AI/ML Systems Engineering | Module 9: Software Development

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Programme Structure

The programme consists of 14 modules delivered across 18 live sessions:

• Module 1: Software Engineering Foundations | Wed 23 Sep 2026 9:00 AM - 11:00 AM BST

• Module 2: C/C++ Programming Fundamentals | Thu 24 Sep - Fri 25 Sep 2026 10:00 AM to 2:00 PM BST

• Module 3: Python Fundamentals | Mon 12 Oct - Tue 13 Oct 2026 10:00 AM to 2:00 PM BST

• Module 4: Rust Fundamentals | Wed 14 Oct - Thur 15 2026 10:00 AM to 2:00 PM BST

• Module 5: OSI 7-Layer Architecture | Mon 19 Oct 2026 10:00 AM - 2:00 PM BST

• Module 6: Network Programming | Tue 20 Oct 2026 1:00 PM - 5:00 PM BST

• Module 7: Data Formats and Middleware | Wed 21 Oct 2026 1:00 PM - 5:00 PM BST

• Module 8: Embedded Systems | Thu 22 Oct 2026 1:00 PM - 5:00 PM BST

• Module 9: AI/ML Systems Engineering | Wed 28 Oct 2026 10:00 AM - 2:00 PM GMT

• Module 10: Heterogeneous Data Servers | Thu 29 Oct 2026 10:00 AM - 2:00 PM GMT

• Module 11: ADAS and Automotive Software | Mon 2 Nov 2026 10:00 AM - 2:00 PM GMT

• Module 12: Networking Applications | Tue 3 Nov 2026 10:00 AM - 2:00 PM GMT

• Module 13: ADAS & Automotive Software | Wed 4 Nov 2026 10:00 AM - 2:00 PM GMT

• Module 14: Capstone Project | Mon 9 Nov - Tue 10 Nov 2026 10:00 AM to 2:00 PM BST

Register for the full 14-module training here.

Discover how modern AI and machine learning systems are engineered using Python, C++, and Rust. This practical module explores the software frameworks, tools, and technologies used to develop intelligent applications, accelerate AI workloads, and deploy scalable machine learning solutions.

Through practical examples and a hands-on project, you'll gain insight into how AI systems are developed for real-world applications across computer vision, distributed inference, and intelligent data processing.

What You Will Learn

By the end of this module, you will:

• Understand modern AI/ML software development workflows

• Explore leading Python machine learning libraries

• Learn how C++ accelerates AI applications

• Understand AI infrastructure using Rust

• Build scalable AI software pipelines

• Apply AI technologies to real-world engineering projects

Who Should Attend

• AI/ML Engineers

• Software Engineers

• Python Developers

• C++ Developers

• Data Scientists

• Systems Engineers

Topics Covered

Session 1

Python

• NumPy

• Pandas

• Scikit-Learn

• PyTorch

• TensorFlow

C++

• OpenCV

• CUDA

• TensorRT

Rust

• AI infrastructure

• Telemetry

• Distributed inference

Module Project

• Real-Time Object Detection Pipeline

Key Benefits

✔ Learn industry-standard AI development frameworks

✔ Explore computer vision and machine learning technologies

✔ Understand high-performance AI acceleration

✔ Build practical AI software solutions

✔ Gain hands-on experience with real-world AI workflows