90 courses covering everything from how a model learns to building enterprise AI systems. No paywalls, no prerequisites, no fluff.
All ten courses are fully built: index, six modules, capstone, and a six-part blog series each.
What a model is, how the training loop works, data and tokenization, the transformer architecture, scaling and evaluation, and fine-tuning and alignment.
What a prompt is, the anatomy of a prompt, zero-shot and few-shot and chain-of-thought, prompt patterns, avoiding bad outputs, and applying it to your use case.
Publishing daily. Each course includes 6 modules, a capstone, and a 6-part blog series.
Vector databases, embeddings, chunking strategies, RAG pipelines, and evaluating retrieval quality.
Building the business case, choosing vendors, governance, risk, and leading an AI transformation.
Benchmarks, human evaluation, automated metrics, red-teaming, and the MEDFIT-LLM framework for domain-specific evaluation.
What alignment means, RLHF, Constitutional AI, jailbreaks, and what safety research looks like today.
Transformers, tokenization, pretraining objectives, RLHF and DPO, inference efficiency, and scaling laws. No black boxes.
What the shift to agentic AI demands from enterprise teams: failure modes, infrastructure, governance, use case selection, and an 18-month pilot-to-scale roadmap.
The role that ships enterprise AI in weeks, not years. Discovery sprints, rapid pilots, demos that close, handoff protocols, and how to grow as an FDE.
Board-ready AI fluency: business case frameworks, governance obligations under EU AI Act, buy/build/partner decisions, the CAIO question, and an 18-month roadmap.
Vision-language models, document AI for PDFs and invoices, audio transcription and diarization, cross-modal retrieval, multimodal agents, and enterprise deployment.
Pick the path that matches where you are today.
Start with Model Development Fundamentals, then Prompt Engineering. No math required.
Prompt Engineering first, then AI for Enterprise Leaders, then AI Governance.
Model Development, then Fine-Tuning, then RAG, then Inference Optimization.
Prompt Engineering, then AI Agents, then RAG, then Evaluating AI Models.
The courses are free. For hands-on strategy work with your team, book a session.
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