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CIT412Sciences3 Unitsintermediate

Modelling and Simulation

This course introduces the fundamental concepts of modelling and simulation, covering various stages of model development and simulation implementation. It explores different simulation methods and their applications in diverse fields. The course also incorporates essential statistical knowledge, including statistical distributions and probability theories, to enhance understanding of simulation outcomes. Topics such as queuing theory, simulation languages, stochastic processes, and random walks are covered, providing a comprehensive overview of modelling and simulation techniques.

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96h
Study Time
13
Weeks
7h
Per Week
intermediate
Math Level
Course Keywords
ModellingSimulationQueuing TheoryStochastic ProcessesRandom Numbers

Course Overview

Everything you need to know about this course

Course Difficulty

Intermediate Level
Builds on foundational knowledge
65%
intermediate
📊
Math Level
Moderate Math
🔬
Learning Type
Hands-on Practice

Course Topics

Key areas covered in this course

1

Modelling

2

Simulation

3

Random Numbers

4

Monte Carlo Method

5

Statistical Distributions

6

Queuing Theory

7

Stochastic Processes

8

Simulation Languages

Total Topics8 topics

Requirements

Knowledge and skills recommended for success

Basic Statistics

Introduction to Programming

💡 Don't have all requirements? Don't worry! Many students successfully complete this course with basic preparation and dedication.

Assessment Methods

How your progress will be evaluated (3 methods)

Assignments

Comprehensive evaluation of course material understanding

Written Assessment

Tutor-Marked Assessments (TMAs)

Comprehensive evaluation of course material understanding

Written Assessment

Final Examination

Comprehensive evaluation of course material understanding

Written Assessment

Career Opportunities

Explore the career paths this course opens up for you

Simulation Engineer

Apply your skills in this growing field

Data Scientist

Apply your skills in this growing field

Operations Research Analyst

Apply your skills in this growing field

Systems Analyst

Apply your skills in this growing field

Business Intelligence Analyst

Apply your skills in this growing field

Industry Applications

Real-world sectors where you can apply your knowledge

ManufacturingTelecommunicationsFinanceHealthcareLogistics

Study Schedule Beta

A structured 13-week journey through the course content

Week
1

Module 1: MODELLING AND SIMULATION CONCEPTS

4h

Unit 1: Basics of Modelling and Simulation

2 study hours
  • •Understand the definitions of model, modelling, and simulation.
  • •Explain the modelling process and its advantages.
  • •Identify different types of models and their applications.

Unit 2: Random Numbers

2 study hours
  • •Describe pseudorandom number generation techniques.
  • •Use the RND function in QBasic to simulate randomness.
  • •Explain the properties of a good random number generator.
Week
2

Module 1: MODELLING AND SIMULATION CONCEPTS

3h

Unit 3: Congruential Random Number Generator

3 study hours
  • •Explain the congruential method for generating random numbers.
  • •Choose appropriate parameters for the congruential method.
  • •Translate the method into computer programs.
Week
3

Module 1: MODELLING AND SIMULATION CONCEPTS

4h

Unit 4: Monte Carlo Methods

2 study hours
  • •Describe the Monte Carlo method and its applications.
  • •Trace the origin of the Monte Carlo method.
  • •Apply Monte Carlo methods to solve problems.

Unit 5: Statistical Distribution Functions

2 study hours
  • •Define statistics and statistical distributions.
  • •Compute measures of central tendency and variations.
  • •Explain the components of statistical distributions.
Week
4

Module 1: MODELLING AND SIMULATION CONCEPTS

3h

Unit 6: Common Probability Distributions

3 study hours
  • •Explain the role of probability distribution functions in simulations.
  • •Describe probability theory and its fundamental concepts.
  • •List common probability distributions.
Week
5

Module 2: MODELLING AND SIMULATION CONCEPTS

3h

Unit 1: Simulation and Modelling

3 study hours
  • •Explain what simulation is and why it is needed.
  • •Describe how simulations are done and various types of simulations.
  • •Give examples of simulation and its areas of application.
Week
6

Module 2: MODELLING AND SIMULATION CONCEPTS

3h

Unit 2: Modelling Methods

3 study hours
  • •Define modelling and describe basic modelling concepts.
  • •Differentiate between visual and conceptual models.
  • •Explain the characteristics of visual models.
Week
7

Module 2: MODELLING AND SIMULATION CONCEPTS

3h

Unit 3: Physics-Based Finite Element Model

3 study hours
  • •Define Finite Element Method (FEM) and its relationship to Finite Element Analysis.
  • •Describe the basics of FEM, including discretization and assembly procedures.
  • •Explain the application of boundary conditions in FEM.
Week
8

Module 2: MODELLING AND SIMULATION CONCEPTS

3h

Unit 4: Statistics for Modelling and Simulation

3 study hours
  • •Define data modelling and describe different types of data models.
  • •Explain the three perspectives of data models.
  • •Provide an overview of database models.
Week
9

Module 3: QUEUES

3h

Unit 1: Simple Theories of Queues

3 study hours
  • •Define queuing theory and describe queuing systems.
  • •Explain basic probability theories in queuing.
  • •Describe essential queuing theories.
Week
10

Module 3: QUEUES

3h

Unit 2: Basic Probability Theories in Queuing

3 study hours
  • •Explain the role of exponential and Poisson probability distributions in queuing systems.
  • •Describe the input and output processes in queuing systems.
  • •Explain steady-state probability for queues.
Week
11

Module 3: QUEUES

3h

Unit 3: Queuing Models

3 study hours
  • •Define queuing models and describe their construction.
  • •Describe single-server queue systems.
  • •Explain multiple and infinite server systems.
Week
12

Module 3: QUEUES

3h

Unit 4: Queuing Experiments

3 study hours
  • •Apply queuing theory in car wash and salesman call scenarios.
  • •Translate queuing experiments into simulation flowcharts and programs.
  • •Simulate goods production using queuing models.
Week
13

Final Revision

6h

Final Revision

6 study hours
  • •Review course materials and prepare for assignments.
  • •Work on tutor-marked assignments (TMAs).

This study schedule is in beta and may not be accurate. Please use it as a guide and consult the course outline for the most accurate information.

Course PDF Material

Read the complete course material as provided by NOUN.

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Study Tips & Exam Preparation

Expert tips to help you succeed in this course

1

Review all module objectives and key concepts.

2

Practice solving numerical problems from each unit.

3

Create concept maps linking different simulation methods.

4

Focus on understanding queuing theory formulas and their applications.

5

Practice coding simple simulation models in QBasic or other languages.

6

Review all TMAs and their solutions.

7

Allocate equal time to each module during exam preparation.

8

Create flashcards for key terms and definitions.

9

Form a study group to discuss challenging concepts.

10

Practice time management during mock exams.

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