CPE 409: Artificial Intelligence & Machine Learning for Engineers

By PAMCET Learning Team

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CPE 409: Artificial Intelligence & Machine Learning for Engineers

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Enrolled Students0

Last UpdateSep 17, 2026

About Course

Heuristic search (A*), regression, SVM, random forests, deep learning (CNN/RNN), backpropagation, and engineering deployment.

Course Includes

8 Chapters
16 Lectures
24h Course Duration
Skill Level advanced
Taught in English
Lifetime Access

Course Includes

8 Chapters
16 Lectures
24h Course Duration
Skill Level advanced
Taught in English
Lifetime Access

What You'll Learn

Formulate engineering problems as state-space search graphs and solve them using A* and heuristic algorithms.
Implement supervised learning pipelines (linear/logistic regression, support vector machines, random forests) in Python.
Derive gradient descent optimization mathematics and backpropagation equations for multi-layer neural networks.
Train Convolutional Neural Networks (CNNs) for industrial vision inspection and defect classification tasks.
Evaluate machine learning models using precision, recall, F1-score, ROC curves, and cross-validation techniques.

Requirements

Completion of CPE 202 and CPE 212.

Instructor

PAMCET Learning Team

The PAMCET Learning Team is the institutional curriculum and content group behind course publishing on this platform. PAMCET (Professional and Academic Management Centre for Education and Training) is operated by Digitpen Hub Ltd, a company registered in Lagos, Nigeria. Courses credited to the PAMCET Learning Team are structured, organized, and published centrally by the platform rather than authored by a single named individual instructor — each course's syllabus, learning outcomes, and content are reviewed before publication under this institutional account. For questions about a specific course or to report a content issue, please use the platform's Help & Support or Contact Us pages.

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Course Curriculum

1. Foundations of Artificial Intelligence: Rational Agents, Search Spaces, and Problem Formulation: Theoretical Foundations, Mathematical Modeling & System Architecture

1 hour 30 minutes

2. Foundations of Artificial Intelligence: Rational Agents, Search Spaces, and Problem Formulation: Worked Engineering Problems, Design Computations & Simulation Protocols

1 hour 30 minutes

3. Chapter 1 Formative Assessment: Foundations of Artificial Intelligence: Rational Agents, Sea

CPE 409: Artificial Intelligence & Machine Learning for Engineers

Rating

Enrolled Students0

Last UpdateSep 17, 2026

About Course

Heuristic search (A*), regression, SVM, random forests, deep learning (CNN/RNN), backpropagation, and engineering deployment.

Course Includes

8 Chapters
16 Lectures
24h Course Duration
Skill Level advanced
Taught in English
Lifetime Access

Course Includes

8 Chapters
16 Lectures
24h Course Duration
Skill Level advanced
Taught in English
Lifetime Access

What You'll Learn

Formulate engineering problems as state-space search graphs and solve them using A* and heuristic algorithms.
Implement supervised learning pipelines (linear/logistic regression, support vector machines, random forests) in Python.
Derive gradient descent optimization mathematics and backpropagation equations for multi-layer neural networks.
Train Convolutional Neural Networks (CNNs) for industrial vision inspection and defect classification tasks.
Evaluate machine learning models using precision, recall, F1-score, ROC curves, and cross-validation techniques.

Requirements

Completion of CPE 202 and CPE 212.