IT Mentorship & Software Courses | Yugandhar Open Academy

Course Name	Description	Next Batch
System Design for Interviews	Learn how to design scalable, reliable systems and confidently crack system design interviews at top product and technology companies.	Planning
Microservices using Java	Build scalable microservices using Java and Spring Boot, covering service discovery, communication, resilience, and deployment.	Planning
Full Stack Development using Node/React	End-to-end web application development covering frontend, backend, APIs, authentication, and deployment.	Planning
Machine Learning using Python	Learn core machine learning concepts, algorithms, and hands-on model building using Python and popular ML libraries.	Planning
Agentic AI Development	Design and build autonomous AI agents capable of planning, reasoning, tool usage, and multi-agent collaboration.	Planning

Course Curriculum

Module 1: System Design Fundamentals
- Functional vs Non-functional requirements
- Scalability, availability, reliability
- Capacity estimation and trade-offs
Module 2: Core Building Blocks
- Load balancers and caching
- Databases (SQL vs NoSQL)
- Message queues and async processing
Module 3: Distributed Systems Concepts
- CAP theorem
- Consistency models
- Sharding and replication
Module 4: Designing Popular Systems
- URL shortener
- News feed system
- Chat and file storage systems
Module 5: Interview Strategy
- Structuring answers
- Design communication techniques
- Common pitfalls

Module 1: Microservices Architecture
- Monolith vs microservices
- Domain-driven design basics
Module 2: Spring Boot Essentials
- REST API development
- Configuration and profiles
- Error handling
Module 3: Inter-Service Communication
- REST and messaging
- Service discovery
- API gateways
Module 4: Resilience & Observability
- Circuit breakers
- Retries and timeouts
- Logging and monitoring
Module 5: Deployment & Scaling
- Docker and containerization
- CI/CD pipelines
- Cloud deployment patterns

Module 1: Frontend with React
- Components, hooks, and state
- Routing and UI patterns
Module 2: Backend with Node.js
- REST APIs with Express / NestJS
- Middleware and validation
Module 3: Database & Authentication
- SQL and NoSQL databases
- JWT and session-based authentication
Module 4: Full Stack Integration
- Frontend-backend integration
- Security best practices
Module 5: Deployment & Production
- Build pipelines
- Performance optimization

Module 1: Python & Data Foundations
- NumPy, Pandas, Matplotlib
- Data preprocessing
Module 2: ML Fundamentals
- Supervised vs unsupervised learning
- Bias-variance tradeoff
Module 3: Algorithms
- Regression models
- Decision trees and clustering
Module 4: Model Evaluation
- Feature engineering
- Hyperparameter tuning
Module 5: Practical Applications
- End-to-end ML project
- Deployment basics

Module 1: Agentic AI Foundations
- What is agentic AI?
- LLM capabilities and limitations
Module 2: Single-Agent Design
- Goal setting and task decomposition
- Tool usage and memory
Module 3: Multi-Agent Systems
- Agent roles and coordination
- Planner–Executor–Reviewer pattern
Module 4: Tooling & Integrations
- APIs and databases
- Search and retrieval
Module 5: Safety & Deployment
- Guardrails and observability
- Production deployment patterns