Course catalog
Found: 1 course · 15 in the catalog
Tagged RAG · Remove the tag
Version 1.1.0, 27 September 2026
level: intermediate
A practical AI course for IT professionals at Big4 and other professional-services firms. Not data-science training: you learn to choose the right AI approach, measure quality, cost and risk, and design a PoC that can honestly say no. The whole course follows one running case. You work in the Digital & IT team of the fictional firm Aldervane Advisory LLP and run two pilots: a Triage PoC that suggests and partly automates routing of ENGAGE Service Desk tickets, and a Policy Assistant, a RAG assistant over internal IT policies that later gets limited agent actions. The data is synthetic but carries real-world defects: leakage in the ticket export, a superseded policy version in the index, a restricted client folder. Topics: framing AI use cases; optimization; probability, base rates and Bayesian updating; classical ML (regression, classification, similarity, triage); enterprise documents; evaluation (precision, recall, overfitting, shadow mode, monitoring); neural networks without magic; LLMs and adaptation options; RAG; AI agents, least privilege and prompt injection; Responsible AI and governance, including the EU AI Act, NIST AI RMF and ISO/IEC 42001 as of September 2026; business cases and go / iterate / stop criteria; a capstone proposal. Every topic is taught as pain, solution and cost. About 190 practice items including calculations, diagrams and illustrations in every unit, and three optional Python labs with ready-made data generators: workload forecasting, ticket classification and a RAG prototype. Course language: Russian.
19 units · ~32.5 h without the optional units, ~39.5 h with them · material in Русский · author: Andrey Kuralekh