The definitive 32-module masterclass: from foundation models and multimodal systems to fine-tuning, reasoning models, distributed inference, LLMOps, SRE, FinOps, red teaming, and enterprise capstones.
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Foundation models, tokenization, autoregressive sampling, context windows, temperature, top-p, and architectural taxonomy.
Few-shot prompting, system instructions, JSON mode, Pydantic schemas, function calling, and output parsing reliability.
Scaled dot-product attention, multi-head self-attention, query-key-value projections, positional encoding, and decoder blocks.
Dense embeddings, chunking strategies, FAISS vector search, semantic reranking, and hybrid lexical-semantic pipelines.
Graph RAG, query decomposition, hypothetical document embeddings (HyDE), context compression, and agentic retrieval.
Chains, tool calling, stateful StateGraphs, conditional routing, human-in-the-loop validation, and multi-agent coordination.
Autonomous GUI interaction, OS environment execution, planning cycles (ReAct), and sandbox execution security.
Vision-Language Models (VLMs), image understanding, document OCR, speech-to-text, and video sequence comprehension.
Cross-modal latent projections, interleaved multimodal generation, and multimodal tool-use pipelines.
Code generation architectures, AST-aware prompt construction, test generation, and automated refactoring agents.
Supervised fine-tuning (SFT), low-rank adapters (LoRA), 4-bit quantization (QLoRA), and Hugging Face PEFT.
Distributed Data Parallel (DDP), DeepSpeed ZeRO, pipeline parallelism, tensor parallelism, and loss scaling.
Reinforcement Learning from Human Feedback (RLHF), Direct Preference Optimization (DPO), and safety tuning.
Teacher-student distillation, weight pruning, Post-Training Quantization (AWQ/GPTQ), and edge optimization.
Architectures for Phi, Gemma, and Llama-Small, ONNX Runtime, and local on-device neural deployment.
Test-time compute scaling, Chain-of-Thought (CoT), Tree-of-Thoughts, and self-consistency verification.
Curating high-quality training corpora, Evol-Instruct methodology, data filtering, and deduplication.
Multi-tenant LLM gateways, enterprise identity integration, data residency, and high-availability design.
High-throughput serving engines, PagedAttention, continuous batching, and GPU cluster load balancing.
Continuous batching, KV caching, vLLM serving, latency budgeting, and streaming response architecture.
Fallback routing, token rate-limiting, semantic caching, and unified multi-provider model routing.
Token economics, model tiering (SLM vs Frontier), cache hit optimization, and cost allocation telemetry.
SLOs/SLAs for probabilistic systems, circuit breakers, graceful degradation, and incident mitigation.
Golden evaluation datasets, synthetic evaluation generation, and continuous CI/CD evaluation test harnesses.
LLM-as-a-Judge, RAG Triad (Faithfulness, Relevance, Groundedness), and domain-specific benchmarking.
NeMo Guardrails, regex/semantic input-output filtering, PII redaction, and hallucination containment.
OWASP Top 10 for LLMs, zero-trust inference, data privacy compliance (GDPR/HIPAA), and audit logging.
Automated red-teaming harnesses, jailbreak payload generation, indirect injection probing, and vulnerability scans.
Bridging state-of-the-art academic papers to scalable, battle-tested software engineering architectures.
State-Space Models (Mamba), Mixture-of-Depths, test-time compute, and future neural paradigms.
Production-grade multi-agent autonomous support engine with vector retrieval and human review.
Complete autonomous research and code analysis system deployed with Docker, FastAPI, and telemetry.