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Business Analytics & Data Science
Prepare data you can trust, describe it, test ideas with statistics, and build models that predict and explain. 6 of 12 courses are open; the rest are planned and listed with what they will cover.
Prepare data you can trust, describe it, test ideas with statistics, and build models that predict and explain. Courses are listed in the order to take them, from introductory to advanced; each lists what it requires. Courses marked Planned are not written yet, but their syllabus is here and some link to plates and tools that already cover part of the ground.
Suggested order
If you are starting out, take the courses in this order: each comes after everything it requires, and the general before the specialised. Step 1, B01, is open now and starts from scratch.
- B01 Introduction to Business Analytics
- B02 Data Cleaning and Preparation
- B03 Excel for Business Analytics
- B07 SQL and Business Databases
- B04 Descriptive and Inferential Statistics
- B10 Visualisation and Business Intelligence
- B05 Correlation Analysis
- B06 Regression Analysis
- B08 Machine Learning for Business
- B09 Forecasting and Time Series
- B11 Optimisation and Decision Analytics
- B12 Experimental Design and Applied Analytics
Introductory
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B01Complete
Introduction to Business Analytics
The four kinds of analytics, turning business questions into measurable ones, and reading data sensibly.
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B02Complete
Data Cleaning and Preparation
Turn a messy export into data you can trust: profile it, fix records and formats, handle missing and unusual values, and prepare it for analysis without biasing the result.
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B03Complete
Excel for Business Analytics
Formulas, lookups, tables and cleaning, PivotTables, charts, descriptive statistics and regression output, what-if analysis and dashboards in Excel.
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B07Planned
SQL and Business Databases
Relational databases and the queries that answer business questions.
What it will cover
- Relational databases
- Tables and primary keys
- Foreign keys
- Entity relationships
- One-to-one and one-to-many relationships
- SELECT, WHERE, GROUP BY, ORDER BY
- JOINs
- Aggregate functions
- Subqueries
- Common table expressions
- Data integrity
- Reporting queries
Intermediate
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B04Complete
Descriptive and Inferential Statistics
Describe data and chance, then reason from samples to populations with confidence intervals, tests for means and proportions, chi-square tests and ANOVA, by hand and in Excel.
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B10Planned
Visualisation and Business Intelligence
Choose the right chart, design dashboards people can use, and tell an honest story with data.
What it will cover
- Choosing charts
- Dashboard design
- Data storytelling
- Heatmaps
- Histograms
- Scatterplots
- Line and bar charts
- KPI scorecards
- BI tool concepts
- Visual accessibility
- Misleading visualisations
- Interactive reporting
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B05Complete
Correlation Analysis
Measure how variables move together, test it, and avoid reading causation into it.
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B06Reviewed
Regression Analysis
Fit, read and check linear and logistic regressions, and know what they can and can’t tell you.
Advanced
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B08Planned
Machine Learning for Business
Supervised and unsupervised models, honest evaluation, and the limits of prediction.
What it will cover
- Supervised learning
- Unsupervised learning
- Training and test sets
- Cross-validation
- Data leakage
- Linear and logistic models
- Decision trees
- Random forests
- Gradient boosting
- k-means clustering
- Principal component analysis
- Feature engineering
- Model evaluation
- Overfitting and underfitting
- Bias and variance
- Explainability and ethics
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B09Planned
Forecasting and Time Series
Trend, seasonality, smoothing and ARIMA, judged by honest out-of-sample error.
What it will cover
- Time-series components
- Trend and seasonality
- Moving averages
- Exponential smoothing
- Forecast error
- MAE, MSE, RMSE, MAPE and their limits
- Regression-based forecasting
- ARIMA fundamentals
- Demand forecasting
- Business forecasting scenarios
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B11Planned
Optimisation and Decision Analytics
Linear programming, simulation and decision trees for allocating scarce resources.
What it will cover
- Linear programming
- Objective functions
- Constraints
- Resource allocation
- Transportation and supply-chain problems
- Portfolio optimisation
- Simulation
- Monte Carlo methods
- Sensitivity analysis
- Decision trees
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B12Planned
Experimental Design and Applied Analytics
A/B tests and experiments done properly, then an end-to-end analytics project.
What it will cover
- A/B testing
- Control and treatment groups
- Randomisation
- Confounding variables
- Statistical inference
- Sample size
- Interpreting experiments
- Business decisions from evidence
- End-to-end analytics projects
Prerequisite map
The map as a list
- B01 Introduction to Business Analytics: no required courses.
- B02 Data Cleaning and Preparation: no required courses; B01 recommended.
- B03 Excel for Business Analytics: no required courses; B01 and B02 recommended.
- B07 SQL and Business Databases: no required courses; B01 and B02 recommended.
- B04 Descriptive and Inferential Statistics: requires B01 and B03; B02 recommended.
- B10 Visualisation and Business Intelligence: requires B01; B03 recommended.
- B05 Correlation Analysis: requires B04; B03 recommended.
- B06 Regression Analysis: requires B05; B03 recommended.
- B08 Machine Learning for Business: requires B06 and B02.
- B09 Forecasting and Time Series: requires B06.
- B11 Optimisation and Decision Analytics: requires B04; B03 recommended.
- B12 Experimental Design and Applied Analytics: requires B04 and B06.