2026/2027
Аналитика и представление данных
Язык:
английский
Кредиты:
5
Контактные часы:
48
Course Syllabus
Abstract
The course is the first-semester analytical foundation of the HSE University minor Analytics and Consulting. It covers data and measurement, statistical reasoning, experiments and causal decisions, business intelligence and communication, and AI-assisted analytical work. The course is intended primarily for undergraduate students from business-oriented programmes with varied technical backgrounds.
Learning Objectives
- Develop students’ ability to formulate analytical questions, work critically with data and quantitative evidence, and communicate conclusions and limitations for decision-making
Expected Learning Outcomes
- ● Translate an ambiguous business or client problem into a decision, focused analytical questions, and testable hypotheses.
- ● Define and critically assess business and product metrics, including their population, unit of analysis, time window, calculation rules, and relationship to the decision.
- ● Explain how business events become analytical data and identify risks related to data collection, identifiers, grain, joins, transformations, and data quality.
- ● Summarise and analyse data and interpret distributions, sampling variation, confidence intervals, hypothesis tests, practical significance, power, and regression at an introductory level.
- ● Distinguish descriptive, predictive, and causal claims; design and evaluate a basic A/B test; and recognise when the available evidence does not support a causal conclusion.
- ● Select clear and truthful visualisations and dashboard structures appropriate to the audience and the decision.
- ● Communicate evidence, uncertainty, limitations, a recommendation, and a practical next action in a decision-ready form.
- ● Use AI tools to support data discovery, SQL, calculations, visualisation, and communication while verifying provenance, assumptions, outputs, and reproducibility and recognising when specialist support is required
Course Contents
- 1. Analytics and decision-making in the AI era
- 2. Data and measurement
- 3. Statistical reasoning
- 4. Experiments and causal decisions
- 5. Business intelligence and communication
- 6. AI-native analytical workflow
Interim Assessment
- 2026/2027 2nd module0.1 * Attendance + 0.3 * Final project + 0.2 * Homework 1 + 0.2 * Quizzes on lectures and seminars + 0.2 * Homework 2
