Introduction to Data Science Certificate
This 3 course certificate introduces students to the key elements of Data Science: Python programming, SQL & database design, data processing, and analysis & visualization. This certificate will add a valuable skillset to any professional and the skills and training that a student can develop by completing this certificate are widely applicable and transferrable.
Coursework explores the topics of data ethics and digital ethics, helping to prepare the student for a challenging, dynamic career in data analytic work. Students may be interested in this certificate if they are seeking to grow in their existing careers, switch to a career within the data science realm, or explore data science as a field before committing to a degree program or advanced study in the topic.
This certificate can be taken as a stand-alone or in partnership with a SCPS degree.
|Total Number of Courses||
(4 if completing an optional course)
|Total Number of Credit Hours||
9 credit hours
(10-12 credit hours if completing the optional course)
|Start Term & Time to Completion||
Once started, you will take 1 course each 8-week session for 3 sessions and complete within 7-12 months.
Schedule for students starting in Fall I (August):
Fall I – CPST 291, Fall II – COMP 251, Spring I – CPST 325
Please note that this certificate only offers a Fall I start.
|Schedule Format||Courses are offered in an online, 8-week format.|
|Transfer Credit Accepted Toward Certificate||3 credit hours (1 course). Transfer credit must be from the last five years and can’t be applied toward CPST 325.|
Online with weekly synchronous meetings held in the evening.
|Application and Admission Requirements||
Students must demonstrate knowledge in introductory level object-oriented programming and statistics either through prior academic coursework or through professional experience. Students without this background may be asked to complete additional coursework.
|Tuition and Fees|
- COMP 251 Introduction to Database Systems
- CPST 291 Dynamic Programming Languages
- CPST 325 Data Processing, Analysis, and Visualization
CPST 265 Special Topics – 1-3 credits of directed study. Student will solve a data science problem for a community non-profit organization under the guidance of a faculty member.
- Students will be able to: Design, implement, test, and debug a program that uses each of the following fundamental programming constructs: basic computation, variables, expressions, I/O, standard conditional and iterative structures (loops), the definition of functions, parameter passing, and recursion.
- Students will be able to: Apply the relational model to solving real-world problems and implement those models using SQL on standard DBMS platforms and to use a declarative query language (SQL) to elicit information from a database.
- Students will be able to: Evaluate, clean, and prepare datasets for analysis, and report the results of analyses using clear, accessible language and appropriate visualizations.
- Students will be introduced to working with data using a standard industry language (Python or R).
- Students will be introduced to ethical considerations relevant to data analysis and reporting.
For more information
Contact us at email@example.com or 312-915-6501 to schedule a meeting with one of our admissions counselors.
Course descriptions are available on LOCUS
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