Advanced Path

Master AI deployment, policy design, fine-tuning, and optimization. For teams building serious AI systems.

36 guides·~332 minutes total

Your learning journey

Model Compression: Smaller, Faster AI

Compress AI models with quantization, pruning, and distillation. Deploy faster, cheaper models without sacrificing much accuracy.

Advanced8 min read

Quantization and Distillation Deep Dive

Master advanced model compression: quantization-aware training, mixed precision, and distillation strategies for production deployment.

Advanced8 min read

Distributed Training for Large Models

Scale AI training across multiple GPUs and machines. Learn data parallelism, model parallelism, and pipeline parallelism strategies.

Advanced9 min read

Advanced RAG Techniques

Go beyond basic RAG: hybrid search, reranking, query expansion, HyDE, and multi-hop retrieval for better context quality.

Advanced7 min read

Multi-Agent AI Systems

Build AI systems with multiple specialized agents that collaborate, debate, and solve complex tasks together.

Advanced8 min read

Prompt Injection Attacks and Defenses

Adversaries manipulate AI behavior through prompt injection. Learn attack vectors, detection, and defense strategies.

Advanced8 min read

AI Red Teaming: Finding Failures Before Users Do

Systematically test AI systems for failures, biases, jailbreaks, and harmful outputs. Build robust AI through adversarial testing.

Advanced7 min read

Constitutional AI: Teaching Models to Self-Critique

Constitutional AI trains models to follow principles, self-critique, and revise harmful outputs without human feedback on every example.

Advanced7 min read

Preference Optimization: DPO and Beyond

Direct Preference Optimization (DPO) and variants train models on human preferences without separate reward models. Simpler, more stable than RLHF.

Advanced8 min read

Tool Use and Function Calling

Enable AI to call APIs, query databases, and use external tools. Build agentic systems that take actions in the world.

Advanced8 min read

Advanced AI Evaluation Frameworks

Build comprehensive evaluation systems: automated testing, human-in-the-loop, LLM-as-judge, and continuous monitoring.

Advanced7 min read

Synthetic Data Generation for AI Training

Generate training data with AI: create examples, augment datasets, and bootstrap models when real data is scarce or sensitive.

Advanced6 min read

Active Learning: Smart Data Labeling

Reduce labeling costs by intelligently selecting which examples to label. Active learning strategies for efficient model training.

Advanced6 min read

Continual Learning: Models That Keep Learning

Train models on new data without forgetting old knowledge. Continual learning strategies for evolving AI systems.

Advanced8 min read

Efficient Inference Optimization

Optimize AI inference for speed and cost: batching, caching, model serving, KV cache, speculative decoding, and more.

Advanced7 min read

Model Interpretability: Understanding AI Decisions

Understand how AI makes decisions: attention visualization, feature importance, LIME, SHAP, and interpretability techniques.

Advanced7 min read

Adversarial Robustness: Defending AI from Attacks

Harden AI against adversarial examples, data poisoning, and evasion attacks. Testing and defense strategies.

Advanced8 min read

AI Governance Frameworks for Organizations

Establish AI governance: policies, approval processes, risk assessment, and compliance for responsible AI deployment at scale.

Advanced8 min read

Enterprise AI Architecture

Design scalable, secure AI infrastructure for enterprises: hybrid deployment, data governance, model management, and integration.

Advanced8 min read

MLOps for LLMs

Apply MLOps practices to LLMs: versioning, CI/CD, monitoring, incident response, and lifecycle management for production AI.

Advanced7 min read

Advanced Prompt Optimization

Systematically optimize prompts: automated testing, genetic algorithms, prompt compression, and performance tuning.

Advanced7 min read

Training Custom Embedding Models

Fine-tune or train embedding models for your domain. Improve retrieval quality with domain-specific embeddings.

Advanced8 min read

AI Policy and Regulation Landscape

Navigate AI regulations: EU AI Act, US executive orders, sector-specific rules, and global frameworks. Compliance strategies for organizations.

Advanced7 min read

Training Multi-Modal Models

Train models that understand images and text together. Contrastive learning, vision-language pre-training, and alignment techniques.

Advanced7 min read

Designing Custom AI Architectures

Design specialized AI architectures for unique problems. When and how to go beyond pre-trained models and build custom solutions.

Intermediate12 min read

Fine-Tuning vs RAG: Which Should You Use?

Compare fine-tuning and RAG to customize AI. Learn when each approach works best, how they differ, and how to combine them.

Intermediate14 min read

Guardrails & Policy Design for AI

Design policies and guardrails to keep AI safe, compliant, and aligned with your values. Prevent harm, bias, and misuse.

Advanced13 min read

Cost & Latency: Making AI Fast and Affordable

Optimize AI systems for speed and cost. Techniques for reducing latency, controlling API costs, and scaling efficiently.

Advanced14 min read

Evaluations 201: Golden Sets, Rubrics, and Automated Eval

Build rigorous evaluation systems for AI. Create golden datasets, define rubrics, automate testing, and measure improvements.

Advanced13 min read

Privacy & PII Basics: Protecting Personal Data in AI

How to handle personally identifiable information (PII) in AI systems. Privacy best practices, compliance, and risk mitigation.

Intermediate13 min read

Deployment Patterns: Serverless, Edge, and Containers

How to deploy AI systems in production. Compare serverless, edge, container, and self-hosted options.

Intermediate12 min read

Orchestration Options: LangChain, LlamaIndex, and Beyond

Frameworks for building AI workflows. Compare LangChain, LlamaIndex, Haystack, and custom solutions.

Advanced12 min read

AI System Design Patterns: Building Robust AI Applications

Learn proven design patterns for AI systems. From retrieval-augmented generation to multi-agent architectures—practical patterns for building reliable, scalable AI applications.

Advanced11 min read

Scalable AI Infrastructure: Building for Growth

Learn how to build AI infrastructure that scales with demand. From compute optimization to cost management—practical guidance for production AI systems.

Advanced20 min read

Monitoring AI Systems in Production

Enterprise-grade monitoring, alerting, and observability for production AI systems. Learn to track performance, costs, quality, and security at scale.

Advanced10 min read

Training Efficient Models: Doing More with Less

Learn techniques for training AI models efficiently. From data efficiency to compute optimization—practical approaches for reducing training costs and time.

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Intermediate Path

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