AI/ML Systems Engineering | Module 9: Software Development

We offer 50% discount to students, please complete this form to avail discount.

Programme Structure

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

• • Module 1: Software Engineering Foundations | 28 Oct 2026 9:00 AM - 11:00 AM BST
  • Module 2: C/C++ Programming Fundamentals | 29 and 30 Oct 2026 10:00 AM - 2:00 PM BST
  • Module 3: Python Fundamentals | 2 and 3 Nov 2026 10:00 AM - 2:00 PM BST
  • Module 4: Rust Fundamentals | 4-5 Nov 2026 10:00 AM - 2:00 PM BST
  • Module 5: OSI 7-Layer Architecture | 6 Nov 2026 10:00 AM - 2:00 PM BST
  • Module 6: Network Programming | 9 Nov 2026 1:00 PM - 5:00 PM BST
  • Module 7: Data Formats and Middleware | 10 Nov 2026 1:00 PM - 5:00 PM BST
  • Module 8: Embedded Systems | 12 Nov 2026 1:00 PM - 5:00 PM BST
  • Module 9: AI/ML Systems Engineering | 16 Nov 2026 10:00 AM - 2:00 PM BST
  • Module 10: Heterogeneous Data Servers | 19 Nov 2026 10:00 AM - 2:00 PM BST
  • Module 11: ADAS and Automotive Software | 11 Nov 2026 10:00 AM - 2:00 PM BST
  • Module 12: IoT Applications | 26 Nov 2026 10:00 AM - 2:00 PM BST
  • Module 13: Networking Application | 30 Nov 2026 10:00 AM - 2:00 PM BST
  • Module 14: Capstone Project | 2-3^rd Dec 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