This program is perfect for...
- Students who want to learn data architecture, data preparation, and data optimization skills with Python as the data programming language of choice
- Students who have completed the Data Science certificate and wish to gain more specialized training in data infrastructure, data architecture, and data consolidation design and implementation using Python
- Students with basic software engineering, information technology, or database administration knowledge who are considering a career in data engineering focusing on data preparation and optimization
What you can learn.
- How to use Python and its libraries as a general programming environment
- Core numerical computation methods using Numpy
- How to use Pandas, one of the core Python data analysis packages, for performing various types of data analysis tasks
Estimated Cost Breakdown
Application & Candidacy Fee
Estimated Program Tuition
Estimated program textbook/materials
*The Application & Candidacy fee establishes your candidacy in the program for a period of time covering normal progress toward completion and may allow you to access a variety of program benefits. See our website or speak to a program representative for more information about candidacy and program benefits.
Visa Requirement Applicable
VA Benefit Eligible
The U.S. Department of Education requires colleges and universities to disclose certain information for any financial aid eligible program that, “prepares students for gainful employment in a recognized occupation”. This information includes program costs; occupations that the program prepares students to enter; occupational profiles; on time completion rate; and for the most recent award year: the number of students who have completed the program, the number of students who complete the program within the estimated duration, the job placement rate, and the median Title IV and private loan debt incurred by those who complete the program. For gainful employment information for this program, visit our Financial Aid page.