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Program Overview
With an associate degree from Madison College in IT-Data & Analytics Specialist, you will have practical, applicable skills in data engineering and analytics to secure employment in this rapidly-growing specialty and thrive in most technical workplaces.
Valuable skills sought by employers include Python programming, relational database technologies/programming and data-related cloud expertise. Training blends general educational development and required IT technical skills. Graduates are prepared for data-centric jobs in information technology, government, insurance, medicine, marketing, manufacturing, service, software development, wholesale and retail sales, utilities, banking and academics.
Program Details
Students in the IT-Data & Analytics Specialist program can attend full or part time.
The core classes unique to the IT-Data & Analytics Specialist program are offered only in person and during the day.
IT-Data & Analytics Specialist classes are offered at our Madison Truax campus.
Spring admissions: Some courses in the IT-Data & Analytics Specialist program are only offered in the daytime and may take 5 semesters to complete.
Careers
Madison College IT-Data & Analytics Specialist graduates are prepared to:
- Data Analyst
- Data Wrangler
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Curriculum and Experience
Prospective program students, the information below reflects the basic requirements for students admitted for the 2023-2024 academic year. To learn more about Madison College, visit us.
Current and newly admitted program students, go directly to your Degree Progress Report to view:
- Progress toward your specific requirements
- Alternative (in lieu of) courses to meet specific requirements
If you have questions after reviewing your degree progress report (advisement report), please see Advising Services.
First SemesterSecond SemesterThird SemesterFourth SemesterElective3 creditsRecommended Electives -
Admission
To Apply
Earning a degree is a great way to advance your career development opportunities, so apply today!
International students who wish to apply for, maintain, or transfer their F-1 student visa status to Madison College are required to complete the International Admission Process.
Application Dates
Fall 2023
- Application open
- Application completion deadline is August 31, 2023
Admission Requirements
All materials must be submitted by the application deadline.
1. Admission Application
The online application allows you to save your work as you complete it and ensures fast, secure delivery to our office.
2. Education Completion
Students must submit official transcripts for one of the following:- High school transcript (current high school seniors may submit an in-progress transcript)
- GED/HSED transcript
- College transcript(s) showing:
- At least 30 credits completed with a minimum GPA of 2.0, or
- Completion of an associate degree or higher
All high school and/or college transcripts are recommended to be submitted for Credit for Prior Learning evaluation.
Additional Notes
- Class capacity is limited and is available on a first come, first served basis.
- Course prerequisites differ from admission requirements; admission into a program does not guarantee eligibility to enroll in courses or success in the program. Refer to program curriculum for details.
After Acceptance
Once you are admitted into your program, review the Start of Semester Checklist to prepare for your first day of classes at Madison College.
Questions?
Contact the Enrollment Center at EnrollmentServices@madisoncollege.edu or 608.246.6210.
Get Started!
Apply to Madison College and take the first step towards your IT-Data and Analytics Specialist career.
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Career Outcomes
Graduates of the IT-Data & Analytics Specialist are prepared to:
- Prepare data for more extensive analysis through data engineering (ETL) by writing moderately complex Python scripts.
- Discover and quantify trends in data by using industry-standard tools or writing moderately complex Python scripts.
- Solve common analytics tasks through machine learning.
- Recommend basic business solutions through a complete understanding of the data analytics life cycle.
- Communicate status and findings through professional charts and dashboards.
- Manage and store data based on usage (e.g. data lakes, relational, warehouse), both in the cloud and on-prem.
- Migrate data between data stores using Python scripts and industry-standard tools, both in the cloud and on-prem.
