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ML & Anomaly Detection
An advanced course on the methods and models used to detect anomalies through the application of Machine Learning.
120 hours
Artificial Intelligence and Machine Learning
120 hours
Artificial Intelligence and Machine Learning
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ABOUT THE PROGRAM

Machine learning-based anomaly detection methods and models are one step ahead of the once manual processes. ML is proven to be more effective and capable of handling larger data sets when implemented. Nonetheless, detecting anomalies successfully through ML requires theoretical and practical skills and a deep understanding of the context, especially when dealing with unstructured data (such as encoded images or languages). Nevertheless, there are benefits of applying ML-based anomaly detection in high-risk industries that need secure operations such as banking security, medicine, or manufacturing.
By undertaking this course, trainees will earn the necessary skills to harness machine learning technology to detect anomalies. Learning to identify abnormal data is valuable in deep learning, data analytics, predictions, and many more cases. Understanding the theory behind the methods is an essential role of the developer and researcher. This advanced course is for developers and BI or data engineers.

The course covers the following topics:

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The Why and How
  • Types of anomalies
  • Applications of anomaly detection
  • Types of search engines
Probability and Geometry in the use of anomaly detection
  • Common models for anomaly detection
  • Applying extreme value analysis
  • Implement anomaly detection with Python
The Linear Models
  • Linear regression models
  • The use of support vectors for anomaly detection
Additional Models
  • Using the LOF model
  • K nearest neighbor and K means models for anomaly detection
Supervised learning and classifications
  • The cost sensitive algorithm
  • The resampling and boosting methods
Working with Streams
  • Statistical process control
  • The auto regressive model
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ABOUT SOTERIA GLOBAL

SOTERIA Global is a global leader in cyber-security training solutions and services.

The cyber world is now a part of our everyday life. New technology emerges daily, and as opportunities increase, so do cyber risks. Threats constantly evolve, and we must protect our valuable assets.

A successful cyber defense has many factors, but they all have one thing in common: dedicated, skilled individuals.

SOTERIA Global experts develop our solutions and rely on the best technological assets in the market. Our impressive global presence expands over four continents, giving us access to the best cybersecurity professionals.

Our solutions range from customized training programs to developing cyber-oriented facilities, ensuring that individuals and organizations are ready to face real-world threats. Over the years, we have worked with various organizations across many sectors, giving us the skillset to shape and adapt our solutions to meet our client’s needs.

COURSE INFO

Target audience

    • Developers
    • BI Engineers
    • Data Engineers

Prerequisites

    • Python
    • Statistics

Skills Gained

    • Methods of anomaly detection
    • Derive depth-based and proximity-based detection models
    • Use wide range of data streams
    • Implement models using Python

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