🚀 The Algorithm Mastery Series ( part 2 )

Let's dive into the Tier 2 master space

🟡 TIER 2: PRODUCTION SYSTEMS (Build Real Infrastructure)

Part 4: Load Balancing & Resource Optimization

The infrastructure layer

Focus: Distributing work efficiently at scale
Problem: "How do I handle 1M requests/second without breaking the bank?"

Topics:
├─ Intelligent load balancing algorithms
├─ Kubernetes autoscaling algorithms
├─ Resource allocation strategies
├─ Cost optimization (Docker/JVM tuning)
└─ Cloud cost monitoring algorithms

Real-world applications:
├─ Netflix streaming (handles 200M+ users)
├─ AWS auto-scaling
├─ Kubernetes pod scheduling
└─ Cloud cost reduction

2026 Connection: Managing AI model serving infrastructure,
                 edge computing resource allocation

Skills gained:
✓ Production system design
✓ Resource optimization
✓ Cost-aware algorithms
✓ Scalability patterns

Part 5: Database Algorithms: From SQL to Vector Search 🆕

Focus: Efficient data storage and retrieval
Problem: "How do databases find my data in milliseconds from billions of records?"

Topics:
├─ B-tree indexes (why databases are fast)
├─ Hash indexes vs B-tree indexes
├─ Query optimization algorithms
├─ LSM trees (Cassandra, RocksDB)
├─ Vector databases for AI (2026 critical!)
│  └─ Approximate nearest neighbor (ANN)
│  └─ HNSW algorithm
│  └─ Product quantization
└─ Distributed database consensus (Paxos, Raft)

Real-world applications:
├─ PostgreSQL query planner
├─ MongoDB sharding
├─ Elasticsearch inverted indexes
├─ Pinecone/Weaviate vector search (LLM embeddings)
└─ Google Spanner global consistency

2026 Connection: RAG systems for LLMs, semantic search,
                 AI-powered recommendations

Skills gained:
✓ Index design
✓ Query optimization
✓ Vector similarity algorithms
✓ Distributed systems

Part 6: Caching Strategies & CDN Algorithms 🆕

Focus: Speed through intelligent data placement
Problem: "How to serve content globally with <50ms latency?"

Topics:
├─ Cache eviction algorithms
│  └─ LRU, LFU, ARC, W-TinyLFU
├─ Cache coherence in distributed systems
├─ CDN routing algorithms
├─ Edge computing placement
├─ Bloom filters for cache checking
└─ Consistent hashing for distribution

Real-world applications:
├─ Redis eviction policies
├─ Cloudflare's Argo routing
├─ Netflix Open Connect CDN
├─ Browser cache strategies
└─ DNS caching hierarchy

2026 Connection: Edge AI inference, distributed LLM serving,
                 real-time content delivery

Skills gained:
✓ Caching strategies
✓ Distributed data placement
✓ Probabilistic data structures
✓ Global optimization

Part 7: Streaming & Real-Time Processing Algorithms 🆕

Focus: Processing infinite data streams
Problem: "How to analyze millions of events per second in real-time?"

Topics:
├─ Sliding window algorithms
├─ Count-Min Sketch (approximate counting)
├─ HyperLogLog (cardinality estimation)
├─ Reservoir sampling
├─ Stream joins and aggregations
├─ Complex event processing (CEP)
└─ Backpressure handling

Real-world applications:
├─ Twitter trending topics
├─ Uber ride matching
├─ Stock market tick processing
├─ IoT sensor data processing
└─ Real-time fraud detection

2026 Connection: Real-time AI monitoring, autonomous vehicle
                 sensor fusion, live recommendation updates

Skills gained:
✓ Stream processing patterns
✓ Approximate algorithms
✓ Memory-bounded processing
✓ Real-time analytics

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🔴 TIER 3: 2026 FRONTIER (Solve Tomorrow's Problems)

Part 8: AI & Machine Learning Algorithm Engineering 🆕

Focus: Algorithms that power modern AI systems
Problem: "How do recommendation systems and LLMs actually work?"

Topics:
├─ Recommendation algorithms
│  └─ Collaborative filtering
│  └─ Matrix factorization
│  └─ Neural collaborative filtering
├─ Transformer attention mechanism
│  └─ Self-attention algorithm
│  └─ Multi-head attention
│  └─ KV-cache optimization
├─ Vector similarity search
│  └─ Cosine similarity
│  └─ FAISS algorithms
├─ Online learning algorithms
│  └─ Bandit algorithms
│  └─ A/B testing optimization
└─ Model serving optimization
   └─ Batching algorithms
   └─ Model quantization
   └─ Inference optimization

Real-world applications:
├─ YouTube recommendations (2B+ users)
├─ ChatGPT response generation
├─ Spotify Discover Weekly
├─ Amazon product recommendations
└─ Google Search ranking

2026 Problems Solved:
├─ Efficient RAG (Retrieval-Augmented Generation)
├─ Real-time personalization at scale
├─ Multi-modal search (text + image + video)
└─ Edge AI deployment

Skills gained:
✓ ML algorithm implementation
✓ Vector operations optimization
✓ Attention mechanisms
✓ Production ML systems

Part 9: Security & Cryptography Algorithms 🆕

Focus: Protecting data in the quantum era
Problem: "How to secure systems against quantum computers?"

Topics:
├─ Symmetric encryption (AES internals)
├─ Asymmetric encryption (RSA, ECC)
├─ Hash functions (SHA-256, Blake3)
├─ Digital signatures
├─ Post-quantum cryptography (2026 CRITICAL!)
│  └─ Lattice-based crypto
│  └─ CRYSTALS-Kyber algorithm
│  └─ CRYSTALS-Dilithium
├─ Zero-knowledge proofs
├─ Homomorphic encryption
├─ Threat detection algorithms
│  └─ Anomaly detection
│  └─ Rate limiting
│  └─ DDoS mitigation
└─ Blockchain consensus algorithms

Real-world applications:
├─ HTTPS/TLS encryption
├─ Bitcoin/Ethereum mining
├─ WhatsApp end-to-end encryption
├─ Password hashing (bcrypt, Argon2)
└─ AWS KMS key management

2026 Problems Solved:
├─ Quantum-safe communications
├─ AI-powered threat detection
├─ Privacy-preserving computation
├─ Decentralized identity systems
└─ Secure multi-party computation

Skills gained:
✓ Cryptographic primitives
✓ Security algorithm design
✓ Quantum-resistant systems
✓ Threat modeling

Part 10: Autonomous Systems & Optimization 🆕

Focus: Algorithms for self-driving vehicles and robotics
Problem: "How do autonomous systems make split-second decisions?"

Topics:
├─ Pathfinding for robotics
│  └─ A* algorithm
│  └─ RRT (Rapidly-exploring Random Trees)
│  └─ Dynamic programming for planning
├─ Computer vision algorithms
│  └─ Object detection (YOLO internals)
│  └─ Semantic segmentation
│  └─ Optical flow
├─ Sensor fusion algorithms
│  └─ Kalman filters
│  └─ Particle filters
├─ Decision-making under uncertainty
│  └─ Markov Decision Processes (MDP)
│  └─ Monte Carlo Tree Search (MCTS)
├─ Supply chain optimization
│  └─ Vehicle routing problem
│  └─ Traveling salesman (modern approaches)
│  └─ Inventory optimization
└─ Energy grid optimization
   └─ Load balancing algorithms
   └─ Peak shaving strategies

Real-world applications:
├─ Tesla Autopilot path planning
├─ Waymo object detection
├─ Amazon warehouse robots
├─ FedEx route optimization
├─ Google Maps traffic prediction
└─ Smart grid management

2026 Problems Solved:
├─ Level 5 autonomous driving
├─ Drone delivery routing
├─ Robot manipulation planning
├─ Supply chain resilience
└─ Renewable energy optimization

Skills gained:
✓ Motion planning
✓ Sensor processing
✓ Optimization algorithms
✓ Real-time decision making

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