Course Structure
Module 1: Introduction to core Data Analysis tools | ||
3% | Sprint 1 | Structured approach to data analysis |
5% | Sprint 2 | Analyst toolkit. Spreadsheets |
7% | Sprint 3 | Analyst toolkit. SQL and databases |
8% | Sprint 4 | Analyst toolkit. Advanced SQL and databases |
Module 2: Communicating Analysis Results | ||
8% | Sprint 1 | Visualising Data Using Tableau |
5% | Sprint 2 | Presentations & Soft skills |
Modules 3-4 (modules A & B can be taken in any order): | ||
8% | Module A | Data analysis and visualisation with Python |
17% | Module B | Funnels, AB tests (5%); Linear & logistic regression (7%); Risk Analyst (5%) |
Module 5: Main Analysis Types (Danske) | ||
5% | Sprint 1 | Cohorts, Retention, Churn |
5% | Sprint 2 | CLV (Customer Lifetime Value), Customer segmentation, RFM (recency, frequency & monetary value) |
Specialisation modules (modules A-E can be taken in any order) | ||
5% | Module A | Financial Analyst |
5% | Module B | Product analyst |
5% | Module C | Marketing analyst |
5% | Module D | Payments, Monetisation Analyst |
9% | Module E | Capstone project |