What You'll Learn
Comprehensive curriculum designed by industry experts
Software Architecture for AI
- Microservices Pattern
- Event-Driven Architecture
- Queue Systems (Kafka/RabbitMQ)
- Caching for AI
- Database Selection
- API Gateway
Model Serving
- TorchServe / TF Serving
- Ray Serve
- Triton Inference Server
- Batch vs Inference
- Latency Optimization
- Edge Computing
Data Engineering Basics
- ETL Pipelines
- Data Warehousing
- Feature Stores
- Data Validation
- Apache Airflow
- Data Versioning (DVC)
DevOps for AI
- Containerization (Docker)
- Orchestration (Kubernetes)
- GPU Resource Management
- Monitoring AI Systems
- Alerting
- Security
Live Projects
Build real-world applications that look great on your portfolio
High-Scale Inference API
Build a load-balanced API capable of serving millions of AI predictions per day.
FastAPIKubernetesRedisRay
Real-time Video Processing Pipeline
Create a pipeline for processing live video streams with AI models.
KafkaOpenCVPythonWebRTC
Prerequisites
- Strong coding skills
- System design knowledge
- Linux familiarity
Career Outcomes
- Architect AI systems
- Deploy scalable models
- Manage data pipelines
- Master MLOps tools
Tools You'll Master
DockerKubernetesKafkaFastAPIAWS
Certification
AI Software Engineering Certificate
Performance-based stipend
Apply for This Internship
Start your journey with AI Software Engineering Internship