INTRODUCTION TO PROGRAMMING

Course Description

The course will introduce basic and fundamental programming constructs and techniques through using the C++ programming language in order to generate algorithmic solutions to problems. Upon completion of the course, students will learn an introduction to algorithms, solving problems by flowcharts and pseudo codes, header files, data types, arithmetic & logic operators, control statements (if, if/else, switch-case) and use them as inner statements, loop statements (while, do/while, for), functions, standard functions of programming language, random number generation and their area of use, user-defined functions, global and local variables, recursion, arrays, searching algorithms on arrays, sorting algorithms on arrays, pointers, pointer operators, using pointers with arrays and functions. In the laboratory hours, students are writing full programs or modifying existing programs for other solutions.

INTRODUCTION TO PROGRAMMING

Evaluation Tools (Active Term)

Course outcomes

1. 01 analyse problems and design solutions through algorithms (draw flowchart and write pseoudocode);
2. 02 define fundamental constructs of computer programming (i.e. sequence, selection and loops);
3. 03 convert algorithms into C++ compatible programming code;
4. 04 write structured programs using user defined functions;
5. 05 write structured programs using arrays;
6. 06 Identify programming constructs from given problems and create structured programming patterns when writing computer programs.

Course Syllabus

Reference Books & Course Materials

1. 01 Introducing Python: Modern Computing in Simple Packages, Bill Lubanovic, O'Reilly, 2019
2. 02 Python Programming for Beginners, Philip Robbins, Functional Software Programming, 2024

Learning Outcomes

1. L01 Implement basic sorting and searching algorithms on small arrays SOLO 4
2. L01 Differentiate between different types of input/output operations and their uses and compare different development environments SOLO 4
3. L01 Differentiate between different types of input/output operations and their uses and compare different development environments SOLO 4
4. L02 Describe different data types and their uses in programming SOLO 3
5. L02 Describe different data types and their uses in programming SOLO 3
6. L03 Implement programs using variables, arithmetic, and logical operations and analyze their effectiveness SOLO 4
7. L03 Implement programs using variables, arithmetic, and logical operations and analyze their effectiveness SOLO 4
8. L04 Compare different selection statements and explain their advantages and disadvantages in specific programming scenarios SOLO 3
9. L04 Compare different selection statements and explain their advantages and disadvantages in specific programming scenarios SOLO 3
10. L05 Classify different types of loops in Phyton SOLO 3
11. L05 Classify different types of loops in Python SOLO 3
12. L06 Differentiate between different types of input/output operations and their uses and compare different development environments SOLO 4
13. L06 Differentiate between different types of input/output operations and their uses and compare different development environments SOLO 4
14. L07 Implement user-defined functions that are modular, reusable, and well-documented, and can effectively integrate functions into larger programs SOLO 4
15. L07 Implement user-defined functions that are modular, reusable, and well-documented, and can effectively integrate functions into larger programs SOLO 4
16. L08 Apply basic operations on arrays SOLO 4
17. L08 Apply basic operations on arrays SOLO 4
18. L09 .Implement basic sorting and searching algorithms on small arrays SOLO 4

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