Software Developer
AI Systems Architect
Master distributed AI systems using modern tools and agents.
Advanced Python
Async patterns, decorators, metaclasses, performance profiling.
Distributed Systems
CAP theorem, consensus, fault tolerance, scalability patterns.
Cloud Infrastructure
Kubernetes, Docker, containerization, cloud native architectures.
Systems Design
Load balancing, caching, databases, message queues, APIs.
ML Fundamentals
Supervised, unsupervised, reinforcement learning core principles.
Deep Learning
Neural networks, CNNs, RNNs, transformers, attention mechanisms.
Large Language Models
Transformer architecture, pretraining, fine-tuning, alignment techniques.
Vector Databases
Embeddings, semantic search, similarity matching, RAG architecture.
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