HIT 216 - Healthcare Data Analytics
Credits: 3
1 Lecture Hours 4 Lab Hours
Prerequisites: HIT 103 and MAT 161/MAT 165
Description
This course allows students to manage, analyze, interpret and transform data. Basic concepts for machine learning are introduced. Commonly used languages and tools for data are introduced including Python and Statistical Analysis Software (SAS). Students are prepared for the competencies addressed in the Certified Healthcare Data Analyst (CHDA), including cleaning and organizing data for transformation, visualizations and validation.
Learning Outcomes
Upon completion of this course, students will:
- Assess the stakeholders and facilitate root cause identification.
- Determine analytical methods and create an analysis plan.
- Extract healthcare data from various sources using Python.
- Analyze healthcare information using industry-specific tools.
- Perform data cleaning, validation and mapping.
- Describe machine learning.
Listed Topics
- SAS and Python
- Data mining
- Data validation
- Data visualization and presentation
- Machine learning
Reference Materials
Appropriate software and textbooks
Students who successfully complete this course acquire general knowledge, skills and abilities that align with CCAC’s definition of an educated person. Specifically, this course fulfills these General Education Goals: - Quantitative & Scientific Reasoning
- Technological Competence
Approved By: Dr. Quintin B. Bullock Date Approved: 04/12/2024
Last Reviewed: 04/12/2024
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