Artificial Intelligence and Data Analytics Diploma
About the Artificial Intelligence and Data Analytics Diploma
The Artificial Intelligence and Data Analytics (AIDA) diploma prepares you to use AI technology to create innovative solutions for modern industry problems.
In this program, you will learn the steps in the deep learning and data analytics process including;
data mining, text scraping, and sensor data collection
data preprocessing, exploratory analysis and storytelling
developing machine learning algorithms and data systems
deploying models with security in mind
You'll choose a personalized learning path that aligns with your interests and career goals to specialize in one of three areas of focus; Machine Learning, Business Intelligence, Bioinformatics or create your own unique specialization.
Co-op Specialization
The Co-op Specialization allows you the opportunity to network and apply knowledge through structured work experience. Most of the courses will be held in-person on RDP's Main campus, with a few available online.
Note: Co-op placements may require travel to locations in central Alberta outside of the City of Red Deer.
Work-integrated Learning
To ensure workplace readiness, all students will complete WIL 1100 during their first year, before placement. This module prepares you for work placements with skills such as resume writing and interview preparation.
AIDA Diploma
WIL 2100 generally consists of a 100-hour work placement or an equivalent project that solves a problem or creates efficiency for an organization.
Weekly seminar discussions will connect Work-Integrated Learning and classroom learning.
AIDA Diploma: Co-op Specialization
COOP 2100 is a required 420-hour (minimum) paid work term secured on a competitive basis in Term Four.
Note: Students should be prepared to incur the costs of a work placement. This could include suitable attire, travel to and from the placement, and other incidentals.
Further Study
The AIDA diploma can transfer into RDP degrees. The number of transferable credits varying by the nature of the degree.
Chat with our Student Connect Centre to learn more.
Related Careers
The Artificial Intelligence and Data Analytics diploma prepares graduates for a career using technology to innovate and problem-solve.
Data Analyst
Machine Learning Analyst
AI Technologist
Business Intelligence Analyst
Data Technologist
Data Administrator
Data Consultant
Marketing Analyst
GIS (Geographic Information Systems) Technician
Machine Learning Specialists
Logistics Analyst
Meet the Faculty
At Red Deer Polytechnic we are proud of our faculty members and staff who are experts in their disciplines and subject areas.
Domestic Intakes
Fall 2025 - Open
- Application window:
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- Registration start date:
- Fee payment deadline:
- First day of classes:
International Intakes
Fall 2025 - Open
- Application window:
-
- Registration start date:
- Fee payment deadline:
- First day of classes:
Note:
International students have to pay their tuition deposit to receive their letters of acceptance
Important dates may change.
Admission Requirements
Admission requirements for specific programs will often refer to Alberta Grade 12 course groups. Visit the Admission Requirements page for detailed group descriptions.
If you have completed your high school education outside of Alberta, please refer to our International Course Equivalencies page for information on how your coursework may align with our admission requirements.
Qualified applicants who meet all minimum requirements will be offered admission on a first-come, first-served basis.
Academic Requirements
Students applying for the Artificial Intelligence and Data Analytics diploma must have:
A minimum of 50% in English 30-1 (ENGL 0301) or equivalent or a minimum of 60% in English 30-2 (ENGL 0300) or equivalent; and
- A minimum of 50% in Math 30-1 (MATH 0301) or equivalent
AIDA Co-op Specialization Diploma Admission Requirements:
Students applying to the AIDA Diploma, Co-op Specialization must meet the above Academic Requirements.
Students interested in the Co-Op Specialization should apply directly, as there are limited seats available, and are required to meet the pre-requisites for COOP 2100 to continue with the Co-Op placement in their final term.
COOP 2100 is a required course in the Co-op Specialization. The pre-requisites for COOP 2100 include:
a minimum of 60 credits
good academic standing
completion of the CEED Work Readiness modules, and
a job offer with a suitable employer.
Note:
RDP cannot guarantee a Co-op placement if students are unable to secure a job offer
Students who do not meet the requirements for the Co-op specialization will be eligible to graduate with the Artificial Intelligence and Data Analytics Diploma.
Students taking COOP 2100 should be prepared to incur the costs of employment. This could include suitable attire, travel to and from work, and other incidentals
Additional Requirements
English Language Proficiency
Applicants whose first language is not English must demonstrate English language proficiency in addition to the program admission requirements.
Prior Learning and Transfer
Students may receive Recognition of Prior Learning in some courses where the learning of skills, knowledge or competencies has been acquired through work, formal and informal education or training, or self-study.
Recommended for Online Learners
While not an admission requirement for the program, to be successful, students should have basic computer skills, such as the ability to function independently on basic computer software programs and to carry out basic internet navigation.
Program Cost
These costs are an estimate of tuition and fees based on the recommended course load per year.
NOTE: Additional fees apply. See below for estimated breakdown of tuition, non-instructional mandatory fees, health and dental plan costs, and estimated textbooks and supplies costs:
Financial Aid Options
Explore financial aid options, including loans, scholarships, and awards.
Program Content
All students will develop strong foundational learning through shared required courses. In the second year, you'll be able to specialize in one of four areas: Machine Learning, Business Intelligence, Bioinformatics, or Build Your Own Stream.
Years 1 & 2 Required Courses
- AIDA 1141 Introduction to Machine Learning and Data Science.
- CPRO 1201 Python Programming I
- CPRO 1301 Database Design and SQL
- MATH 1221 Linear Algebra I
- AIDA 1143 Machine Learning Algorithms I
- AIDA 1145 Data Engineering
- PHIL 2399 Technology & Computing
- AIDA 2152 Machine Learning Algorithms II
- AIDA 2154 Computer Vision
- AIDA 2156 Exploratory Data Analysis (EDA)
- WIL 2100 Work Integrated Learning Experience
- AIDA 2157 Emerging Techniques in ML and AI
- AIDA 2158 Neural Networks and Deep Learning
AND one of the following
- ENGL 1212 English for Engineering Students
- ENGL 1219 Essay Writing and Critical Reading
- CPRO 1011 Communication in the Workplace
- COMM 1250 Business and Workplace Writing
AND one of the following
- BUS 2306 Business Statistics I
- STAT 1251 Introductory Statistics
Choose Your Stream
Deep dive into artificial intelligence, data-driven decision making, the intersection of biology & computer science, or a blend of all three by choosing five courses within your chosen stream.
Machine Learning Stream (ML)
- BUS 2110 Management Principles
- ENT 2251 Innovation and Entrepreneurship or ESB 2254 Project Design and Management
- AIDA 2360 Internet of Things (IOT) or AIDA 2362 Geographic Information Systems (GIS)
- AIDA 2364 Graph Theory and Applications in ML
- AIDA 2362 Geographic Information Systems (GIS)
- AIDA 2372 Machine Learning Deployment
Business Intelligence Stream (BI)
- MKT 2242 Marketing Research
- ENT 2368 Business Analysis
- ESB 2204 Interpersonal Skills and Leadership
- AIDA 2362 Geographic Information Systems (GIS)
- AIDA 2364 Graph Theory and Applications in ML
- AIDA 2360 Internet of Things (IOT)
- ENT 2374 Enterprise Analytics
Bioinformatics Stream (BIO)
- ESB 2254 Project Design and Management OR
- AIDA 2360 Internet of Things (IOT)
- AIDA 2366 Bioinformatics
- AIDA 2376 Epidemiological Data Analysis
- AIDA 2362 Geographic Information Systems (GIS)
- AIDA 2370 Clinical Trials
- BIOL 1217 Introduction to Cell Biology
- BIOL 1218 Evolution & Biological Diversity
Build Your Own Stream
- Complete five courses from ML, BIO, BI, and/or any 3-credit academic course at RDP.
Program Courses
Graduation Requirements
AIDA Diploma:
Students must pass all courses and achieve a minimum cumulative GPA of 2.0 to graduate from the Artificial Intelligence and Data Analytics Diploma.
AIDA Co-Op Specialization Diploma:
Students must pass all courses including the Co-Op Work Term (COOP 2100) and achieve a minimum cumulative GPA of 2.0 to graduate from the Artificial Intelligence and Data Analytics Co-Op Specialization Diploma.
Continuing and Professional Education
Further your career by advancing your existing skills through flexible courses, micro-credentials and programs.