Advanced Data Science
Applied Statistics & Machine Learning
The day-to-day work of your engineers often involves statistical questions and challenges. Sometimes these are recognized as such, but sometimes they are not. It is not always clear which technique to use in which situation, how to apply these techniques correctly or how to draw the right conclusions. If this sounds familiar, our Advanced Data Science training may be exactly what you need.
This has become increasingly relevant in recent years. Companies are collecting more and more data during production and logging data from equipment while it is operating at customer sites. But how do you extract valuable knowledge from these vast amounts of data? In addition to traditional statistical methods, a wide range of modern Machine Learning techniques is now available.
This training equips participants with practical skills in statistics and Machine Learning. They learn which techniques to use in different situations and gain a clear understanding of the differences between them. Participants also learn how to translate a business problem into a statistical or Machine Learning problem, solve it using the appropriate methods, and translate the mathematical results back into meaningful answers to the original business problem.
Content
The training is always customized to your specific needs and requirements. To give you an idea of what the training could look like, below is an example of a program consisting of two parts:
- Part 1: Applied Statistics for Data Analysts
- Part 2: Advanced Statistics and Machine Learning
In this example, both parts could consist of six or seven half-day sessions:
Part 1
- Recap of statistics and probability theory, introduction to software tools, regression and correlation
- Measurement System Evaluation and process capability
- Q&A, CQM cases and participant cases
- Significance testing
- Principles of Design of Experiments
- Introduction to autocorrelated data, Q&A, your company's typical approaches in the context of the statistical topics covered, and participant cases
Part 2
- Recap of Part 1 and Optimal Designs
- Spread breakdown – Part A
- Spread breakdown – Part B
- Q&A and real company cases
- Machine Learning – Part A
- Machine Learning – Part B
- Q&A and participant cases
By the end of the training participants will be able to:
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Recognize common statistical challenges encountered in industrial environments
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Translate business challenges into statistical and Machine Learning problems
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Identify the statistical and Machine Learning techniques required and determine which technique to use in which situation
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Apply these techniques using statistical software
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Interpret the results and translate them into insights that can be applied in their day-to-day work
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Apply and interpret the most commonly used statistical and Machine Learning techniques in their daily work
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Tackle complex, organization-specific challenges using appropriate statistical and Machine Learning techniques
Interested?
Interested in customized training in Applied Statistics & Machine Learning – in other words, Advanced Data Science?
Contact Bert Schriever to discuss the possibilities.
