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View our Virtual tourCourses - September 2024
Level 1
Course details
Conestoga 101
CON0101
- Hours: 1
- Credits: 0
- Pre-Requisites:
- CoRequisites:
Project Management
MGMT8666
- Hours: 56
- Credits: 4
- Pre-Requisites:
- CoRequisites:
Fundamentals of Programming
PROG8491
- Hours: 56
- Credits: 4
- Pre-Requisites:
- CoRequisites:
Data Modelling for Analytics
PROG8501
- Hours: 56
- Credits: 4
- Pre-Requisites:
- CoRequisites:
Statistical Applications for Data Analytics I
STAT8021
- Hours: 56
- Credits: 4
- Pre-Requisites:
- CoRequisites:
Multivariate Statistics
STAT8031
- Hours: 56
- Credits: 4
- Pre-Requisites:
- CoRequisites:
Level 2
Course details
Career Management
CDEV8132
- Hours: 28
- Credits: 2
- Pre-Requisites:
- CoRequisites:
Management and Leadership Essentials
MGMT8761
- Hours: 42
- Credits: 3
- Pre-Requisites:
- CoRequisites:
Programming Statistics for Business
PROG8511
Using analytical software and programming, students will learn to delve into data sets and draw conclusions using exploratory analytics, predictive and statistical techniques. Including confidence intervals, t-tests, and statistical inference. Students will also practice visualizing their findings in a way that will effectively communicate their conclusions to business stakeholders.
- Hours: 56
- Credits: 4
- Pre-Requisites:
- CoRequisites:
Data Modelling II – Analytics
PROG8521
This course will build on the predictive analytics tool kit by utilizing both supervised (dependent variable) and unsupervised (no dependent variable) learning methods to uncover the information from the data and then act on this information. Building models such as Classification and Regression (supervised) as well as Clustering (unsupervised) will be covered. Students will apply data modelling techniques using Microsoft Excel.
- Hours: 42
- Credits: 3
- Pre-Requisites:
- CoRequisites:
Statistical Forecasting
STAT8041
This course will apply the principles of time series analysis to teach students to analyze data where multiple measurements are made over time using common statistical forecasting techniques. Students will study the key concepts, patterns, and relationships found in time series data. Emphasis will be placed on forecasting and predictive analysis.
- Hours: 56
- Credits: 4
- Pre-Requisites:
- CoRequisites:
Statistical Applications for Data Analytics II
STAT8051
This course builds on the skills developed in Statistical Applications for Data Analytics I to further explore data analytics using current industry tools and best practices. Students will learn to use common industry tools and practices to analyze and interpret analytical models and results to facilitate decision making and generate visualizations. Practical applications of descriptive, predictive, and prescriptive data mining and analysis will be explored across a broad range of industries.
- Hours: 56
- Credits: 4
- Pre-Requisites:
- CoRequisites:
Program outcomes
- Develop high quality software solutions to collect, manipulate and mine data sets that satisfy the business requirements of organizations
- Analyze different system architectures and data storage technologies in order to select appropriate solutions that support data analytics requirements.
- Design data models that meet the needs of the predictive analysis process.
- Develop software solutions that align with the predictive analysis process to produce desired reports.
- Analyze existing data visualization methods used in business to recommend customizations that align with the predictive process.
- Customize business intelligence tools to support evidence-based decision making based on the predictive process.
- Employ environmentally sustainable practices within the field of data analytics.
- Predict industry trends and collect insights to expand the organization’s entrepreneurial strategies and generate new opportunities.
- Examine relationships among multiple variables simultaneously to predict the effect of proposed changes to business.