Pipeline Deployment
Python Essentials: Numpy, Pandas, Matplotlib
ML Algorithms: Regression, Classification, Clustering
Project: Sentiment Analysis, Stock Prediction
Model Evaluation, Hyperparameter Tuning
Project: End-to-End ML Project
Model Deployment: Flask + AWS/Azure (Optional)
Core Python + OOPs Concepts
Data Structures: Arrays, Strings, Lists
Logic Building & Problem Solving
Advanced Structures: Trees, Graphs, Recursion
Sorting, Searching, Time Complexity
Practice: Leetcode-style challenges
Capstone Projects Across All Tech Stacks
Mock Interviews & Problem Solving
Resume Building & Placement Support
Crack Tech Interviews with Confidence
✅ 4-in-1 Mastery: Cloud + DevSecOps + ML + DSA
✅ Project-Based Learning with Real-Time Deployment
✅ Industry-Grade Tools: Git, Jenkins, Docker, Terraform
✅ Global Certifications Support
Let me know if you want this in brochure or PDF format as well.
0 Reviews
🎓 12-Month Master Program: Cloud, DevOps, DSA, MLOps & GenAI 📍 Phase 1: Foundations (Month 1 – Month 3) Month 1 – Cloud Basics & DSA Foundations Cloud: Intro to Cloud Computing, IaaS/PaaS/SaaS, AWS/Azure/GCP overview DSA: Complexity Analysis, Arrays, Strings, Recursion Hands-on Project: Deploy a static website on AWS S3 + Basic DSA coding challenges Month 2 – DevOps Fundamentals Version Control: Git, GitHub/GitLab workflows CI/CD Basics: Jenkins, GitHub Actions DSA: Searching & Sorting, Linked Lists Hands-on Project: Set up a CI/CD pipeline for a sample app Month 3 – Cloud Core Services + DSA Expansion Cloud: Compute (EC2, VM), Storage (S3, Blob), Networking (VPC) DSA: Stacks, Queues, Hashing Hands-on Project: Build a 3-tier cloud architecture + DSA problem sets 📍 Phase 2: Intermediate (Month 4 – Month 6) Month 4 – DevOps Intermediate + Cloud IAM Cloud: IAM, Security, Monitoring (CloudWatch, Azure Monitor) DevOps: Docker basics, Containerization DSA: Trees (Binary Trees, BST) Hands-on Project: Dockerize a web app + IAM role-based access project Month 5 – Kubernetes & IaC DevOps: Kubernetes basics (Pods, Deployments, Services) IaC: Terraform, Ansible DSA: Graphs (BFS, DFS, Shortest Path) Hands-on Project: Deploy microservices on Kubernetes Month 6 – Cloud Native & Advanced DevOps Cloud: Serverless (AWS Lambda, Azure Functions, GCP Functions) DevOps: Advanced CI/CD, GitOps (ArgoCD) DSA: Dynamic Programming basics Hands-on Project: End-to-end Serverless app with CI/CD pipeline 📍 Phase 3: Advanced (Month 7 – Month 9) Month 7 – MLOps Foundations MLOps: ML lifecycle, Data pipelines, DVC, MLflow Cloud: Managed AI/ML services (AWS Sagemaker, Azure ML) DSA: Advanced DP, Greedy algorithms Hands-on Project: Train & track ML experiments with MLflow Month 8 – MLOps Deployment Deployment: FastAPI/Flask model serving CI/CD for ML: Kubeflow pipelines Monitoring: Drift detection, logging Hands-on Project: Deploy ML model on Kubernetes with monitoring Month 9 – Generative AI Foundations GenAI: Transformer basics, LLMs overview (GPT, LLaMA, BERT) Prompt Engineering Tools: Hugging Face, LangChain basics Hands-on Project: Build a simple GenAI chatbot with OpenAI API 📍 Phase 4: Specialization (Month 10 – Month 12) Month 10 – GenAI Applications & DSA Advanced GenAI: RAG (Retrieval Augmented Generation), Fine-tuning (LoRA, PEFT) Applications: Chatbots, Image generation, Speech AI DSA: Backtracking, Segment Trees, Bit Manipulation Hands-on Project: Custom knowledge chatbot with LangChain + Vector DB Month 11 – Specialization Track Selection Students choose one specialization: Cloud & DevOps Architect Multi-cloud architecture CI/CD at scale Security, compliance, FinOps MLOps Engineer Advanced pipelines, ML observability Large-scale model deployment GenAI Engineer Fine-tuning LLMs Building multimodal apps (text + image + speech) Hands-on Project: Capstone preparation aligned with specialization Month 12 – Capstone & Career Prep Capstone Projects: Cloud/DevOps → Multi-Cloud E-commerce infra with CI/CD MLOps → End-to-end ML pipeline with monitoring GenAI → AI Copilot app (Chatbot + RAG + API integration) Career Prep: Resume, Interview training, Mock interviews Final Demo Day: Present capstone projects 🎯 Outcome & Certification By end of the program, learners graduate as: Cloud & DevOps Architect (if specialization chosen) MLOps Engineer (if specialization chosen) GenAI Engineer (if specialization chosen) Plus strong foundation in DSA for coding interviews
☁️ Cloud Computing with ML Ops – Beginner to Advanced (9 Months) Master the future of tech by combining Cloud Computing, DevOps, and Machine Learning Operations (ML Ops) in one powerful program. This 9-month course takes you from foundational cloud skills to advanced ML deployment, including AWS/GCP, Docker, Kubernetes, Python, MLflow, and more. Learn by building real-world projects and get certified with industry-recognized credentials. Ideal for those aiming to become Cloud ML Engineers, ML Ops Specialists, or DevOps Engineers with AI expertise.
Learn the advance data engineering of Azure setup, user management, and directory services.
