Post Graduate Certificate in VLSI Design

Course 1: MOS Device Physics
- In this course, you will focus on reinforcing your fundamental understanding on MOS technology. You will explore band diagrams as an approach to device physics, build your understanding on MOS capacitors as two terminal devices, and gain an in-depth introduction to advanced FETs and its applications.

Course 2: Digital VLSI Circuit Design
- In this course, you will focus on digital VLSI circuit design. You'll begin the course by exploring CMOS inverter characteristics and noise margins. You will then dive into CMOS-based combinational and sequential logic design characteristics, followed by memory and array architecture.

Course 3: Analog VLSI Circuit Design
- In this course, you will gain an in-depth understanding of analog VLSI circuit design as you explore CMOS-based single stage and differential amplifiers. You will then learn about the design and applications of operational amplifiers, voltage controlled oscillators, and phase locked loops.

Course 4: Digital System Design (FPGA based design)
- In this course, you will gain an in-depth understanding of digital system design by focusing on FPGA-based design. You'll then explore hardware description language (HDL)-based designs, static timing analysis (STA), pipelining, and parallel processing architectures.

Course 5: Mixed Signal Design (Elective)
- In this elective course, you will dive into the world of mixed signal design by focusing on switched capacitor circuits, sampling and aliasing, data converters, and integrator-based CMOS filters.

Course 6: Emerging Technologies: Accelerators for AI (Elective)
- In this elective course, you will learn about a key emerging technology, namely, accelerators for artificial intelligence (AI). You will learn the fundamentals of AI accelerator design and optimization techniques such as approximate computing, pruning and quantization. Further, you will learn about well-known commercial accelerators such as those from Google, Microsoft and NVIDIA. The computing platforms of the accelerators discussed will range from smartphone (e.g., Facebook App), embedded systems (e.g., NVIDIA Jetson) to data-center (Google’s tensor processing unit, and Microsoft’s Brainwave).