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NTU Sem 2 17/18 (Timeline (Week 12 (HW0288: Assignment 2
Oral…
NTU Sem 2 17/18
Timeline
Week 6
HW0288: Assignment 1
- Introduction of a research report
- 500 words
Week 12
HW0288: Assignment 2
- Oral presentation on research introduction
- 5 minutes
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UNKNOWN
HW0288: Assignment 3
- E-mail analysis and writing
- 800 words
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Week 11
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CZ4071 Quiz
- Test concepts taught from Week 1 – 11
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Grading
CZ4071
- 30%: Project (2 Project?)
- 20%: Quiz
- 50%: Exam
CE3001
- 40%: Quiz (Lab 2,3,5) + Report (Lab 4)
- 60%: Exam
CE3003
- 60%: Semester-end Written Examination
- 32%: Four Lab Quizzes
- 8%: Participation in Team Based Learning Exercises
CZ4041
- 40%: Course project - Course report + presentation
- 60%: Open book final exam
HW0288
- 25%: Assignment 1
- 30%: Assignment 2
- 30%: Assignment 3
- 15%: Class participation
CE3004
- 55%: Group Assessment
- 30%: Competitive Group Assessment
- 15%: Individual Assessment
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Resources
CE4071 Network Science
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- Weeks 1, 2: Introduction, graph theory
- Weeks 3, 4: Network models
- Weeks 4-5: Properties of real-world networks
- Weeks 5-7: Network querying
- Weeks 7 -10: Network analytics
- Weeks 11, 12: Network dynamics
- Weeks 12, 13: Massive graph/network engines
CE3001
- Module-1: Introduction and background
- Module-2: Instruction set architecture design
- Module-3: Data-path and control design
- Module-4: Instruction-level parallelism (ILP)
- Module-5: Memory systems
- Module-6: Data-level parallelism
- Module-7: Multiprocessors and thread-level parallelism
- Module-8: custom computing and emerging trends:
CE3003
- Overview of ARM Processors’ Architecture and Profiles.
- Cortex-M Processor Architecture and Programming.
- Case Study: STM32F Cortex-M4 Processor (Cortex-M4F).
- Microcontroller Programming Techniques (Embedded C Programming).
- Microcontroller Programming Techniques (State Machine Programming).
- e-Learning.
- Introduction to Real-Time Operating System (Micrium uC/OS-lll).
- Application Development using Real-Time Operating System.
CZ4041
- Supervised Learning
- Classification
- Regression
- Ensemble Learning
- Dimensionality Reduction
- Unsupervised Learning
- Clustering
- Density Estimation
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