Special 3-credit zero-to-mastery tracks: a build every day, a portfolio artefact every phase, and an oral defence.
MST 501Mastery · 90 days3 US credit hours · Mastery course · Upper-division / professional elective
Zero knowledge to production-grade agent systems in 90 days: the ten-layer production agent lifecycle taught as architectural primitives first, with a build every day and a portfolio artefact every phase.
US credit hour (34 CFR 600.2)Bangladesh BNQFOutcome-based assessmentMastery track
MST 502Mastery · 90 days3 US credit hours · Mastery course · Upper-division / professional elective
Zero knowledge to production-grade agent harnesses in 90 days: the loop, tools, context, memory, orchestration, evaluation, security and governance that turn a model into a reliable agent.
US credit hour (34 CFR 600.2)Bangladesh BNQFOutcome-based assessmentMastery track
MST 503Mastery · 30 days3 US credit hours · Mastery course · Upper-division / professional elective
Zero to master in 30 days with Cursor, the AI-native editor: Tab, Agent, Composer, Rules, MCP, Hooks, Cloud Agents, the Agents Window and the enterprise stack, with every step linked to the source.
US credit hour (34 CFR 600.2)Bangladesh BNQFOutcome-based assessmentMastery track
MST 504Mastery · 30 days3 US credit hours · Mastery course · Upper-division / professional elective
Zero to production in 30 days with Jev, a System One decision model: calibrated, typed decisions, confidence policies, cascades, agent and knowledge-graph integration, and a production architecture on AWS, with four audience tracks.
US credit hour (34 CFR 600.2)Bangladesh BNQFOutcome-based assessmentMastery track
MST 505Mastery · 90 days3 US credit hours · Mastery course · Upper-division / professional elective
Zero knowledge to production-grade context systems in 90 days: everything a model receives, retains, retrieves, prioritises and discards — retrieval, memory, tools, evaluation, caching, security and governance.
US credit hour (34 CFR 600.2)Bangladesh BNQFOutcome-based assessmentMastery track
MST 506Mastery · 90 days3 US credit hours · Mastery course · Upper-division / professional elective
Zero to production-grade AI data platforms in 90 days: parsing and chunking, vector databases, hybrid retrieval, knowledge graphs and GraphRAG, evaluation, pipelines, security and governance.
US credit hour (34 CFR 600.2)Bangladesh BNQFOutcome-based assessmentMastery track
MST 507Mastery · 90 days3 US credit hours · Mastery course · Upper-division / professional elective
Zero to mastery of feedback loops for AI systems in 90 days: control theory, agentic loops, reflection, verifiers, orchestration, evaluation, production safety and autonomous self-improving loops.
US credit hour (34 CFR 600.2)Bangladesh BNQFOutcome-based assessmentMastery track
MST 508Mastery · 90 days3 US credit hours · Mastery course · Upper-division / professional elective
Zero to production LLM engineer in 90 days: model internals, prompt and context engineering, RAG and agents, evaluation and observability, serving and fine-tuning, and production LLMOps with security and governance.
US credit hour (34 CFR 600.2)Bangladesh BNQFOutcome-based assessmentMastery track
MST 509Mastery · 90 days3 US credit hours · Mastery course · Upper-division / professional elective
Zero to mastery in 90 days: build a trusted enterprise knowledge fabric — ingestion and document intelligence, entity resolution and provenance, ontology-validated knowledge graphs, permission-aware hybrid retrieval, the AI control plane, and governance, scale and architecture.
US credit hour (34 CFR 600.2)Bangladesh BNQFOutcome-based assessmentMastery track