The focus of this course is to understand the general principles behind assessing the classification performance of an AI system. We will explore, in more detail, the different available metrics for three different classification scenarios (binary, multi-class, and multilabel), the available statistical significance tests that are appropriate for classification, and some important computational complexity metrics.
On-demand - training that’s even more flexible
BSI’s on-demand courses are market-leading and available 24/7. Developed by top subject matter experts, they contain the same high-quality content you will find in our tutor-led training, but with the added benefit of being able to learn at your own pace and at any time.
How will I benefit?
This course will help you:
- Understand the general process of assessing performance in a classificationbased AI system.
- Obtain deeper knowledge of performance assessment techniques:
understanding of the main measures available to quantify performance in the context of classification. - To establish a common ground to compare and evaluate models: by
incorporating these concepts early in the design lifecycle of an AI application, you’ll be able to establish clear grounds to establish how good is the model you are working on, and to compare it to other models in a sensible way.
How will I learn?
This is an online, interactive on-demand course. Courses are available 24/7 and you can learn at any time and from any place that suits you – you just need an internet connection. You can learn as fast or as slowly as you want to. You can also take breaks at any time in the course and pick up where you left off when you are ready to continue.
During the access period, you can go back and repeat parts or all the course to refresh and reinforce what you have learned. The course content is both detailed and engaging, with explanations, activities, and knowledge checks to enhance your learning.
Who should attend?
- AI managers, team-leaders, and machine learning practitioners in general.
What will I learn?
Upon completion of this course, you will be able to:
- Understand the purpose of assessing classification performance.
- Use the all the metrics and measures mentioned in the standard to evaluate classifiers in three different scenarios: binary, multi-class, and multi-label.
- Use statistical significance testing to establish comparisons with different
models or versions of the same model. - Use metrics to evaluate the computational complexity of your model.
What is included?
On completion, you’ll be awarded an internationally recognized BSI training course certificate.
Prior knowledge and learning
The course assumes that delegates know some basic math concepts and have a basic understanding on machine learning, statistics, and probability.
Further information
You will have access to a downloadable copy of the slides used in this course to keep and refer back to. These can be used as a study guide should you choose to take the optional online exam.
Benefits of On-Demand for the individual
Convenient - Courses are available 24/7 and you can learn at any time and from any place that suits you – you just need an internet connection
Learning pace - You can learn as fast or as slowly as you want to. You can also take breaks at any time in the course and pick up where you left off when you are ready to continue
Information retention - During the access period, you can go back and repeat parts or all the course to refresh and reinforce what you have learned
High-quality materials - Developed by top subject matter experts, course content is both detailed and engaging, with explanations, activities, and knowledge checks to enhance your learning.
Related training:
You may also be interested in our ISO 42001 courses, ISO 24027(Bias in AI systems), ISO 24028 (Trustworthiness), and ISO 24029 (Robustness) for deeper understanding key concepts. You may also be interested in AI System Impact Assessment Training.
