Course Catalogue
ArkOne courses are built by practitioners and require network membership. External courses are curated recommendations with no gate.
ArkOne
Deploying Agents at Scale
Build agents that work in production. Covers orchestration patterns, reliability engineering, observability, and cost control — from real deployments, not toy examples.
Eval Frameworks for LLMs
Stop guessing whether your LLM pipeline is getting better. This course covers practical eval methods — from LLM-as-judge to behavioural testing — that work without labelled ground truth.
RAG in Production
A practitioner's guide to building retrieval-augmented systems that hold up in production — not just demos. Covers chunking, embedding selection, retrieval evaluation, and serving at scale.
Curated External
AI Agents in LangGraph
Build agentic AI workflows using LangChain's LangGraph and Tavily's agentic search.
Hugging Face NLP Course
The official Hugging Face NLP course — transformers, tokenizers, fine-tuning, and the full 🤗 ecosystem. Best starting point if you're new to working with pre-trained models.
LLMOps
Learn LLMOps best practices as you design and automate steps to fine-tune and deploy an LLM for a specific task.
Large Language Models with Semantic Search
Learn to use LLMs to enhance search and summarize results, using Cohere Rerank and embeddings for dense retrieval.
Machine Learning Specialization
Andrew Ng's updated ML Specialization — supervised learning, unsupervised learning, and reinforcement learning. The most thorough foundational ML curriculum available, with a free audit option.
Neural Networks: Zero To Hero
Andrej Karpathy's lecture series building neural networks from scratch in Python — starting with backprop, ending with GPT. The clearest bottom-up explanation of how transformers actually work.
Practical Deep Learning for Coders
Fast.ai's foundational course for practitioners. Covers deep learning fundamentals with a code-first approach. Recommended prerequisite before ArkOne's advanced courses.
ChatGPT Prompt Engineering for Developers
Learn the fundamentals of prompt engineering for ChatGPT. Learn effective prompting, and how to use LLMs for summarizing, inferring, transforming, and expanding.