Why a Graduate Certificate in Fundamental Data Science and Analytics?
The demand for professionals trained with deep data and analytical skills is disrupting the job market. There is an incredible need for data scientists and business analysts to make sense of the large amounts of data that are collected, to uncover hidden solutions to messy business problems and to present useful insights to business leaders.
With the Certificate in Fundamental Data Science and Analytics, you gain the necessary knowledge base and useful skills to manage large data sets and present real-world data analytics challenges with the use of statistical modelling and data visualization tools.
The Certificate in Fundamental Data Science and Analytics will count for credit toward the Diploma in Data Science and Analytics, where you may choose to specialize in business analytics, data science or health data science and biostatistics. The diploma program is for students who have completed the certificate and will add 4 courses of specialized study.
NOTE: Once you have initiated your application, be sure to choose "Fundamental Data Science and Analytics-Certificate" from the list of programs offered.
The program in Data Science and Analytics is a unique graduate-level program as the curriculum for this program was developed by an interdisciplinary group of faculty members from the Faculty of Science, the Cumming School of Medicine and the Haskayne School of Business. As a student, you take full advantage of the expertise from all of these disciplines across campus. Furthermore, you have the flexibility to take specialized courses if you decide to ladder into the diploma program. Students progressing through the laddering pathway will receive full course and tuition credit for the four courses they completed in the certificate program and will need to complete four additional courses to obtain the diploma in Data Science and Analytics with a specialization in either Business Analytics or Data Science.
Another unique feature of the program in Data Science and Analytics offered by the University of Calgary is the experiential learning component of the program. As a student, you will get hands-on experience with data from the industry made available through our network of company contacts. This learning experience plays a critical role in knowledge construction and understanding the crucial role of data within organizations.
- The certificate program will expose you to all phases of the Data Science and Analytics Pipeline:
- Data Collection – Applying automated, manual, and hybrid approaches to elicit, sense, simulate, or otherwise capture data.
- Data Cleaning – Transforming raw, noisy, incomplete, or otherwise dirty data into forms that can support further analysis.
- Exploratory Analytics – Using visualization, statistics, and other techniques to examine new data and identify possible opportunities for analysis.
- Statistical & Computational Analytics – Applying computational, mathematical, or statistical techniques and models to make sense of and extract knowledge from data.
- Presentation – Using visual, oral, and written approaches to communicate analysis processes, observations, and results.
The certificate program consists of four intensive courses and will expose you to all phases of the Data Science and Analytics Pipeline.
You will take the following four courses:
Data Science 601 | Working with Data and Visualization
An introduction to fundamental data science concepts including basic data organization, data collection, and data cleaning. Includes a review of basic programming concepts in Python, as well as an introduction to the fundamentals of data visualization and critical thinking with data and it also provides an introduction to data ethics, security, and privacy.
Data Science 602 | Statistical Data Analysis
An introduction to the foundations of statistical inference including the application of probability models to data, as well as an introduction to simulation-based and classical statistical inference, and the creation of statistical models with R.
Data Science 603 | Statistical Modeling with Data
An introduction to the creation of complex statistical models, including exposure to multivariate model selection, prediction, the statistical design of experiments and analysis of data in R.
Data Science 604 | Big Data Management
An introduction to data storage and manipulation at both desktop and cloud scales. Introduces core database concepts and provides a practical introduction to both SQL and NoSQL systems. Also introduces parallel and distributed computing concepts including distributed storage and large scale parallel data processing using MapReduce. Students will also explore how to design and implement new data visualizations to aid their analysis with emphasis on the practical and ethical implications of design and analysis decisions.
This certificate will give you the foundational knowledge needed to begin work related to data science and analytics. As a data scientist you will analyze data from across a company, spot trends and use your business acumen to recommend what problems to tackle and how to tackle them. Your skills will be transferable to many sectors – business, retail, e-commerce, advertising, healthcare, etc.
Graduates of the certificate program also have the opportunity to ladder into the Diploma in Data Science and Analytics. Students progressing through the laddering pathway will receive 12 units (4 HCE) of advanced course and tuition credit toward the 24-unit (8 HCE) diploma program, for the work they complete in this certificate.