Course Detail

 Course Name Computational thinking, programming & problem-solving Course Code 24AIM101 Program M.Sc. in Social Data Science & Policy Semester I Credits 3 Campus Coimbatore

Syllabus

Unit 1

Computational thinking, critical thinking, data representation, abstraction, decomposition- breaking problems into parts, basic data types, pseudocode, algorithms-methods to solve the problems, brute-force or exhaustive search problems, divide and conquer problems

Unit 2

Computational thinking using spreadsheets, basic operations, cell references – relative and absolute, lookup operations, implement fractals – newton, Sierpinski triangle, L-system Micro-credentials, solve calculus-based problems using spreadsheet, using spreadsheet for solving probability related problems

Unit 3

Computational thinking using matlab, basic operations, plotting of vectors, array and matrix operations, implement fractals – newton, Sierpinski triangle, L-system fractals, solve calculus based problems using matlab, using matlab for solving probability related problems

Course Objectives and Outcomes

Course Objectives:

• Enable students to effectively apply computational thinking principles, including critical thinking, data representation, abstraction, decomposition, and problem-solving algorithms to solve complex engineering problems.
• Equip students with skills to proficiently use spreadsheet tools for implementing and solving problems, such as fractals, calculus, and probability, through basic operations, cell references, and lookup operations.
• Foster students’ competence in MATLAB, covering basic operations, vector plotting, array and matrix operations, for implementing and solving mathematical problems, including Micro-credentials, calculus-based challenges, and probability-related scenarios.
• Facilitate the integration of computational thinking across platforms, to solve diverse engineering problems, fostering a holistic understanding of computational methodologies in practical applications.

Course Outcomes:
After completing this course, students should be able to

• CO1: Proficiently apply computational thinking, including critical thinking, data representation, abstraction, and decomposition, to solve complex engineering problems.
• CO2: Effectively use spreadsheet to solve problems related to Micro-credentials, calculus, and probability.
• CO3: Apply computational algorithms using MATLAB, including basic operations, vector plotting, array and matrix operations, to solve mathematical problems such as Micro-credentials, calculus-based problems, and probability-related challenges.
• CO4: Integrate computational thinking skills across multiple domains, fostering a holistic understanding of computational methods in real-world applications.

CO-PO Mapping

 PO PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2 PSO3 CO CO1 3 3 3 3 1 – – – 2 2 – 2 2 1 2 CO2 3 3 3 2 1 – – – 2 2 – 2 2 1 2 CO3 3 3 3 2 1 – – – 2 2 – 2 2 1 2 CO4 3 3 3 2 1 – – – 2 2 – 2 2 1 2

Text Books / References

• Ferragina P, Luccio F. Computational Thinking: First Algorithms, Then Code. Springer; 2018
• Beecher K. Computational Thinking: A beginner’s guide to Problem-solving and Programming.
• BCS Learning & Development Limited; 2017.
• Irfan Turk, Matlab programming, 2018
• Noreen Brown, Beginning Excel 2019, 2019.

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