Advanced Business Analytics Training Course

Name: Advanced Business Analytics and Predictive Modeling Training Course
Availability: InStock

Select, evaluate, interpret, and communicate statistical, predictive, and prescriptive methods for complex business decisions.

Advanced Business Analytics Training Course

At a glance

Duration: 5 days
Format: Classroom
Cities: Chicago, London, Tokyo, Frankfurt, Bangkok, Tbilisi and more
Next session: 18 – 22 October 2026, Chicago
Average fee: 5,800 €

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Advanced Business Analytics and Predictive Modeling Training Course

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Overview

Advanced Business Analytics and Predictive Modeling Training Course is a five-day advanced course for data analysts, business intelligence analysts, analytics engineers, business analysts, data scientists, and decision-support professionals who leave with an Advanced Analytics Decision Portfolio. Participants connect analytical problem framing, statistical inference, regression, classification, clustering, time-series forecasting, anomaly detection, optimization, model evaluation, interpretation, and decision recommendations. Agile Leaders Training Center develops practical advanced business analytics capability.

Who Should Attend

Data analysis functions responsible for investigating patterns and testing business hypotheses
Business intelligence functions responsible for extending reporting into predictive insight
Analytics engineering functions responsible for reliable analytical datasets and workflows
Business analysis functions responsible for framing decisions and interpreting evidence
Data science functions responsible for model selection, evaluation, and explanation
Decision-support functions responsible for comparing options and communicating recommendations

The course assumes participants can prepare tabular data, interpret summary statistics, and work with analytical outputs, and leaves out introductory spreadsheet skills, dashboard design, data-pipeline engineering, and certification exam preparation.

Departments and Industries

The course supports departments and industries that use analytical evidence to guide complex decisions.

Banking risk and customer analytics
Retail demand and commercial planning
Healthcare operations analysis
Manufacturing quality and process improvement
Telecommunications customer and network insight

Learning Objectives

By the end of this course, participants will be able to:

Analyze business questions through an analytics decision frame
Apply statistical inference and diagnostic methods
Build and compare predictive modeling approaches
Evaluate classification, clustering, and forecasting results
Use anomaly detection and optimization for decisions
Build an Advanced Analytics Decision Portfolio

Course Agenda

Day 1: Frame Advanced Analytics Decisions

Analytics Decision Question Canvas
Descriptive, Diagnostic, Predictive, and Prescriptive Map
Analytical Unit and Outcome Definition Sheet
Data Suitability and Leakage Checklist
Decision Cost and Success Measure Register

Day 2: Diagnose Patterns and Relationships

Statistical Distribution and Outlier Profile
Sampling and Statistical Inference Framework
Hypothesis Test Selection Matrix
Correlation and Association Interpretation Guide
Diagnostic Segmentation Evidence Table

Day 3: Build Predictive Models

Regression Model Specification Template
Classification Feature and Outcome Matrix
Training and Validation Split Protocol
Model Performance Comparison Scorecard
Prediction Error and Residual Diagnostic

Day 4: Extend Analytics to Decisions

Clustering and Segment Interpretation Method
Time-Series Forecasting Workflow
Anomaly Detection Threshold Framework
Prescriptive Optimization Decision Model
Model Interpretation and Assumption Register

Day 5: Practice Analytics Decision Support

Exercise: Frame an Analytical Decision Question
Exercise: Diagnose Patterns and Test Evidence
Exercise: Compare Predictive Model Performance
Exercise: Translate Forecasts and Optimization into Options
Capstone: Advanced Analytics Decision Portfolio

Practical Exercises

The course uses suggested activities based on banking, retail, healthcare, manufacturing, and telecommunications decisions.

Suggested activity: translate a business concern into an analytical unit, outcome, measure, and decision threshold.
Suggested activity: investigate distributions, outliers, relationships, hypotheses, and segments without overstating evidence.
Suggested activity: compare regression and classification models through validation evidence and decision costs.
Suggested activity: combine forecasts, anomaly signals, optimization choices, assumptions, and recommendations in a decision portfolio.

FAQs

Who suits advanced business analytics and predictive modeling training, and what does it assume?

Data, business intelligence, analytics engineering, business analysis, data science, and decision-support functions suit the training; it assumes experience preparing tabular data and interpreting summary statistics.

How does advanced business analytics differ from introductory data analysis training?

Advanced business analytics evaluates statistical, predictive, and prescriptive methods for complex decisions, while introductory data analysis training focuses on basic preparation, summaries, charts, and straightforward interpretation.

How should analysts choose between regression and classification?

Analysts should choose regression when the outcome is continuous and classification when the outcome is a defined class, then test assumptions, validation evidence, error costs, interpretability, and intended decisions.

What makes predictive modeling evidence reliable?

Reliable predictive modeling evidence depends on suitable data, leakage prevention, representative validation, appropriate metrics, comparison with a baseline, error analysis, stable assumptions, transparent limitations, and decision relevance.

How do prescriptive analytics support business decisions?

Prescriptive analytics compare feasible actions under objectives and constraints, using forecasts, costs, risks, capacity, scenarios, and sensitivity analysis to present decision options rather than automatic certainty.

Conclusion

Participants take back an Advanced Analytics Decision Portfolio linking questions, data suitability, statistical evidence, models, validation, forecasts, anomalies, optimization, assumptions, and recommendations. It changes isolated analytical outputs into traceable decision support. The portfolio helps data, business intelligence, analytics, science, and management functions evaluate options through shared evidence.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

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Showing 1-20 of 74 events

Location	Dates	Duration	Mode	Price
Chicago	Week 42, 2026 18 – 22 October 2026	5 Days	Onsite	€12,000
London	Week 43, 2026 19 – 23 October 2026	5 Days	Onsite	€5,700
Tokyo	Week 44, 2026 26 – 30 October 2026	5 Days	Onsite	€10,000
Frankfurt	Week 44, 2026 26 – 30 October 2026	5 Days	Onsite	€5,700
Zoom	Week 45, 2026 2 – 6 November 2026	5 Days	Online	€1,500
Bangkok	Week 45, 2026 8 – 12 November 2026	5 Days	Onsite	€6,000
Tbilisi	Week 48, 2026 23 – 27 November 2026	5 Days	Onsite	€5,000
Phuket	Week 48, 2026 29 November – 3 December 2026	5 Days	Onsite	€6,000
Marbella	Week 48, 2026 29 November – 3 December 2026	5 Days	Onsite	€5,700
Muscat	Week 49, 2026 6 – 10 December 2026	5 Days	Onsite	€5,700
Dubai	Week 50, 2026 7 – 11 December 2026	5 Days	Onsite	€4,500
Paris	Week 51, 2026 14 – 18 December 2026	5 Days	Onsite	€5,700
Lisbon	Week 51, 2026 14 – 18 December 2026	5 Days	Onsite	€5,700
Vienna	Week 52, 2026 21 – 25 December 2026	5 Days	Onsite	€5,700
Rome	Week 53, 2026 28 December 2026 – 1 January 2027	5 Days	Onsite	€5,700
Abu Dhabi	Week 53, 2026 28 December 2026 – 1 January 2027	5 Days	Onsite	€4,700
London	Week 01, 2027 4 – 8 January 2027	5 Days	Onsite	€5,700
Amman	Week 01, 2027 10 – 14 January 2027	5 Days	Onsite	€4,100
Johannesburg	Week 01, 2027 10 – 14 January 2027	5 Days	Onsite	€4,500
Rome	Week 03, 2027 18 – 22 January 2027	5 Days	Onsite	€5,700

Frequently asked questions

What does this course cover?

OverviewAdvanced Business Analytics and Predictive Modeling Training Course is a five-day advanced course for data analysts, business intelligence analysts, analytics engineers, business analysts, data scientists, and decision-support professionals who leave with an Advanced Analytics Decision Portfolio. Participants connect analytical problem framing, st…

Are training dates available?

Yes. Available dates and destinations are listed in the course dates section on this page.

How can I register?

Choose an available date on this page and complete the registration form, or send a programme enquiry.

Can I download the course brochure?

Yes. Use the brochure download link provided on this page.

Advanced Business Analytics Training Course