Thirteen weeks of structured progression.

1. Week 0 — Foundation and Setup

   Programme orientation; role of a data analyst; file management; spreadsheet basics; business mathematics; percentages, ratios and averages; logical reasoning; GitHub and project organisation; software setup; responsible AI; data privacy; diagnostic assessment.

   Deliverable: Foundation assessment and learning-readiness record.

2. Week 1 — Analyst Mindset and Excel Foundations

   Business questions; KPIs; data types and structure; sorting/filtering; formulas; basic functions; data-quality checks; duplicates and missing values; introductory analysis.

   Deliverable: Cleaned dataset and basic analytical summary.

3. Week 2 — Advanced Excel and Power Query

   Lookup functions; conditional calculations; PivotTables/PivotCharts; data validation; Power Query; transformation; combining datasets; refreshable workflows; dashboard design.

   Deliverable: Sales performance dashboard.

4. Week 3 — Statistics for Business Decisions

   Descriptive statistics; central tendency; variability and distributions; percentages/ratios; outliers; correlation and limitations; sampling; introductory hypothesis testing; statistical interpretation; business recommendations.

   Deliverable: Statistical analysis report.

5. Week 4 — SQL Fundamentals

   Relational databases; SELECT; WHERE; sorting; aggregation; GROUP BY; HAVING; CASE; introductory joins; readable query formatting.

   Deliverable: SQL practical assignment.

6. Week 5 — SQL Joins, Subqueries and CTEs

   Inner/outer joins; multi-table analysis; subqueries; Common Table Expressions; date analysis; customer/product metrics; query debugging; consistency checks.

   Deliverable: Multi-table business analysis.

7. Week 6 — Advanced SQL and Customer Analysis

   Window functions; ranking; running totals; period comparisons; customer cohorts; repeat purchases; retention metrics; query optimisation fundamentals; interpretation.

   Deliverable: E-commerce customer and retention analysis.

8. Week 7 — Python Fundamentals for Analytics

   Syntax; variables and types; conditions/loops; lists/dictionaries; functions; error handling; files; Jupyter notebooks; NumPy; Pandas.

   Deliverable: Python fundamentals assignment.

9. Week 8 — Data Cleaning and Exploratory Analysis

   Importing datasets; DataFrame inspection; missing values; duplicates; data types; filtering/grouping; descriptive analysis; visualisation; pattern identification; communication.

   Deliverable: Python exploratory data analysis.

10. Week 9 — Power BI and Data Modelling

    Importing data; Power Query; relationships; data modelling; fact/dimension tables; star schema; report design; filters/slicers; drill-through; visualisation; usability.

    Deliverable: Initial Power BI dashboard.

11. Week 10 — DAX and Executive Dashboards

    Measures/calculated columns; basic DAX; filter context; CALCULATE; business metrics; period comparisons; dashboard validation; executive reporting; performance storytelling.

    Deliverable: Completed executive dashboard.

12. Week 11 — AI-Augmented Analytics and Integrated Business Case

    AI for business questions; AI-assisted SQL/Python; reviewing formulas/code; independent testing; error detection; hallucination awareness; privacy; validation logs; integrated case; communicating limitations.

    Deliverable: AI-assisted assignment and validation log.

13. Week 12 — Capstone and Career Preparation

    Capstone finalisation; technical/dashboard review; documentation; portfolio organisation; project presentation; interview simulation; CV and project discussion; feedback.

    Deliverable: Final capstone and presentation.

The curriculum is subject to confirmation of lesson plans, datasets, teaching materials, assignments, marking rubrics and the session calendar by the programme’s academic lead before launch, and may be updated under TerraNext’s programme policies. Material changes are communicated transparently to enrolled learners.