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Printed on 1/22/2024

Data & Analytics Specialist

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10-156-3 Associate Degree (AAS) Part Time, Full Time 60 Credits Financial Aid Eligible Location*: Online

*If general education courses are required, they may be available at multiple locations.

As a Data Specialist, you’ll collect, structure, transform, quality check and analyze data from numerous sources. You’ll collaborate with decision-makers and stakeholders; create processes to gather, manage and utilize data; implement those processes using a variety of technologies to create reports and visualizations; and support data scientists, data architects and data consumers. Through their systems, analyses and communications, Data Specialists empower decisions and their organizations.

COURSE LIST

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Course list for reference only. Current students please refer to your individualized program plan or see your advisor.
**Outside effort hours are an estimate based on state standards, and may vary from person to person.

    Technical Studies (36 Credits)

    Course Title
    Course Number
    Credits
    Instructional Hours
    Outside Effort Hours**
    Prior Learning Credit Eligibility
  • Linux Essentials - Just Enough Linux
    10-150-155
    1Credit
    18
    36
    N/A

    • Instructional Hours: 18
    • Outside Effort Hours: 36
    • Course Number: 10150155
    • Credits: 1.00

    Covers Basic Linux topics including operating system basics, file management, graphic user interfaces and the command line interface.

  • Data Access for Programmers
    10-152-168
    3Credit
    72
    90
    N/A

    • Instructional Hours: 72
    • Outside Effort Hours: 90
    • Course Number: 10152168
    • Credits: 3.00

    Provides background in fundamental database concepts, design, documentation, implementation and distribution involving the relational database model. Students will create, query and update relational databases using Structured Query Language (SQL).

  • Python Data Programming
    10-156-103
    3Credit
    72
    90
    N/A

    • Instructional Hours: 72
    • Outside Effort Hours: 90
    • Course Number: 10156103
    • Credits: 3.00

    Introduction to programming using the Python language. Covers programming fundamentals including variables, datatypes, loops, conditionals, functions, and libraries. Examples focus on storage, retrieval, and manipulation of data.

  • College Success: On Course
    10-890-100
    1Credit
    18
    36

    • Instructional Hours: 18
    • Outside Effort Hours: 36
    • Course Number: 10890100
    • Credits: 1.00

    On Course helps you learn a number of proven strategies for creating greater academic, professional and personal success. You will discover how to create a rich, fulfilling life by developing new beliefs and behaviors. College Success: On Course empowers you to make wise choices in your academic and personal life which leads to improved experiences and outcomes.

  • Data Administration Techniques
    10-152-170
    3Credit
    72
    90

    • Instructional Hours: 72
    • Outside Effort Hours: 90
    • Course Number: 10152170
    • Credits: 3.00

    Covers the operation and management of client/server back-end relational databases. Topics include data definition language, table modification, creating views, indices, triggers, transactions, backup and recovery.

    Prereq: Must earn a C or better in Data Access for Programmers 10152168
  • Data Analytics, Introduction
    10-156-104
    3Credit
    72
    90
    N/A

    • Instructional Hours: 72
    • Outside Effort Hours: 90
    • Course Number: 10156104
    • Credits: 3.00

    Technologies and techniques for identifying, collecting, preparing, processing, and analyzing data relevant to business questions.

    Prereq: Python Data Programming 10156103
  • IT Career Experience
    10-107-110
    2Credit
    54
    54

    • Instructional Hours: 54
    • Outside Effort Hours: 54
    • Course Number: 10107110
    • Credits: 2.00

    Examines and identifies job-seeking, job-keeping and interviewing techniques, strategies for identifying and meeting external and internal customer needs as well as good listening skills and techniques for dealing with difficult customers. Also covers time management, team dynamics, continual improvement processes and global business practices.

    Prereq: 13 credits of IT Coursework (1015xxxx and/or 10107xxx)
  • Network Essentials
    10-150-162
    2Credit
    54
    54

    • Instructional Hours: 54
    • Outside Effort Hours: 54
    • Course Number: 10150162
    • Credits: 2.00

    Provides an introduction to networking theory and technologies, including the basics of communication, common protocols, the OSI model, network topologies, local network media, network devices, network security and networking tools. Includes more in-depth study of the components of TCP/IP, Ethernet, and wireless networks. Involves considerable time developing troubleshooting skills.

  • Data Analytics, Intermediate
    10-156-105
    3Credit
    72
    90
    N/A

    • Instructional Hours: 72
    • Outside Effort Hours: 90
    • Course Number: 10156105
    • Credits: 3.00

    Additional technologies and techniques for analyzing data, including cloud cognitive services and simple machine learning. Also examines organizational processes surrounding data as well as business analysis for data projects.

    Prereq: Data Analytics, Introduction 10156104
  • Programming in R
    10-156-106
    3Credit
    72
    90
    N/A

    • Instructional Hours: 72
    • Outside Effort Hours: 90
    • Course Number: 10156106
    • Credits: 3.00

    Programming in the R statistical computing language. Examples cover data manipulation, analysis, and plotting.

    Prereq: Data Analytics, Introduction 10156104 AND Introductory Statistics 10804189
  • ETL & Data Warehousing
    10-156-107
    3Credit
    72
    90
    N/A

    • Instructional Hours: 72
    • Outside Effort Hours: 90
    • Course Number: 10156107
    • Credits: 3.00

    Automating data pipelines. Code Extract, Transform, Load (ETL) procedures to connect a variety of data producers, repositories, and consumers. Explores various strategies and schemas for data warehousing as well as the overall flow of data through the organization and its systems.

    Prereq: Data Administration Techniques 10152170 AND Python Data Programming 10156103
  • Business Intelligence & Data Visualization
    10-156-108
    3Credit
    72
    90
    N/A

    • Instructional Hours: 72
    • Outside Effort Hours: 90
    • Course Number: 10156108
    • Credits: 3.00

    Technologies and techniques for communicating summaries, insights, and predictions gleaned from data analyses. Examines storytelling through report design, infographics, charts and graphs, purpose-built interactive dashboards, as well as custom visualizations and animations.

    Prereq: Data Analytics, Intermediate 10156105 AND ETL & Data Warehousing 10156107
  • Big Data
    10-156-109
    3Credit
    72
    90
    N/A

    • Instructional Hours: 72
    • Outside Effort Hours: 90
    • Course Number: 10156109
    • Credits: 3.00

    Explores the problems created by, strategies to tackle, and technologies to work with large data sets.

    Prereq: Data Analytics, Intermediate 10156105 AND ETL & Data Warehousing 10156107
  • Data Analytics Capstone
    10-156-110
    3Credit
    72
    90
    N/A

    • Instructional Hours: 72
    • Outside Effort Hours: 90
    • Course Number: 10156110
    • Credits: 3.00

    Complete a data project modeled as a real-world scenario. Project phases include business analysis; designing, building, and automating data infrastructure; analysis; visualization; and presenting findings to decision-makers.

    Coreq: Business Intelligence & Data Visualization 10156108

    General Studies (21 Credits)

    Course Title
    Course Number
    Credits
    Instructional Hours
    Outside Effort Hours**
    Prior Learning Credit Eligibility
  • Oral/Interpersonal Comm
    10-801-196
    3Credit
    54
    108

    • Instructional Hours: 54
    • Outside Effort Hours: 108
    • Course Number: 10801196
    • Credits: 3.00

    Focuses on developing effective listening techniques and verbal and nonverbal communication skills through oral presentation, group activity, and other projects. The study of self, conflict, and cultural contexts will be explored, as well as their impact on communication.

    Prereq: HS GPA 2.75+ OR ACPL Read 54+/Sent 83+, Next Gen Read 250+/Sent 237+, ACT Read 18+/Engl 15+ OR Read Prep 10838105/Sent Prep 74851745 OR not pursuing a degree
  • Math & Logic
    10-804-133
    3Credit
    54
    108
    N/A

    • Instructional Hours: 54
    • Outside Effort Hours: 108
    • Course Number: 10804133
    • Credits: 3.00

    Students will apply mathematical problem solving techniques. Topics will include symbolic logic, sets, algebra, Boolean algebra, and number bases.

    Prereq: Arith – HS GPA 2.75+ OR ACPL 65+, Next Gen 263+, ACT Math 18+ OR Arith Prep 10834109 OR College Tech Math 1A 10804113 OR 10804115 College Tech Math 1 OR not in a program
  • English Composition 1
    10-801-136
    3Credit
    54
    108

    • Instructional Hours: 54
    • Outside Effort Hours: 108
    • Course Number: 10801136
    • Credits: 3.00

    Learners develop and apply skills in all aspects of the writing process. Through a variety of learning activities and written documents, learners employ rhetorical strategies, plan, organize and revise content, apply critical reading strategies, locate and evaluate information, integrate and document sources, and apply standardized English language conventions.

    Prereq: HS GPA 2.75+ OR ACPL Read 54+/Sent 83+, Next Gen Read 250+/Sent 250+, ACT Read 18+/Engl 18+ OR Read Prep 10838105/Sent Prep 10831103 OR not pursuing a degree.
  • Introductory Statistics
    10-804-189
    3Credit
    54
    108
    N/A

    • Instructional Hours: 54
    • Outside Effort Hours: 108
    • Course Number: 10804189
    • Credits: 3.00

    Teaches students to display data with graphics, describe distributions with numbers, perform correlation and regression analyses, and design experiments. Students use probability and distributions to make predictions, estimate parameters and test hypotheses. They also draw inferences about relationships including ANOVA.

    Prereq: Alg – HS GPA 2.75+ OR ACPL 51+, Next Gen 250+, ACT Math 18+ OR Alg Prep 10834109 OR not pursuing a degree
  • Intro to Ethics: Theory & App
    10-809-166
    3Credit
    54
    108
    N/A

    • Instructional Hours: 54
    • Outside Effort Hours: 108
    • Course Number: 10809166
    • Credits: 3.00

    Provides a basic understanding of ethical theories and uses diverse ethical perspectives to analyze and compare relevant issues. Students will critically evaluate individual, social and/or professional standards of behavior and apply a systematic decision-making process to these situations.

    Prereq: HS GPA 2.75+ OR ACPL Read 54+/Sent 83+, Next Gen Read 250+/Sent 237+, ACT Read 18+/Engl 15+ OR Read Prep 10838105/Sent Prep 74851745 OR not pursuing a degree
  • Quantitative Reasoning
    10-804-135
    3Credit
    54
    108
    N/A

    • Instructional Hours: 54
    • Outside Effort Hours: 108
    • Course Number: 10804135
    • Credits: 3.00

    Intended to develop analytic reasoning and the ability to solve quantitative problems. Topics to be covered may include: construction and interpretation of graphs; descriptive statistics; geometry and spatial visualizations; math of finance; functions and modeling; probability; and logic. Appropriate use of units and dimensions, estimates, mathematical notation, and available technology will be emphasized throughout the course.

    Prereq: Arith – HS GPA 2.75+ OR ACPL 65+, Next Gen 263+, ACT Math 18+ OR Arith Prep 10834109 OR Not active in program
  • Intro to Psychology
    10-809-198
    3Credit
    54
    108

    • Instructional Hours: 54
    • Outside Effort Hours: 108
    • Course Number: 10809198
    • Credits: 3.00

    Focuses on the theoretical foundation of human functioning and looks at learning, motivation, emotions, personality, deviance and pathology, physiological factors and social influences. Students consider the complexities of human relationships in personal, social and vocational settings.

    Prereq: HS GPA 2.75+ OR ACPL Read 54+/Sent 83+, Next Gen Read 250+/Sent 237+, ACT Read 18+/Engl 15+ OR Read Prep 10838105/Sent Prep 74851745 OR not pursuing a degree

    Suggested Electives (3 Credits)

    Course Title
    Course Number
    Credits
    Instructional Hours
    Outside Effort Hours**
    Prior Learning Credit Eligibility
  • Technical Reporting
    10-801-197
    3Credit
    54
    108
    N/A

    • Instructional Hours: 54
    • Outside Effort Hours: 108
    • Course Number: 10801197
    • Credits: 3.00

    Focuses on the preparation and presentation of a variety of oral and written technical reports. This course is designed as an advanced communication course for students who have completed at least the prerequisite writing course and a minimum of two semesters of relevant program course work.

    Prereq: Written Communication 10801195 or English Composition 10801136 with a C or better; AND minimum 24 college credits or active in UW-O Cert.
  • HTML 5
    10-152-101
    3Credit
    72
    90
    N/A

    • Instructional Hours: 72
    • Outside Effort Hours: 90
    • Course Number: 10152101
    • Credits: 3.00

    Presents the foundation skills necessary to create Web pages using HyperText Markup Language (HTML). Covers design concepts, hypertext links, tables, frames and Cascading Style Sheets (CSS).

    Coreq: College Success: On Course 10890100 OR admitted to Career and Technical Education Instruction plan OR not pursuing a degree
  • Systems Analysis
    10-107-158
    3Credit
    54
    108

    • Instructional Hours: 54
    • Outside Effort Hours: 108
    • Course Number: 10107158
    • Credits: 3.00

    Introduces the principles and techniques of modern system analysis and design. It explores the fundamentals of traditional systems and methodologies, data flow diagrams and case tools. It also tracks the systems' development life cycle and explains the various stages.

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Expected Competencies

For more information visit our Credit For Prior Learning page.