COMP6577001- Machine Learning
Undergraduate course, BINUS University, Computer Science program, 2024
Foundations of machine learning: supervised and unsupervised methods, from data analysis and regression to clustering and dimensionality reduction.
Teaching
I designed and authored the core Artificial Intelligence curriculum at BINUS University's School of Computer Science — seven courses spanning machine learning, applied NLP, deep learning, computer vision, MLOps, signal processing, and IoT and robotics, including full course outlines, assessment (AoL) design, lecture series, and labs. The pages below show each course's session structure and assessment design. Full session materials are shared with enrolled students only.Authored curriculum — BINUS AI Program
Courses I designed and built: course outlines, assessment (AoL) design, and lecture materials.
COMP6965001- Applied Natural Language Processing
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
LLM-centric NLP: language models, tokens and embeddings, transformers, prompt engineering, retrieval-augmented generation, and fine-tuning.
COMP6966001- Applied Computer Vision
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
Computer vision with PyTorch: from neural network fundamentals to CNNs, object detection, segmentation, and generative vision.
COMP6967001- Internet of Things and Robotics
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
From sensors and ESP32 to cloud platforms and edge AI: building end-to-end intelligent IoT ecosystems.
COMP6984001- Machine Learning Operations
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
Building and operating ML systems end-to-end: experimentation, model serving, monitoring, and production discipline.
COMP6986001- Artificial Intelligence Solution
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
How AI creates measurable business value: strategy, data readiness, ethics, and leading AI-driven initiatives.
COMP6987001- Signal Processing
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
Digital signal processing in Python: acquisition, filtering, spectral and time-frequency analysis, and machine learning for signal data.
COSC6051001- Deep Learning
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
Theoretical and probabilistic foundations of deep learning: probability, distributions, neural architectures, and generative models.
Courses taught
Courses and workshops delivered across programs, including global classes.
- Artificial Intelligence
- Code Reengineering (in Java)
- Computer Vision
- Data Mining (including Global Class)
- Data Structures (in C)
- Deep Learning
- Foundations of AI
- Natural Language Processing (Global Class)
- Speech Recognition
Other courses taught
First Year Program
Workshop series, BINUS University, 2026
Preparation workshops for final year project students: algorithms, C programming, Python and machine learning, and computational thinking.
Research Methodology
Course, BINUS University, 2026
Guiding research methodology: research group formation, proposal development, and weekly progress tracking.