Syllabus
Registration via LPIS
This hands-on doctoral course introduces effective use of contemporary AI for business analytics and research. Students learn to specify and verify model assisted work, build a small analytics application through AI assisted coding, call a model through an API, obtain structured output, and connect the model to controlled analytical tools. The course culminates in a minimal bounded agentic AI assistant. The emphasis is on durable principles, analytical correctness, and verification.
| Session | Central question | Principal output |
|---|---|---|
| 1 | How do I work effectively with an AI model? | AI task specification and verification record. |
| 2 | How do I build software through AI assisted coding? | Working analytics application and failure log. |
| 3 | How does an application communicate with an AI model? | Reproducible model measurement pipeline. |
| 4 | How can AI perform a bounded analytical workflow? | Model and tools analytical application. |
| 5 | When does an AI application become an agent? | Minimal bounded agent and capstonedefense. |
After completing the course, students can (1) use AI through clear task specifications and staged interaction; (2) verify AI supported analytical work; (3) build and repair a small application with an AI coding assistant; (4) make basic model API calls and process structured output; (5) connect a model to controlled analytical functions; (6) distinguish models, applications, workflows, and bounded agents; and (7) document and defend AI assisted work reproducibly.
Attendance and active participation are mandatory because the course consists of five cumulative sessions. Students participate in the guided labs, peer testing, failure debriefs, and final project defense. Absences are handled according to the applicable WU study regulations.
Each session begins with a 30-minute discussion of one academic pre-reading. A concise conceptual input and reference demonstration are followed by a guided hands-on lab, an independent challenge, and a failure debrief. All sessions use supplied starter repository and/or code base with data. AI assisted coding is an explicit learning objective.
Individual AI analytics competency task (20 percent); AI assisted analytical application with tests, process documentation, and automated acceptance checks (35 percent); models to agent project with evaluation, report, live demonstration, and individual defense (45 percent). All three components must be completed.
1 | > 89
2 | 80 - 89
3 | 70 - 79
4 | 60 - 69
5 | < 60
Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.
No previous API experience is required. Prior Python experience is welcome but not necessary. Students complete the technical setup and diagnostic task before Session 1 and bring a laptop capable of running a Python environment and installing Claude Desktop.
Before and after class and by appointment. Questions that are relevant to the full group should be submitted through the designated course channel. Research design questions may also be addressed in scheduled project clinics.
The course is taught in English. Students use supplied repositories and codebases as well as public or instructor supplied data. The reference software environment and model versions are pinned for the course. Alternative tools are permitted, but support is limited to the reference stack. Course managed access and usage limits are communicated before the first session. Tool access, hosting, and data protection follow the separate Academic
Dependencies and Data Protection Note. Students are expected to use AI-supported coding for the duration of the course (i.e., Claude Code with a Claude Pro subscription) and have (or obtain) an Anthropic developer account with sufficient API credits (approximately EUR 50).
Back