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B.Sc. DegreeFaculty of Faculty of Social Sciences & MediaEconomics
Introduction to Computing (Economics BSc)
Master Introduction to Computing (Economics BSc) in University - Economics with this structured course, covering 8 modules and practice assessments.
Course Overview
Master Introduction to Computing (Economics BSc) in University - Economics with this structured course, covering 8 modules and practice assessments. Curriculum Structure & Core Modules: • 1. Introduction to Introduction to Computing (Economics BSc) • 2. Theoretical Foundations...
What You'll Learn
- Understand and apply the principles of Computer Hardware and Software Basics (BSc Econ)
- Work confidently through Operating Systems Overview (BSc Econ) and its practical applications
- Analyse real-world scenarios involving Spreadsheet Applications for Economic Analysis
- Develop applied skills in Word Processing Applications (BSc Econ)
- Critically evaluate approaches to Database Concepts (BSc Econ)
Requirements
- A foundational understanding of University - Economics concepts, from an introductory course or equivalent experience
- A computer, tablet or smartphone with a stable internet connection
- Willingness to commit regular study time to complete lessons, quizzes and assignments
Degree Programme Curriculum Context
This course is a curriculum unit of the B.Sc. Economics degree framework in Nigeria.
Earn Your Certificate
Showcase your skills with a certificate! Complete the course, submit your project, and earn your certificate. Here's a sample of what you'll receive to show off your accomplishments.
Course Curriculum
Open-access academic curriculum. All foundational lectures available to read free.
8 Chapters
•24 Lecture
•0s
1. Computational Thinking Principles & Problem Decomposition in Economics
NUC CCMAS Benchmark: CMP 103 | 100L Computational Economics Computational Thinking Principles & Problem Decomposition in Economics Abstraction, Decomposition, Pattern Recognition, Algorithmic Logic, and Structured Pseudocode Design 1. Theoretical Foundation & Conceptual Architecture **Computational Thinking** constitutes a foundational problem-solving methodology that empowers economists to formul...
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2. Algorithmic Efficiency & Asymptotic Complexity Analysis in Economic Datasets
NUC CCMAS Benchmark: CMP 103 | 100L Computational Economics Algorithmic Efficiency & Asymptotic Complexity Analysis in Economic Datasets Big-O, Big-Omega, and Big-Theta Notations, Time-Space Complexity Trade-Offs, and Empirical Scalability in Econometrics 1. Theoretical Foundation & Conceptual Architecture In computational economics, writing an algorithm that produces the correct mathematical answ...
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3. Flowcharting, State Transition Models & Decision Trees in Economic Problem Formulation
NUC CCMAS Benchmark: CMP 103 | 100L Computational Economics Flowcharting, State Transition Models & Decision Trees in Economic Problem Formulation Visual Logic Modeling, Finite State Automata, Conditional Policy Rules, and Automated Financial Underwriting 1. Theoretical Foundation & Conceptual Architecture Before an economic algorithm can be written in syntax-specific programming code, its structu...
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Academic Ecosystem & Connected Pathways
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Instructor
PAMCET Learning Team
Institutional Course Curation · PAMCET
Qualifications:
PAMCET Learning Team — Institutional Course Curation, Digitpen Hub LtdMy Skills:
- Curriculum Curation
- Course Content Review
- Learning Outcome Design
- Course Publishing & Quality Assurance
- Platform Content Operations
Reviews
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Free$24.99100% Off
Certificate available separately for $50 after completionCourse Includes
8 Chapters
24 Lectures
1 week
Skill Level intermediate
Taught in English
Lifetime Access
Certification of Completion
Category: University - Economics
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