HIF 635: Health Information Analytics

Course Description

This course examines and applies analytic methods, data handling, and data cleansing techniques, strategies, and the use of Information Technology (IT) tools for data collection, data analysis, reporting and knowledge management. Applies current theoretical models and research to clinical practice to gain new knowledge from data. Requires students to use analytic tools for analyzing healthcare data with statistics, data visualization, data mining, big data, data warehousing, and report generation. Students will gain an understanding of data visualization, implanting scientific decision making, and using predictive data analytics. **Important Note: Combines Data Analytics and Advanced Data Analytics (3 credits)

Student Learning Outcomes (SLOs)

Students who successfully complete this course will be able to:

Describe the concepts of Advanced Data Analytics.
Examine the importance and value of data.
Produce models utilizing techniques of data mining and predictive analytics to produce desired outcomes.
Design visualizations to explain key outcomes.
Critique model outcomes for quality.
Learn tools for performing data analytics.
Build K-Nearest Neighbor Predictive Models.
Build Decision Tree Predictive Models.
Build Random Forests.
Use Linear Regression for continual data modeling.
Analyzed the use of Prescriptive Modeling.

Course Activities and Grading

Assignments	Weight
Discussions (100 Pts, Weeks 1-8)	20%
Projects (100 Pts, Weeks 1-8)	80%
Total	100%

Required Textbooks

Available through Charter Oak State College's Book Bundle

Kumar, Vikar (2018). Healthcare Analytics Made Simple: Techniques In Healthcare Computing Using Machine Learning and Python. 1st ed. Packt Publishing. ISBN-13: 978-1787286702

Course Schedule

Week	SLOs	Readings and Exercises	Assignments
1	1,2	Topics: Machine Learning Foundations - Introduction to Descriptive, Diagnostic, Predictive Analytics and Prescriptive Analytics Readings: Healthcare Analytics Made Simple, Chapters 1-3 Article, "Why do data initiatives fail?" Videos: Big Data will impact every part of your life The Future of Your Personal Data Improving Health Outcomes with Big Data Data Analytics Introduction Video	Review Getting Started information Review course syllabus Read assigned chapters Review the lecture material Introduce yourself in discussion forum Participate in discussion - The Value of Data Discussion Board Submit Assignment: Determining the value of your data
2	3,4,6	Topic: Introduction to Python Readings: Healthcare Analytics Made Simple, Chapters 1-3 Article, "How to Think Like a Computer Scientist" Videos: Python Introduction videos 1-4 Python Programming Tutorial #1 - Variables and Data Types Python Programming Tutorial #2 - Basic Operators and Input Python Programming Tutorial #4 - IF/ELIF/ELSE	Read assigned chapters Review the lecture material Participate in discussion – Patient Health Identification Submit Assignment: Write a python application
3	3,4,6	Topic: Python Machine Learning Readings: Healthcare Analytics Made Simple, Chapter 5 Introduction to ML with scikit-learn Videos: Scikit-Learn Course - Machine Learning in Python Tutorial	Read assigned chapter Review the lecture material Participate in discussion – Patient Health Information Submit Assignment: Python ML
4	3,4,6,7	Topic: Python for predictive analysis using classification Readings: Healthcare Analytics Made Simple, Chapter 6 Article, Sci-Kit Learn KNN Documentation Videos: Classification Models with Python How KNN Works KNN Fun and Easy Machine Learning	Read assigned chapter Review the lecture material Participate in discussion – Too Much Data Submit Assignment: Writing KNN algorithm using python and analyzing data
5	3,4,5,6,8	Topics: Python and Decisions Trees Readings: Healthcare Analytics Made Simple, Chapter 7 A Beginner’s Guide to Classification and Regression Trees Videos: Introduction to Tree Decision Making Python & Decision Trees Regression Trees Python Tutorial: Decision-Tree for Regression StatQuest: Decision Trees	Read assigned chapter Review the lecture material Participate in discussion – Healthcare Improvement Submit Assignment: Using Decision Trees
6	3,4,5,6,9	Topic: Random Forests Readings: Healthcare Analytics Made Simple, Chapter 8 Random Forest Simple Explanation Random Forest In Python Videos: Random Forests Introduction Random Forest in 7 minutes What is Random Forest Algorithm? Coding a Random Forest from Scratch in Python	Read assigned chapter Review the lecture material Participate in discussion – Changes in Quality Submit Assignment: Building Random Forests
7	3,4,6,10	Topics: Linear Regression Using Python Readings: Healthcare Analytics Made Simple, Chapter 6 Pandas Dataframe: Plot Examples with Matplotlib and Pyplot Videos: Intro to Linear Regression with Python Linear Regression Machine Learning in Python: Building a Linear Regression Model	Read assigned chapters Review the lecture material Participate in discussion – Data Visualization Submit Assignment: Linear Regression with Python
8	3,4,6,11	Topic: Working toward the goal of Prescriptive Analytics Videos: Introduction to PA How to Select the Right Prescriptive Analytics Technique for Your Business Prescriptive Analytics Guide: Use Cases & Examples PyData Paris 2016 - Prespective Analytics with Doplex and Pandas Data Analytics Part 3: Data Infrastructure	Read assigned chapters Review the lecture material Participate in discussion – Predicting the Future Submit Assignment - Cutting Through the Hype

COSC Accessibility Statement

Charter Oak State College encourages students with disabilities, including non-visible disabilities such as chronic diseases, learning disabilities, head injury, attention deficit/hyperactive disorder, or psychiatric disabilities, to discuss appropriate accommodations with the Office of Accessibility Services at OAS@charteroak.edu.

COSC Policies, Course Policies, Academic Support Services and Resources

Students are responsible for knowing all Charter Oak State College (COSC) institutional policies, course-specific policies, procedures, and available academic support services and resources. Please see COSC Policies for COSC institutional policies, and see also specific policies related to this course. See COSC Resources for information regarding available academic support services and resources.