Teaching

I designed and authored the core Artificial Intelligence curriculum at BINUS University's School of Computer Science — eight 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.

Signal Processing (COMP6987001)

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.

Machine Learning Operations (COMP6984001)

Graduate course, BINUS University, 2026

Building and operating ML systems end-to-end: experimentation, model serving, monitoring, and production discipline.

Internet of Things and Robotics (COMP6967001)

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.

Deep Learning Foundations (AI3DL001)

Undergraduate course, BINUS University, Artificial Intelligence Program (Semester 3), 2026

Theoretical and probabilistic foundations of deep learning: probability, distributions, neural architectures, and generative models.

Applied Natural Language Processing (COMP6965001)

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.

Applied Computer Vision (COMP6966001)

Undergraduate course, BINUS University, Artificial Intelligence Program, 2026

Computer vision with PyTorch: from neural network fundamentals to CNNs, object detection, segmentation, and generative vision.

Artificial Intelligence Solution (COMP6986001)

Undergraduate course, BINUS University, Artificial Intelligence Program, 2026

How AI creates measurable business value: strategy, data readiness, ethics, and leading AI-driven initiatives.

Machine Learning (COMP6577001)

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.

Courses taught

Courses and workshops delivered as a lecturer, based on official or shared outlines.

Research Methodology

Course, BINUS University, 2026

Guiding research methodology: research group formation, proposal development, and weekly progress tracking.

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.

Other courses taught

Data Structures
Computer Vision
Data Mining (including Global Class)
Code Reengineering
Foundations of AI