Data Science and Analysis A.A.S.

Program Description

The A.A.S. Degree in Data Science and Analysis provides a comprehensive foundation in technical and analytical skills for data collection, cleaning, modeling, and presentation. Students learn industry-standard programming languages and tools to create and present data analytics, predictive models, and visualizations. Students develop effective communication skills and strategies for impactful data-driven presentations. Some of the courses in the program are cross-listed with continuing education. This degree prepares students for a variety of entry-level positions in the field of data science and analysis.

The degree program builds upon the Data Science Certificate. In completing this degree, students will be able to prepare for the CompTIA Data+, Microsoft Power BI Analyst, and Tableau Certified Data Analyst certification exams.

Program Outcomes

Graduates of the Data Science, A.A.S will be able to:

• Analyze, design, and develop a computer information system in a real-world scenario.
• Conceptualize, design, and diagram possible solutions to logical data-driven problems.
• Apply a variety of information technology concepts and tools to the management of files and large data sets.
• Analyze data using appropriate programming languages and environments for data science.
• Create reports and visualizations that communicate the findings of complex analyses.
• Communicate clearly and in a professional manner within the information technology environment.

Sequence of Study

Below are the required courses for your program arranged in a suggested sequence. Please note that the sequence does not include developmental coursework. See Academic Preparation  for the developmental course sequence if applicable to you.

Required Courses

• EGL-1010 Composition I: Expository Writing Credits: 3 (English Gen. Ed. Requirement)
• INT-1010 Introduction to Information Technology Credits: 3 (Comp. Literacy Institutional Requirement)
• MAT-1140 Introduction to Statistics Credits: 3 (Math Gen. Ed. Requirement)
• PAS-1000 First Year Experience Credits: 1 (Institutional Requirement)
• INT-1111 Programming Logic and Design Credits: 3 (Program Requirement)

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• PHL-1090 Introduction to Logic Credits: 3 (Arts/Humanities Gen. Ed. Requirement)
• NTR-1010 Introductory Nutrition Credits: 3 (Science No Lab Gen Ed. Requirement)
• EGL-1340 Writing About Technical Topics Credits: 3 (English Gen. Ed. Requirement)
• PSY-1010 General Psychology Credits: 3 (Social Science Gen. Ed. Requirement)

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• INT-2080 Fundamentals of Database Management Credits: 3 (Program Requirement)
• INT-2081 Introduction to Oracle Credits: 3 (Program Requirement)
• INT-2140 Problem Solving with Spreadsheets Credits: 3 (Program Requirement)
• INT-2082 Advanced Oracle and PL/SQL Credits: 3 (Program Requirement)
• INT-2150 Problem Solving with Databases Credits: 3 (Program Requirement)
• INT-2180 Data Mining, Manipulation and Analysis Credits: 3 (Program Requirement)
• INT-2240 Introduction to Python Credits: 3 (Program Requirement)
• INT-2280 Data Visualization and Communication Credits: 3 (Program Requirement)

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• INT-2580 Big Data Analytics and Modeling Credits: 4 (Program Requirement)
• INT-2840 Systems Analysis and Project Management Credits: 4 (Program Requirement)

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• INT-1930 Microsoft Azure Fundamentals Credits: 3 (Program Elective) or
• INT-2715 AWS Cloud Practitioner Credits: 3 (Program Elective) or
• INT-2930 Information Technology Internship III Credits: 3 (Program Elective)

Program Total: 60 Credits

Need Help?

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