Aim of the course:

This flexible microdegree equips you with the systematic knowledge and practical skills to develop artificial intelligence chips and design, optimise and integrate complete AI hardware systems. Gain hands-on experience in hardware–software co-design, system architecture and AI deployment while building future-ready skills that Europe's digital transformation increasingly demands. Developed in response to industry needs, the programme prepares you for careers in AI engineering, embedded systems, chip design and system architecture.

Target group:

Company experts, engineers and chip designers who develop or select chips for running AI applications.

Prerequisites:

Bachelor's degree. Prior knowledge of machine learning and digital electronics design.

Topics:

IAS0650 Chips for AI
IAS0640 HDL in Digital Systems Design

Study results:

1. Compares CNNs, RNNs, and Transformers and understands their impact at the operator level.
2. Distinguishes between Edge and Cloud AI trade-offs, including latency, privacy, cost, energy consumption, and availability.
3. Applies quantization and pruning techniques to reduce latency, memory usage, and energy consumption while maintaining accuracy.
4. Compares CPUs, GPUs, TPUs, and ASIC accelerators for AI workloads.
5. Explains the trade-offs between FPGA- and ASIC-based solutions for AI acceleration and demonstrates proficiency in FPGA design methodology.
6. Understands the hardware architecture of AI System-on-Chip (SoC) solutions, can use the SystemVerilog hardware description language, and understands the key stages of chip design (synthesis and physical implementation).

Graduation document:

TalTech certificate

Language:

English

Lecturer:

Sub courses:

1. HDL in Digital Systems Design
2. Chips for AI

Registration deadline:

11.01.2027 23:59

Timetable: