CSE-101, Introduction to Computing
Fall 2026
SMCS, IBA Karachi
Program
BS(CS)
Department Offering
Class Number
Faculty
Email
SMCS
Dr. Farrukh Hasan Syed
fhsyed@iba.edu.pk
Class Details
Session Days and Timings
Friday and Saturday
Class Location
Please see UMS
Credit Hours
3+0
Counselling hours
Tuesdays (2:30-4:30)
Wednesdays (1:00-3:00)
Course Description
The objective of the course is to provide a broad introduction to the field of computing.
• How do computers solve problems?
• How does a computer actually work?
• How do computers communicate and store information?
• How is modern software built and where is computing heading?
Course Learning Outcomes (CLOs)
Faculty should list the course learning objectives.
CLO 1 (Map the CS Discipline): Identify foundational sub-fields of Computer Science (e.g. Architecture, OS, DSA,
Networks, AI) and understand their roles in the degree roadmap.
CLO 2 (Explain Hardware/Software Abstractions): Describe how high-level logical tasks translate into electronic logic
gates, memory lookups, and system instructions.
CLO 3 (Learn and apply problem solving techniques): Learn to solve problems using structured and algorithmic problemsolving techniques.
s
Teaching and Learning Methodology
•
•
Interactive class and peer discussions using a semi-flipped classroom approach.
Assessed student participation and engagement.
Page 1 of 4
•
Graded in-class learning activities.
Emphasis on extensive reading, summarization, explanation, and critical elaboration.
•
Textbook and Pre-Course Reading Material
Recommended Books:
1. Computer Science: An Overview by J. Glenn Brookshear & Dennis Brylow (2022)
2. Invitation to Computer Science by G. Michael Schneider & Judith Gersting
3. Computer Science: An interdisciplinary approach by Sedgewick & Wayne
4. The Elements of Computing Systems: Building a modern computer from first principles by Noam Nisan & Shimon
Schocken
Prerequisite Skills and Knowledge to take this Course
NA
Assessment
Weight
Quizzes
10%
Class Participation
10%
Project
10%
Midterm Exam
30%
Final exam
40%
Total
100
Tentative Weekly Schedule
Week
Topic
Recomm.
Reading
CLO
Mapping
Details
1
Introduction to
Computing
What is computing? History & evolution. Computing in daily life.
CS disciplines, careers, CS curriculum roadmap, human-computer
analogy, introduction to problem solving.
2
Computational
Thinking
Decomposition, pattern recognition, abstraction.
Analytical vs algorithmic vs empirical reasoning. Divide-andconquer. Heuristic examples (Scrabble/Game AI).
Page 2 of 4
3
Problem Solving
& Algorithms
Problem solving process, algorithms, pseudocode basics.
Flowcharts, variables, I/O, selection, iteration, recursion.
4
Models of
Computation
Finite State Machines, FSM examples.
Trees & graphs introduction, Turing machines, limits of
computation.
5
Data
Representation
Number systems (decimal, binary, octal, hexadecimal). Number
conversions.
Binary arithmetic
6
Digital
Representation
of Information
Character encoding (ASCII, Unicode). Images and pixels.
Audio/video representation, compression (lossless vs lossy).
7
Digital Logic
Boolean algebra, logic gates, truth tables.
Combinational circuits, introduction to sequential logic, Logisim
activity.
8
Computer
Organization
Von Neumann architecture, CPU, ALU, Control Unit.
Registers, cache, RAM, storage, GPUs/TPUs, instruction cycle.
9
Midterm
10
Break
11
Operating
Systems
Purpose of OS, processes vs threads, scheduling concepts.
Memory management, virtual memory, file systems, user vs
kernel mode.
12
Networks &
Internet
Data communication, network types, topologies.
OSI, TCP/IP, DNS, HTTP/HTTPS, cloud computing.
13
Data
Management
Data vs information, files, databases, relational model.
Tables, keys, SQL concepts, NoSQL overview.
14
Software
Development
SDLC phases.
Open-source software, walk through SDLC using example project.
15
Cybersecurity
CIA triad, authentication vs authorization, password security.
Encryption concepts, malware, phishing.
16
Emerging Trends
Course review and discussion on emerging technologies/
applications/ paradigms, etc.
Technology & Innovation
The course integrates contemporary information and communication technologies to enhance teaching, learning, and
student engagement. Students are exposed to emerging digital tools and technology-driven practices relevant to the
Page 3 of 4
discipline. Emphasis is placed on the effective and responsible use of technology for problem-solving, collaboration,
information management, and innovation.
Also pen and paper.
Experiential Learning Exposure(s)
The course includes hands-on exercises and a practical project where students design, develop and present a computer
application that is related to a real world application.
Social Contribution / Impact
This course supports SDG 4: Quality Education.
Use of Artificial Intelligence (AI)
Students are allowed to use AI to complement their learning.
For all assessments, the use of AI is permitted only when explicitly allowed by the instructor and for explicitly stated purposes.
Academic Conduct and Attendance Policy
IBA policy
Plagiarism Policy
IBA policy
In case of collusion, everyone involved directly or indirectly will be penalized irrespective of who did the original work.
Re-exam policy
There will be no re-exam for midterm. Student will be awarded marks based on percentage of marks obtained in quizzes +
final exam.
Page 4 of 4