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Main
UQU Programs
Health Informatics

Computer Programming

CS1021
3 hours English

Computer Programming

Computer Programming
1 Introduction to Python in Healthcare
2 Recap- Computer Programming using Python- Basics (Conversing with Python, Variables, expressions, and statements, Conditional execution, Functions, Iteration, Strings, Files, Lists, Dictionaries, Tuples, Regular expressions, Networked programs, Using Web Services, Object-oriented programming, Using Databases and SQL, Visualizing data)
3 Data Handling & Manipulation, Data Visualization
4 Data Pre-Processing
5 Statistical Analysis
6 Genomics and Bioinformatics with Python
7 Machine Learning for Healthcare
8 Deep Learning for Medical Imaging
9 Natural Language Processing
10 Healthcare Data Ethics and Privacy
11 Data Integration and Healthcare Systems
12 Resources and Tools
13 Practical of Python- Advanced Programming
1.1 Mapped to: K1

Define how Python is transforming the landscape of health data analysis, research, and innovation.

Teaching Strategy Interactive Academic Lectures Class and group discussions Textbook and research literature readings Individual and Group Case Studies Individual and Group Projects Inverted Class
Assessment Methods Examination
1.2 Mapped to: K1

Describe the advantages of using Python, from data manipulation to cutting-edge machine learning applications.

Teaching Strategy Interactive Academic Lectures Class and group discussions Textbook and research literature readings Individual and Group Case Studies Individual and Group Projects Inverted Class
Assessment Methods Examination
2.1 Mapped to: S1, S2

Explain data handling and manipulation tailored to healthcare & the power of libraries like NumPy and Pandas for efficient data management.

Teaching Strategy Interactive Academic Lectures Class and group discussions Textbook and research literature readings Individual and Group Case Studies Individual and Group Projects Inverted Class
Assessment Methods Examination
2.2 Mapped to: S1, S2

Practice techniques for data cleaning, pre-processing, and merging data frames to glean meaningful insights.

Teaching Strategy Interactive Academic Lectures Class and group discussions Textbook and research literature readings Individual and Group Case Studies Individual and Group Projects Inverted Class
Assessment Methods Examination
2.3 Mapped to: S1, S2

Analyze machine learning and deep learning in healthcare.

Teaching Strategy Interactive Academic Lectures Class and group discussions Textbook and research literature readings Individual and Group Case Studies Individual and Group Projects Inverted Class
Assessment Methods Examination
2.4 Mapped to: S1, S2

Prepare programs by using Python programming language.

Teaching Strategy Practical Sessions
Assessment Methods Examination Practical Exam
3.1 Mapped to: V1, V2

Work in a team to solve problems professionally.

Teaching Strategy Class and group discussions Textbook and research literature readings
Assessment Methods Assignments Presentations Student Projects
Assessment
Weight
Quiz
10%
Mid- Term Exam
20%
Assignments
10%
Presentations/ Student Project
10%
Practical Exam
10%
Final Exam
40%
Total
100%