Data Analytics is a new way of understanding complex systems by building computational models that are consistent with the observed data about those systems. If you want to play a positive role in shaping the way people make important decisions based on the presentation of data, then this is the right certificate for you.
What is a Certificate?
Certificates are mini-credentials that appear on your official transcript.
- Certificates offered by the School of Computing are meant for non-Computing students.
- They are not a degree. Students looking for a Computing degree must still enrol in either the Computing Major or a Specialization.
- They typically consist of about 5 courses.
- Two of these electives/option courses (i.e., 6.0 units) can be used towards your degree requirements.
- They are a great way to set you apart from your competition when it comes to applying for jobs.
A complete list of certificates offered by the University can be found in the Certificates section of the Academic Calendar.
Requirements
The following are the requirements for the Data Analytics Certificate. This information is meant as a guide and is subject to change. The precise and up-to-date requirements for Computing programs can be found online in the University's Academic Calendar. In case of discrepancies, please notify the School's Curriculum Coordinator.
A half-year/one-term course is worth 3.0 units, while a full-year/two-term course is worth 6.0 units.
1. Core
| Code | Title | Units |
|---|---|---|
| A. Complete the following: | ||
| CISC 251 | Data Analytics | 3.0 |
| CISC 351 | Advanced Data Analytics | 3.0 |
| CISC 451 | Topics in Data Analytics | 3.0 |
| B. Complete 3.0 units from the following: | 3.0 | |
| STAT 263 | Introduction to Statistics | |
| STAT 268 | Statistics and Probability I | |
| STAT 351 | Probability I | |
| STAT_Options | ||
2. Option
| Code | Title | Units |
|---|---|---|
| A. Complete 3.0 units from the following: | 3.0 | |
| BIOL 343 | Data Analysis for Biologists | |
| CISC 181 | Digital Societies | |
| CISC 432 | Advanced Data Management Systems | |
| EMPR 370 | Human Resource Analytics | |
| PATH 411 | Applied Data Science in Molecular Medicine | |
| PSYC 301 | Advanced Statistical Inference | |
| SOCY 284 | Sociology of Information and Communication Technology | |
| SOCY 309 | Surveillance and Society | |
| STAT 269 | Statistics and Probability II | |
| STAT 351 | Probability I | |
| STAT 466 | Statistical Programming with SAS and Applications | |
Statistics Course List (STAT_Options)
| Code | Title | Units |
|---|---|---|
| BIOL 243 | Introduction to Statistics | 3.0 | CHEE 209 | Analysis Of Process Data | 3.5 |
| COMM 162 | Managerial Statistics | 3.0 |
| ECON 250 | Introduction to Statistics | 3.0 |
| GPHY 247 | Introduction to Statistics | 3.0 |
| KNPE 251 | Introduction to Statistics | 3.0 |
| NURS 323 | Introduction to Statistics | 3.0 |
| POLS 385 | Introduction to Statistics | 3.0 |
| PSYC 202 | Statistics in Psychology | 3.0 |
| SOCY 211 | Introduction to Statistics | 3.0 |
| STAM 200 | Introduction to Statistics | 3.0 |
| STAT 263 | Introduction to Statistics | 3.0 |
| STAT 367 | Engineering Data Analysis | 4.0 |