Semester : Odd
Academic Year : 2026/2027
Venue : Informatics Lab
Every : Thursday (1.30 - 4.00 PM) for Class "31"
Saturday (10.30 AM - 1.00 PM) for Class "47"
Week 1 (Semester Program Plan, Study Contract, Book and Supporting Materials) Download
Week 2 (Able to understand the anatomy of the IoT system as a whole) Download
Week 3 (Able to set up a working environment and program basic digital I/O) Download
Week 4 (Able to perform data acquisition using sensors) Download
Week 5 (Able to control external devices via actuators) Download
Week 6 (Able to connect devices to the Internet network) Download
Week 7 (Able to implement MQTT protocol for bandwidth efficiency) Download
Week 8 (Mid Exam) Download
Week 9 (Able to integrate IoT hardware with Web ecosystem) Download
Week 10 (Able to visualize IoT data in the form of a dashboard) Download
Week 11 ([ML Enrichment 1] Able to design dataset collection flows for ML models) Download
Week 12 ([ML Enrichment 2] Able to train and embed basic classification ML) Download
Week 13 (Capable of performing inference locally (Edge) or via Cloud API) Download
Week 14 (Able to design energy efficient IoT Nodes for field implementation) Download
Week 15 (Integrated Final Project Development (Assembly & Coding Stage)) Download
Week 16 (Final Exam) Download
Semester : Odd
Academic Year : 2026/2027
Venue : Informatics Lab
Every : Friday (4.30 - 6.30 PM) for Class "34"
Friday (07.30 - 09.30 AM) for Class "31"
Week 1 (Semester Program Plan, Study Contract, Book and Supporting Materials) Download
Week 2 (Able to explain the basic concepts of Edge Computing, IoT, and TinyML) Download
Week 3 (Able to setup development environment for ESP32) Download
Week 4 (Capable of performing sensor data acquisition via ESP32) Download
Week 5 (Able to send acquisition data to Cloud or Data Logger) Download
Week 6 (Able to understand Machine Learning pipelines for Edge Devices) Download
Week 7 (Capable of performing data pre-processing and feature extraction) Download
Week 8 (Mid Exam) Download
Week 9 (Capable of training and evaluating small-scale Neural Network (NN) models) Download
Week 10 (Capable of performing model optimization and quantization for ESP32) Download
Week 11 (Able to deploy models (C++ Library) into ESP32) Download
Week 12 (Capable of executing Local Inferencing of sensor data in real-time) Download
Week 13 (Able to design Edge-to-Cloud actuation based on inference results) Download
Week 14 (Able to design power-saving systems (Low Power Edge IoT)) Download
Week 15 (Integrated Final Project Development) Download
Week 16 (Final Exam) Download
Semester : Odd
Academic Year : 2026/2027
Venue : Informatics Lab
Every : Tuesday (4.30 - 6.30 PM) for Class "31"
Wednesday (7.30 - 9.30 AM) for Class "34"
Week 1 (Semester Program Plan, Study Contract, Book and Supporting Materials) Download
Week 2 (Introduction of Data Mining) Download
Week 3 (Getting to Know Your Data) Download
Week 4 (Output: Knowledge Representation) Download
Week 5 (Data Preprocessing) Download
Week 6 (Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods) Download
Week 7 (Classification: Advanced Methods) Download
Week 8 (Mid Exam) Download
Week 9 (Cluster Analysis: Basic Concepts and Methods) Download
Week 10 (Advanced Cluster Analysis) Download
Week 11 (Outlier Detection) Download
Week 12 (Data Mining Trends and Research Frontiers) Download
Week 13 (Introduction to Weka) Download
Week 14 (Writing New Learning Schemes) Download
Week 15 (Exercises for the Weka Explorer) Download
Week 16 (Final Exam) Download
Semester : Odd
Academic Year : 2026/2027
Venue : Informatics Lab
Every : Monday (1.30 - 4.00 PM) for Class "42"
Tuesday (1.30 - 4.00 PM) for Class "43"
Thursday (4.30 - 6.30 PM) for Class "45"
Friday (1.30 - 4.00 WIB) for Class "44"
Week 1 (Semester Program Plan, Study Contract, Book and Supporting Materials) Download
Week 2 (Understand the foundations of data communications, OSI, and TCP/IP) Download
Week 3 (Getting to Know Your Data) Download
Week 4 (Output: Knowledge Representation) Download
Week 5 (Data Preprocessing) Download
Week 6 (Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods) Download
Week 7 (Classification: Advanced Methods) Download
Week 8 (Mid Exam) Download
Week 9 (Cluster Analysis: Basic Concepts and Methods) Download
Week 10 (Advanced Cluster Analysis) Download
Week 11 (Outlier Detection) Download
Week 12 (Data Mining Trends and Research Frontiers) Download
Week 13 (Introduction to Weka) Download
Week 14 (Writing New Learning Schemes) Download
Week 15 (Exercises for the Weka Explorer) Download
Week 16 (Final Exam) Download
Semester : Odd
Academic Year : 2026/2027
Venue : C 507
Every : Saturday (1.30 - 3.00 PM) for Class "52"
Week 1 (Semester Program Plan, Study Contract, Book and Supporting Materials) Download
Week 2 (Introduction to Data Security & Cybersecurity) Download
Week 3 (Cyber Threat and Attack Landscape) Download
Week 4 (Basics of Cryptography in Cybersecurity) Download
Week 5 (Symmetric Cryptography and Hash Functions) Download
Week 6 (Asymmetric Cryptography & Public Key Infrastructure) Download
Week 7 (Authentication & Zero Trust Architecture) Download
Week 8 (Mid Exam) Download
Week 9 (Operating System & Database Security) Download
Week 10 (Web Application Security) Download
Week 11 (Security in Smart Systems and IoT) Download
Week 12 (Security Risk and Incident Management) Download
Week 13 (Introduction to Digital Forensics) Download
Week 14 (Cyber Standards, Ethics, and Law) Download
Week 15 (Review of Future Cybersecurity Trends) Download
Week 16 (Final Exam) Download