Duration
The programme is available in two duration modes:
Fast track - 1 month
Standard mode - 2 months
Course fee
The fee for the programme is as follows:
Fast track - 1 month: £140
Standard mode - 2 months: £90
Certificate Programme in Time Series Anomaly Detection
Unlock the secrets of detecting anomalies in time series data with our comprehensive anomaly detection training program. Ideal for data scientists, analysts, and researchers, this course covers advanced techniques for identifying outliers and irregular patterns in time series data. Gain practical skills in anomaly detection algorithms and enhance your data analysis capabilities. Take your data science expertise to the next level and make informed decisions based on accurate insights. Don't miss this opportunity to master time series anomaly detection!
Start your learning journey today!
The programme is available in two duration modes:
Fast track - 1 month
Standard mode - 2 months
The fee for the programme is as follows:
Fast track - 1 month: £140
Standard mode - 2 months: £90
Our Certificate Programme in Time Series Anomaly Detection equips participants with the skills to detect anomalies in time series data effectively. By the end of the programme, students will be able to master Python programming, statistical analysis, and machine learning techniques specifically tailored for anomaly detection in time series data.
The programme has a duration of 10 weeks and is self-paced, allowing students to balance their learning with other commitments. Whether you are a beginner or an experienced data scientist, this programme will enhance your expertise in anomaly detection and provide you with practical tools to apply in real-world scenarios.
This certificate programme is highly relevant to current trends in data science and analytics, as anomaly detection in time series data is a crucial aspect of various industries such as finance, cybersecurity, IoT, and more. The curriculum is aligned with modern tech practices and industry standards, ensuring that participants are well-prepared to tackle the challenges of today's data-driven world.
| Year | Number of Anomaly Detection Incidents |
|---|---|
| 2018 | 546 |
| 2019 | 732 |
| 2020 | 921 |