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Syllabus ( INF 211 )

   Basic information
Course title: Algorithms and Programming I
Course code: INF 211
Lecturer: Assist. Prof. Tuba GÖZEL
ECTS credits: 6
GTU credits: 4 ()
Year, Semester: 1, Fall
Level of course: First Cycle (Undergraduate)
Type of course: Compulsory
Language of instruction: English
Mode of delivery: Face to face , Lab work
Pre- and co-requisites: none
Professional practice: No
Purpose of the course: Provide students knowledge and skills about algorithms and programming.
Understand programming design and use the basic programming constructs.
Obtain necessary technical and practical knowledge in programming.
Write small-scale C programs.
   Learning outcomes Up

Upon successful completion of this course, students will be able to:

  1. Understand and use the programming languages.

    Contribution to Program Outcomes

    1. Obtain basic knowledge of Electronics Engineering.
    2. Employ modern techniques and operate technical devices

    Method of assessment

    1. Written exam
    2. Homework assignment
    3. Laboratory exercise/exam
    4. Term paper
  2. Provide knowledge and skills about algorithm structures

    Contribution to Program Outcomes

    1. Obtain basic knowledge of Electronics Engineering.
    2. Employ modern techniques and operate technical devices

    Method of assessment

    1. Written exam
    2. Homework assignment
    3. Laboratory exercise/exam
  3. Obtain necessary technical and practical knowledge in Programming languages.

    Contribution to Program Outcomes

    1. Design and conduct experiments, as well as analyze and interpret data
    2. Employ modern techniques and operate technical devices

    Method of assessment

    1. Written exam
    2. Homework assignment
    3. Laboratory exercise/exam
    4. Term paper
   Contents Up
Week 1: Introduction to Python
Week 2: Branching and Iteration
Week 3: String Manipulation.
0. Homework (not evaluated).
Week 4: Functions
1. Homework
Week 5: Tuples, Lists and Dictionaries
1. Project
Week 6: Testing, Debugging
2. Homework
Week 7: Exceptions, Assertions
3. Homework
Week 8: Mid-term.
Week 9: Object Oriented Programming
2. Project
Week 10: Python Classes and Inheritance
4. Homework
Week 11: Algorithmic Complexity
5. Homework
Week 12: Searching and Sorting Algorithms .
3. Project
Week 13: Plotting.
6. Homework
Week 14: Project.
4. Project
Week 15*:
Week 16*: Final exam
Textbooks and materials: Mark Lutz, Programming Python: Powerful Object-Oriented Programming Fourth Edition
Harvey M. Deitel, Paul J. Deitel, C How to Program, Prentice Hall, Seventh Edition.
Recommended readings: Introduction to algorithms / Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest. c1990.
Jeri R. Hanly and Elliot B. Koffman, Problem Solving and Program Design in C, Pearson Education
  * Between 15th and 16th weeks is there a free week for students to prepare for final exam.
Assessment Up
Method of assessment Week number Weight (%)
Mid-terms: 8 30
Other in-term studies: 0
Project: 3, 5, 7, 9, 11, 14 10
Homework: 2, 4, 6, 8, 10, 13 10
Quiz: 0
Final exam: 16 50
  Total weight:
(%)
   Workload Up
Activity Duration (Hours per week) Total number of weeks Total hours in term
Courses (Face-to-face teaching): 3 14
Own studies outside class: 1 14
Practice, Recitation: 2 13
Homework: 3.5 6
Term project: 8 4
Term project presentation: 0 0
Quiz: 0 0
Own study for mid-term exam: 5 1
Mid-term: 1 1
Personal studies for final exam: 6 1
Final exam: 3 1
    Total workload:
    Total ECTS credits:
*
  * ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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