π» Full Stack Development with Gen AI β 9 Months Become a future-ready developer by mastering Frontend, Backend, Databases, and integrating powerful Gen AI tools like ChatGPT & DALLΒ·E into real-world web apps. Learn React, Node.js, MongoDB, OpenAI APIs, and build a strong portfolio with live projects, certifications, and job support.
π Data Analyst with Python β 6 Months Program. Kickstart your career in data with this beginner-friendly to advanced course focused on Python, SQL, Excel, Power BI/Tableau and real-world projects. Master data cleaning, visualization, and analysis, build a strong portfolio, and become job-ready with full certification & placement support.
βοΈ Cloud Computing with ML Ops β 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.
π FastTrack Career Program | 6-Month Job-Ready Training | Live Classes, Mentorship & Projects π©βπ» Beginner to Advanced | Learn Programming, DSA, SQL, & Choose Your Specialisation π Backend, Full Stack, or Data Engineering | Industry Tools + Hands-On Practice π― Mock Interviews + Resume Building | Capstone Project With Expert Guidance π Bonus: GenAI, System Design, Product Thinking | Flexible EMI | Placement Support
π Month 1: Core Foundations β Linux, Networking & Infrastructure π― Objective: Build rock-solid fundamentals required for production systems π§ Topics Covered π§ Linux internals (processes, memory, file systems, permissions, systemd) π Advanced shell scripting (Bash, AWK, Sed, Cron jobs) π Networking fundamentals (TCP/IP, DNS, HTTP/HTTPS, Load Balancing) π OS-level security basics π SSH hardening & access control π§ͺ Hands-On Labs π₯οΈ Hardened Ubuntu Server setup π Secure NGINX web server deployment π Reverse proxy & load balancer configuration βοΈ Month 2: Cloud Fundamentals β AWS & Azure from Scratch π― Objective: Understand cloud infrastructure at scale π οΈ Technologies π§ AWS: EC2, VPC, IAM, S3, ALB, Auto Scaling π¦ Azure: VM, VNets, NSG, Azure Storage π Cloud networking & identity design π° Cost optimization & tagging strategies π’ Industry Use Cases ποΈ AWS infra setup for a TCS-style internal application ποΈ Multi-tier architecture for an EY consulting workload π³ Month 3: Containerization & Kubernetes Engineering π― Objective: Move from VM-based systems to container orchestration βοΈ Technologies π¦ Docker internals & image optimization βΈοΈ Kubernetes architecture (API Server, Scheduler, etcd) π Helm charts π¦ Ingress controllers (NGINX, Traefik) βοΈ Stateful vs Stateless workloads π Project ποΈ Kubernetes-based microservices deployment for an Amazon-like e-commerce backend π Month 4: CI/CD & DevOps Automation π― Objective: Build automated delivery pipelines π§° Technologies π§ GitHub Actions, Jenkins, GitLab CI ποΈ Infrastructure as Code (Terraform) π οΈ Configuration management (Ansible) π Blue-Green & Canary deployments π Real-World Scenarios π CI/CD pipeline for Walmart-scale application releases π’ Automated infra provisioning for a PwC consulting client π‘οΈ Month 5: DevSecOps β Security Embedded into Pipelines π― Objective: Shift security left π Technologies & Practices π§ͺ SAST, DAST, SCA π Secrets management (Vault) π¦ Container security (Trivy, Aqua) βΈοΈ Kubernetes RBAC & Network Policies π Compliance automation π§© Project π DevSecOps pipeline aligned with KPMG audit & compliance standards π Month 6: Observability, Reliability & AIOps Foundations π― Objective: Operate systems intelligently at scale π Technologies π Prometheus & Grafana π ELK Stack (Elasticsearch, Logstash, Kibana) π§΅ Distributed tracing (Jaeger) π― SLA, SLO, Error Budgets π€ Introduction to AIOps π Use Case β‘ Real-time monitoring for a Blinkit-style logistics platform π€ Month 7: MLOps β Machine Learning in Production π― Objective: Operationalize ML systems π§ Technologies π ML pipelines (training, validation, deployment) π¦ Model versioning (MLflow) π¬ Feature stores βΈοΈ Kubernetes-based ML serving π CI/CD for ML models π Project ποΈ Demand forecasting model deployment for Retail Analytics (Amazon/Walmart inspired) π§ Month 8: LLMOps β Managing Large Language Models π― Objective: Deploy and manage LLM-based systems π οΈ Technologies π LLM deployment pipelines π§ͺ Model fine-tuning workflows ποΈ Vector databases (Pinecone, FAISS) βοΈ Prompt engineering pipelines π API gateways for AI services π’ Enterprise Scenario π Internal AI assistant for a Deloitte-style consulting knowledge base π Month 9: Capstone Projects & Enterprise Simulation π― Objective: Deliver production-grade systems end-to-end π§© Capstone Options (Choose One) 1οΈβ£ AI-Powered E-Commerce Platform π Amazon/Walmart Inspired βοΈ Cloud + βΈοΈ Kubernetes + π CI/CD + π€ AIOps + π¬ LLM Chatbot 2οΈβ£ Consulting Firm Cloud Platform π’ PwC/KPMG Inspired π Secure multi-tenant infra + DevSecOps + Compliance dashboards 3οΈβ£ Real-Time Logistics Intelligence Platform π Blinkit Inspired π Observability + π Predictive scaling + π€ ML-driven alerts π¦ Deliverables π Architecture design documents π» GitHub repositories π Monitoring dashboards π Security & cost reports π Production-grade deployment π Outcome & Career Readiness By the end of the program, learners will be able to: β Design & operate enterprise cloud platforms β Build secure, scalable CI/CD pipelines β Manage AI & ML workloads in production β Work as Cloud Engineer, DevOps Engineer, SRE, MLOps Engineer, Platform Engineer π Why This Program is Different π₯ Starts from absolute fundamentals π Ends with real-world, enterprise-grade deployments π§ Covers DevOps + AI Operations, not just tools π’ Strong alignment with Big 4 consulting & product companies π― Built for placement-backed, outcome-driven learning
Learn AWS (20+ services), Azure, Git, GitHub, Docker, Kubernetes, Jenkins, Terraform, JIRA, Maven, Ant, and SonarQube. Perfect for IT professionals aiming to build CI/CD pipelines, automate infrastructure, and deploy secure, scalable applications. 100% pre-recorded sessions, hands-on labs, and certification included.
Learn the advance data engineering of Azure setup, user management, and directory services.
This power-packed course combines Python, Data Structures & Algorithms, Machine Learning, and cutting-edge GenAI tools like ChatGPT, LangChain, and AutoML. Build projects, strengthen your coding foundation, and prepare for top tech roles with structured pre-recorded content and real-world applications.
Learn everything from Excel to Power BI, SQL to Python, and data storytelling to dashboard building. This hands-on, beginner-friendly course will take you from data basics to business insights, equipping you with all the tools top companies look for in a Data Analyst.