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With an associate degree from Madison College in IT-Data and 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.
Students in the IT-Data and Analytics Specialist program can attend full or part time.
The core classes unique to the IT-Data and Analytics Specialist program are offered only in person and during the day.
IT-Data and Analytics Specialist classes are offered at our Madison Truax campus.
Spring admissions: Some courses in the IT-Data and Analytics Specialist program are only offered in the daytime and may take 5 semesters to complete.
Madison College IT-Data and Analytics Specialist graduates are prepared to:
- Data Analyst
- Data Wrangler
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 Semester10-103-1331 credit10-103-1391 credit10-107-1111 credit10-151-1021 credit10-152-1203 credits10-152-2113 credits10-156-1243 credits10-804-1443 creditsSecond SemesterThird SemesterFourth SemesterRecommended Electives
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 open
- Application completion deadline is August 31, 2024
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
Official transcripts must be sent from the institutions you attended and indicate one of the following:
- High school transcript (current high school seniors may submit an in-progress transcript)
- GED/HSED transcript
- College transcript(s) showing:
- Completion of an associate degree or higher, or
- At least 30 credits completed with a minimum GPA of 2.0 on a 4-point scale
- The credits must be completed at a single college and cannot be combined with other transcripts
- Any transfer credit listed on a transcript does not count toward the 30-credit minimum
All high school and/or college transcripts are recommended to be submitted for Credit for Prior Learning evaluation.
- 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.
Once you are admitted into your program, review the Start of Semester Checklist to prepare for your first day of classes at Madison College.
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.