Details
1-day course
CPD Credit: 6 hours; Competence/s: 1
Course Delivery Options
Course Overview
By attending this course, delegates will gain a comprehensive understanding of how to construct robust AI models, handle complex engineering datasets, and integrate these models into engineering workflows. Attendees will gain insight into leveraging measurement data for building robust predictive models, which can outperform conventional methods in accuracy and efficiency.
Course Programme
- Building regression or classification predictive AI models using engineering measurement data
- Building a neural network for scratch
- Data handling and processing in Python
- Exploratory Data Analysis (EDA) techniques
- Evaluating AI models and understanding their limitations
Learning Outcomes/Objectives
Upon successful completion of this course, delegates should be able to:
- Learn how to build and implement predictive AI models that accurately reflect complex engineering patterns, going beyond the limitations of traditional formulas and simulations.
- Develop skills to manage and analyse complex engineering datasets.
- Combine engineering expertise with cutting-edge AI modelling capabilities
- Gain valuable hands-on experience with real-world engineering datasets, preparing you to tackle actual challenges in the field.
- Build, train, and evaluate AI models.
- Stay updated with the latest trends and advancements in AI.
Who Should Attend?
Design or maintenance engineers, senior and principal engineers and technical leads who has responsibility for innovation and implementing improvement processes in the organisation.
Course Prerequisites
We recommend that delegates are proficient in Python programming to truly benefit from this course.
We also require delegates to bring to the course a laptop/device with Python 3.6 or later or Anaconda installed. We recommend Visual Studio Code for development and git bash for running commands. Alternatively, delegates can use Google Colab (https://colab.research.google.com/) for running code notebooks (requires Google Account).
Instructions for downloading this software for free will be included in the course joining instructions. It is the delegate's responsibility to ensure that they have access to the necessary software prior to arriving.
Trainer Profile
Ali Parandeh started his career as a mechanical engineering consultant at a large multinational consultancy. Once be-coming a Chartered Engineer (CEng) member of the IMechE, he switched careers into building AI powered products and data analytic solutions.
He has also authored a book on “Building Generative AI Services with FastAPI” (O’Reilly, 2025) which teaches AI professionals how to make products from generative models across organisations.
A Microsoft Azure Certified Developer and data scientist with over 10 years of experience in consulting—Ali has a strong background in data science, machine learning, and web development having led teams from large multinational consultancies through to tech startups and AI SMEs in London.
Please contact the CPD Training Team for further information on scheduled course dates and in-company options.