VISUAL PROGRAMMING

Course Description

This course is an introductory programming course for visual programming. Event-driven, visual and structured programming concepts will be presented. Initially, the emphasis will be on fundamentals of visual programming and basic controls. Then, advanced controls, file and database management features will be presented. Programming projects will involve common problems that require data entry, display of calculated results, conditional testing, arithmetic operations, array processing, searching, sorting, reading and writing files, and operations on databases.

VISUAL PROGRAMMING

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

1. 01 Practice fundamentals of visual programming forms and components.
2. 02 Exercise graphical user interface and experience design.
3. 03 Acquire knowledge of/skill in event-driven programming and operations.

Course Syllabus

Reference Books & Course Materials

1. 01 Beginning C# 7 Programming with Visual Studio 2017, Benjamin Perkins, Jacob Vibe Hammer, Jon D. Reid.
2. 02 Microsoft Visual C# Step by Ste, Ninth Edition, John Sharp.

Learning Outcomes

1. L01 Practice fundamentals of visual programming forms and components.
2. L02 Exercise graphical user interface and experience design.
3. L03 Acquire knowledge of/skill in event-driven programming and operations.

Program Outcomes

1. P01 Apply data science principles and techniques to challenges in real life situations, and effectively communicate their solutions.
2. P02 Identify and implement data analysis methodologies based on theoretical ideas, ethical code, and in-depth knowledge of the underlying data.
3. P03 Analyze the guiding concepts and assessment procedures for information analysis in real-life applications.
4. P04 Design and apply relevant data analysis models to find obscure solutions to business-related problems.
5. P05 Utilize modern computing techniques to handle real-world problems characterized by massive amounts of data, such as parallel and distributed computing and machine learning.
6. P06 Configure and administer the software tools required to efficiently produce usable information from any size of structured and unstructured datasets.
7. P07 Administer or manage data science tools and techniques to organize and complete projects aimed at gaining useful insight from complex data.
8. P08 Think critically and imaginatively, conceiving real-world issues from several angles, and work well in a variety of teams to solve issues cooperatively.
9. P09 Be able to effectively integrate data‐based solutions into the user environment and help non-technical professionals in exploring, visualizing, and using these solutions
10. P10 Understand their obligations under professional and ethical standards in relation to matters like data ownership and citation, data security and sensitivity and the privacy implications of data analysis.

Po-Lo Matrix