ST2187 Business analytics, applied modelling and prediction

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Hi all! Here will be published the information about Business analytics, applied modeling and prediction course

Aleksandr Khelvas
Evgeniya Tsybulko
Dr. James Abdey, invited lecturer

The book will be edited here on

Grade Formula


BU==Business Unit of course Max=100

UoL==UoL Unit Max=100

BCWE==Business Course Work and Exam Max=100

BCFW== Business Course Final Work Max=100

BMU==Business Monthly Unit Max=100


Total score = 0.7*BU + 0.3*UoL

BU=BU1*0.5 + BU2*0.5

BU1=BCWE*0.4 + (BMU1+BMU2+BM3)*0.2

BU2=BCFW2*0.7 + (BMU4+BMU5+BM6)*0.1

For each BMUn all weekly homeworks should be positive.

For each homework student has the first attempt and if the result is not positive he should use the second one with new requirements.

Due Dates:

Reporting Due Date Comments
BMU1 Oct 3 Ready for execution
BMU2 Nov 7
BMU3 Dec 5
BMU4 Feb 6
BMU5 Mar 6
BMU6 Apr 3
BCWE Dec 31
BCFW May 1

All BMU and BCW shoul be prepared and presented by pairs of students

Best 3 BMU grants +5 to BU1 and BU2 Best 3 BCW grants +10 to BU1 and BU2

Home work schedule

BHW - Home works for Business Unit

UoL - Home works for UoL

Week Link BHW UoL Due Date
Week 1 + Sept 21
Week 2 + Sept 25 + Sept 25
Week 3 BMU1 + Oct 3
Week 4 + Oct 10
Week 5 + Oct 26
Week 6 + Oct 31

Home work files requirements

All student's files should have names


FIO1 and FIO2 - latin like IvanovII

Cyrillic and special symbols in file names are prohibited.

All Seminar's Videos will be shared here

Course structure


Lecture 1 Course structure. Requirements and deliverables. Semantic model of problem. Ontology of Case 1. Bakery (COS Block 1)

Seminar 1 Data. Structured data types. CSV, XML, JSON, YAML. Excel simplest applications. Bakery component description in YAML.

Lecture 2 Introduction to the course, overview, assessment, Monty Hall problem (LSE Block 1)

Seminar 2 ABCD analysis in excel. Histogram in Excel.

Lecture 3 Processes, actions and events. BPMN.

Seminar 3 Tracks arriving schedule analysis and simulation

Lecture 4 Petri Nets. PN in event-driven simulation. Vehicles arriving and departure in bakery case. Shipping plan

Seminar 4 Tracks arriving schedule analysis and simulation in BPMN.

Lecture 5 Descriptive statistics, relationships between variables, Tableau (LSE Blocks 2, 3 and 4)

Seminar 5 Bakery Orders Dataset.

Lecture 6 Lecture 6. Event-Driven Simulation. Vehicles arriving and departure in bakery case. SimPy library for Python.

Seminar 6 ABCD analysys for bakery in Python.

Lecture 7 Probability, distributions, decision trees (LSE Blocks 5, 6 and 7) 31 Oct 2020

Seminar 7 Tableau data visualisation for Bakery Orders Dataset

Lecture 8 31 Oct 2020

Seminar 8

Lecture 9 31 Oct 2020

Seminar 9

Lecture 10 Sampling, sampling distributions, confidence intervals, hypothesis testing (Blocks 8, 9 and 10) 28 Nov 2020

Seminar 10

Lecture 11 28 Nov 2020

Seminar 11

Lecture 12 28 Nov 2020

Seminar 12

Lecture 13 5 Dec 2020

Seminar 13

Lecture 14 Regression analysis (Blocks 11 and 12) 5 Dec 2020

Seminar 14


1. YAML from Tutorials Point (I) Pvt. Ltd.

2. YAML Ain’t Markup Language (YAML™) Version 1.2 3rd Edition

3. BPMN 2.0 - Business Process Model and Notation

4.Real-Life BPMN: Using BPMN 2.0 to Analyze, Improve, and Automate Processes in Your Company 1st Edition by Jakob Freund, Bernd Rücker ISBN-13: 978-1480034983