Theory:
1. Classical Information Systems: Utilizing signal processing techniques to analyze and understand the fundamental architecture of communication systems and the technical challenges that need to be overcome. This section includes topics such as Introduction to Communication Systems, Digital Modulation/Demodulation, Source Coding, Convolutional Codes, and more.
2. Quantum Information Systems: Learning the basic principles of recent quantum information technologies and their applications, such as quantum circuits, quantum computing algorithms, quantum transmission, and related topics.
3. Signal Processing: This course covers several topics and applications derived from signals and systems. These topics include Audio Signal Processing, Image Processing, Time-Frequency Analysis, and Signal Compression.

Practical Applications:
1. Using MATLAB and software-defined radio to validate the theoretical knowledge learned.
2. Simulating small-scale quantum circuits using Qiskit and Python programming packages.
3. Conducting computer-simulated experiments on audio signals, images, and communication systems.
4. Academic presentations: Split into literature reports and final projects, allowing students to practice problem analysis, academic writing, and oral presentations related to current research topics.