Emphasis in Analytics

analytics icon

Analytics covers a range of methodologies, from descriptive to predictive to prescriptive approaches.

Descriptive

Information

Using statistic to analyze and understand data

Predictive

Insight

Use machine learning to forecast unknown info

Prescriptive

Decisions

Use optimization to make data-driven decision

The following descriptions are adapted from IBM white paper (source).

Descriptive analytics: “What has happened?”

  • Mines data to provide information on past or current events
  • Often emphasizes effective data visualization
  • Characterized by use of key performance indicators, reports, dashboards, basic statistics

Predictive analytics: “What could happen?”

  • Uses data accumulated over time and mathematical models to predict possible future events or associations between data
  • Characterized by use of advanced statistics, forecasting, simulation, machine learning methods

Prescriptive analytics: “What should we do?”

  • Uses data (possibly predictions) and models to recommend optimal decisions
  • Modern methods account for uncertainty in data and predictions when optimizing the decision
  • Characterized by use simulation and optimization methods

Master of Engineering (MEng) students in graduate units in the departments of Chemical Engineering & Applied Chemistry, Civil Engineering, Electrical & Computer Engineering, and Mechanical & Industrial Engineering can earn an Emphasis in Analytics by successfully completing four courses from the two lists presented below. At least one (1) course must be from the list of core courses. The other courses must be selected from the list of elective courses.

Core Courses

 MIE 1624H: Introduction to Data Science and Analytics

ECE1504H: Statistical Learning (new course offered in the 2018-2019 academic year)

 

Elective Courses

APS 502H: Financial Engineering

APS 1005H: Operations Research for Engineering Management

APS 1017H: Supply Chain Management and Logistics

APS 1022H: Financial Engineering II

CHE 507H: Data-based Modelling for Prediction and Control

CHE 1147H: Data Mining in Engineering

CHE 1148H: Process Data Analytics

CHE 1434H: Six Sigma for Chemical Processes

CIV 1504H: Applied Probability and Statistics for Civil Engineering

CIV 1506H: Freight Transportation and ITS Applications

CIV 1507H: Public Transport

CIV 1532H: Fundamentals of ITS and Traffic Management

CIV 1538H: Transportation Demand Analysis

ECE 537H: Random Processes

ECE 1505H: Convex Optimization

ECE 1510H: Advanced Inference Algorithms

ECE 1657H: Game Theory and Evolutionary Games

ECE 1778H: Creative Applications for Mobile Devices

ECE 1779H: Introduction to Cloud Computing

MIE 562H: Scheduling

MIE 1413H: Statistical Models in Empirical Research

MIE 1501H: Knowledge Modelling and Management

MIE 1512H: Data Analytics

MIE 1513H: Decision Support Systems

MIE 1620H: Linear Programming and Network Flows

MIE 1621H: Non­Linear Optimization

MIE 1622H: Computational Finance and Risk Management

MIE 1623H: Introduction to Healthcare Engineering

MIE 1653H: Integer Programming Applications

MIE 1721H: Reliability

MIE 1723H: Engineering Asset Management

MIE 1727H: Statistical Methods of Quality Assurance


EXAMPLE OF COURSES IN EACH OF THE THREE PILLARS OF ANALYTICS

 DescriptivePredictivePrescriptive
Department of Chemical Engineering and Applied Chemistry (ChemE)CHE 1434H: Six Sigma for Chemical ProcessesCHE 507H: Data-based Modelling for Prediction and ControlCHE 507H: Data-based Modelling for Prediction and Control
CHE 507H: Data-based Modelling for Prediction and ControlCHE 1148: Process Data AnalyticsCHE 1148: Process Data Analytics
CHE 1148: Process Data Analytics
Department of Civil Engineering (CivE)CIV 1504H: Applied Probability and Statistics for Civil EngineeringCIV 1507H: Public Transport
CIV 1507H: Public TransportCIV 1532H: Fundamentals of ITS and Traffic ManagementCIV 1506H: Freight Transportation and ITS Applications
CIV 1532H: Fundamentals of ITS and Traffic ManagementCIV 1538H: Transportation Demand AnalysisCIV 1507H: Public Transport
CIV 1538H: Transportation Demand AnalysisCIV 1532H: Fundamentals of ITS and Traffic Management
CIV 1538H: Transportation Demand Analysis
Department of Electrical and Computer Engineering (ECE)ECE 537H: Random ProcessesECE 1504H: Statistical Learning ECE 1505H: Convex Optimization
ECE 1778H: Creative Applications for Mobile DevicesECE 1510H: Advanced Inference AlgorithmsECE 1657H: Game Theory and Evolutionary Games
ECE 1779H: Introduction to Cloud Computing
Department of Mechanical and Industrial Engineering (MIE)MIE 1413H: Statistical Models in Empirical ResearchMIE 1413H: Statistical Models in Empirical ResearchMIE 562H: Scheduling
MIE 1501H: Knowledge Modelling and ManagementMIE 1501H: Knowledge Modelling and ManagementMIE 1501H: Knowledge Modelling and Management
MIE 1512H: Data AnalyticsMIE 1512H: Data AnalyticsMIE 1620H: Linear Programming and Network Flows
MIE 1513H: Decision Support SystemsMIE 1622H: Computational Finance and Risk ManagementMIE 1621H: Non­Linear Optimization
MIE 1624H: Introduction to Data Science and AnalyticsMIE 1623H: Introduction to Healthcare EngineeringMIE 1622H: Computational Finance and Risk Management
MIE 1727H: Statistical Methods of Quality AssuranceMIE 1624H: Introduction to Data Science and AnalyticsMIE 1623H: Introduction to Healthcare Engineering
MIE 1721H: ReliabilityMIE 1653H: Integer Programming Applications
MIE 1723H: Engineering Asset ManagementMIE 1723H: Engineering Asset Management
MIE 1727H: Statistical Methods of Quality Assurance
Entrepreneurship, Leadership, Innovation and Technology in Engineering (ELITE) APS 502H: Financial Engineering
APS 1005H: Operations Research for Engineering Management
APS 1017H: Supply Chain Management and Logistics
APS 1022H: Financial Engineering II
JMG 2020H: Big Data and Global CitiesJMG 2020H: Big Data and Global Cities