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B.Eng DegreeFaculty of Faculty of Engineering & TechnologyComputer Engineering
CPE 403: Advanced Embedded Systems & Edge AI
TinyML, model quantization (int8), pruning, TensorFlow Lite Micro, neural accelerators (NPU), and low-power inference.
Course Overview
TinyML, model quantization (int8), pruning, TensorFlow Lite Micro, neural accelerators (NPU), and low-power inference. Curriculum Structure & Core Modules: • 1. The TinyML Paradigm: Edge Artificial Intelligence Constraints, Latency, Privacy, and Energy Budgets • 2. Model...
What You'll Learn
- Train, quantize (float32 to int8), and prune deep learning models for deployment on constrained microcontrollers.
- Deploy Convolutional Neural Networks (CNNs) using TensorFlow Lite for Microcontrollers (TFLM) and Edge Impulse.
- Optimize memory footprint to execute inference within restricted MCU SRAM (<256 KB) and Flash limits.
- Evaluate dedicated edge AI neural processing unit (NPU) accelerators and DSP instruction extensions (CMSIS-NN).
- Design real-time audio keyword spotting and vision anomaly detection systems on edge hardware.
Requirements
- Completion of CPE 302.
Degree Programme Curriculum Context
This course is a curriculum unit of the Bachelor of Engineering (B.Eng.) in Computer Engineering degree framework in Nigeria.
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Course Curriculum
Open-access academic curriculum. All foundational lectures available to read free.
8 Chapters
•16 Lecture
•24h
1. The TinyML Paradigm: Edge Artificial Intelligence Constraints, Latency, Privacy, and Energy Budgets: Theoretical Foundations, Mathematical Modeling & System Architecture
CPE 403 • 400 Level • Computer Engineering Chapter 1: The TinyML Paradigm: Edge Artificial Intelligence Constraints, Latency, Privacy, and Energy Budgets — Theoretical Foundations, Mathematical Modeling & System Architecture Course: CPE 403: Advanced Embedded Systems & Edge AI Curriculum: NUC-CCMAS-CPE Accreditation: COREN-CPE-OBE Standard: IEEE/ACM-CE2024 1. Pedagogical Scope...
2. The TinyML Paradigm: Edge Artificial Intelligence Constraints, Latency, Privacy, and Energy Budgets: Worked Engineering Problems, Design Computations & Simulation Protocols
CPE 403 • 400 Level • Computer Engineering Chapter 1: The TinyML Paradigm: Edge Artificial Intelligence Constraints, Latency, Privacy, and Energy Budgets — Worked Engineering Problems, Design Computations & Simulation Protocols Course: CPE 403: Advanced Embedded Systems & Edge AI Curriculum: NUC-CCMAS-CPE Accreditation: COREN-CPE-OBE Practice: COREN ERM / IEEE Design Standards...
1 hour 30 minutes
3. Chapter 1 Formative Assessment: The TinyML Paradigm: Edge Artificial Intelligence Constraint
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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
Course Includes
8 Chapters
16 Lectures
2 - 4 weeks
Skill Level advanced
Taught in English
Lifetime Access
Certification of Completion
Category: University - Computer Engineering
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