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CIT108Sciences2 Unitsintermediate

Problem-Solving Algorithm

This course introduces students to problem-solving strategies using computational approaches. It covers algorithms, heuristics, and the problem-solving process, emphasizing the role of algorithms, flowcharts, and pseudocode. The course explores implementation strategies like recursion, control structures, decomposition, and modularization. Students will learn program testing and debugging techniques to ensure efficient and reliable solutions. The course aims to equip learners with technical skills for handling routine problems and representing solutions in a computer-enabled format.

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156h
Study Time
13
Weeks
12h
Per Week
basic
Math Level
Course Keywords
Problem SolvingAlgorithmsFlowchartsPseudocodeDebugging

Course Overview

Everything you need to know about this course

Course Difficulty

Intermediate Level
Builds on foundational knowledge
65%
intermediate
➕
Math Level
Basic Math
🔬
Learning Type
Hands-on Practice

Course Topics

Key areas covered in this course

1

Problem Solving Strategies

2

Algorithms

3

Heuristics

4

Flowcharts

5

Pseudocode

6

Implementation Strategies

7

Testing

8

Debugging

9

Decomposition

10

Modularization

Total Topics10 topics

Ready to Start

No specific requirements needed

This course is designed to be accessible to all students. You can start immediately without any prior knowledge or specific preparation.

Assessment Methods

How your progress will be evaluated (3 methods)

assignments

Comprehensive evaluation of course material understanding

Written Assessment

tutor-marked assessments

Comprehensive evaluation of course material understanding

Written Assessment

final examination

Comprehensive evaluation of course material understanding

Computer Based Test

Career Opportunities

Explore the career paths this course opens up for you

Software Developer

Apply your skills in this growing field

Programmer

Apply your skills in this growing field

Systems Analyst

Apply your skills in this growing field

Software Engineer

Apply your skills in this growing field

Data Analyst

Apply your skills in this growing field

Industry Applications

Real-world sectors where you can apply your knowledge

Software DevelopmentData ScienceWeb DevelopmentIT ConsultingComputer Programming

Study Schedule Beta

A structured 13-week journey through the course content

Week
1

Module 1: Problem Solving Strategies

8h

Unit 1: Roadmap to Solving Problems: Typical Strategies

4 study hours
  • •Understand problem-solving strategies.
  • •Define algorithm and heuristic.
  • •Describe common problem-solving strategies.
  • •Explain roadblocks to effective problem-solving.

Unit 2: The Problem Solving Process

4 study hours
  • •Understand the computer as a model of computation.
  • •Explain the problem-solving process.
  • •Apply the problem-solving paradigm to routine problems.
Week
2

Module 1: Problem Solving Strategies

4h

Unit 3: Computational Approaches to Problem Solving

4 study hours
  • •Describe computational approaches to problem-solving.
  • •Classify computational approaches.
  • •Evaluate computational approaches.
  • •Apply a computational approach to solve a problem.
Week
3

Module 2: Role of Algorithms in Problem Solving

4h

Unit 1: Abstraction as a Problem Solving Tool

4 study hours
  • •Define abstraction as a problem-solving aid.
  • •Understand the importance of abstraction.
  • •Describe how to perform abstraction.
  • •Explain types of abstraction.
Week
4

Module 2: Role of Algorithms in Problem Solving

4h

Unit 2: Algorithms

4 study hours
  • •Understand the concept of algorithms.
  • •Appreciate the need for algorithms.
  • •Describe algorithm development steps.
  • •Develop algorithms for simple problems.
  • •Evaluate algorithm efficiency.
Week
5

Module 2: Role of Algorithms in Problem Solving

4h

Unit 3: Flowcharts

4 study hours
  • •Understand flowchart concepts.
  • •Apply symbols and notations.
  • •Differentiate flowchart types.
  • •Understand flowchart design conditions.
  • •Undertake simple flowcharting problems.
Week
6

Module 2: Role of Algorithms in Problem Solving

4h

Unit 4: Pseudocode

4 study hours
  • •Understand pseudocode relevance.
  • •Apply pseudocode rules.
  • •Demonstrate pseudocode skills.
  • •Address simple problems.
Week
7

Module 3: Implementation Strategies

4h

Unit 1: Recursion

4 study hours
  • •Understand recursion.
  • •Apply recursion to implement a solution.
  • •Avoid circularity in recursion.
  • •Explain recursion workings and overhead.
Week
8

Module 3: Implementation Strategies

4h

Unit 2: Control Structure: Selection and Iteration

4 study hours
  • •Explain control structures.
  • •Apply selection control.
  • •Implement solutions using iteration.
  • •Combine control structures.
Week
9

Module 3: Implementation Strategies

4h

Unit 3: Decomposition and Modularisation

4 study hours
  • •Appreciate decomposition and modularisation.
  • •Understand decomposition approaches.
  • •Justify modularisation motivations.
  • •Describe modularisation properties.
  • •Discuss modularisation advantages.
Week
10

Module 3: Implementation Strategies

4h

Unit 4: Testing and Debugging

4 study hours
  • •Define and classify program testing.
  • •Explain testing properties.
  • •Appreciate the need for testing.
  • •Understand debugging process and errors.
  • •Apply debugging strategies.
Week
11

Module 1: Problem Solving Strategies

4h

Unit 1: Review of Problem Solving Strategies

4 study hours
  • •Review problem-solving strategies and algorithm design.
  • •Practice algorithm development for various problems.
Week
12

Module 2: Role of Algorithms in Problem Solving

4h

Unit 2: Mastering Flowcharts and Pseudocode

4 study hours
  • •Consolidate understanding of flowcharts and pseudocode.
  • •Apply flowcharts and pseudocode to solve practical problems.
Week
13

Module 3: Implementation Strategies

4h

Unit 3: Advanced Implementation and Debugging Techniques

4 study hours
  • •Practice implementation strategies, testing, and debugging.
  • •Work on assignments and prepare for final examination.

This study schedule is in beta and may not be accurate. Please use it as a guide and consult the course outline for the most accurate information.

Course PDF Material

Read the complete course material as provided by NOUN.

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Study Tips & Exam Preparation

Expert tips to help you succeed in this course

1

Create flowcharts and pseudocode for key algorithms.

2

Practice solving problems using different computational approaches.

3

Review and understand the different types of control structures.

4

Focus on testing and debugging techniques.

5

Understand the concepts of decomposition and modularization.

6

Practice past examination questions and tutor-marked assignments.

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