In the following list we present our courses limited to a specific category. When interested, please feel free to contact us using the 'Get in touch'-button on top.

Category
Course
Course description
AI & Analytics
Introduction to data analytics with Python and Pandas
This course introduces the basics of data handling and manipulation in Python, based on Pandas and NumPy. Concepts such as arrays, vectorization and data frames are covered.
AI & Analytics
Topic modeling
The course provides an introduction to exploiting patterns in large sets of unstructured data, using Topic Modeling. Topic modeling can be applied on unstructured data (e.g., texts and images) to exploit patterns as similar ...
AI & Analytics
Spark / Scala
The spark-Scala training is a practical introduction on working with spark using Scala. It focuses on spark 1.6.2 and for data processing we focus on data frames. Topics that are covered are: the Spark framework (what is it, ...
AI & Analytics
Bayesian statistics
The standard way of hypothesis testing relies on the so-called frequentist approach, using t-statistics and p-values for statistical inference. Yet this approach is misleading, and suffers from problems of interpretation. ...
AI & Analytics
Introduction to Machine Learning in Pyspark
This training provides a general introduction to some basic concepts of Machine Learning in the context of logistic regression in Pyspark. It discusses the difference between linear and logistic regression, the algorithm ...
AI & Analytics
Simulation
This training helps participants understand when simulation is a suitable solution to a problem. It describes basic methodologies and touches best practices and pitfalls. Finally through demonstrations and excercises this ...
AI & Analytics
Neural networks with an application in R/H2O
During this training, participants will get an introduction to feed-forward Neural Networks, and gain an understanding of how they work, what their strengths and weaknesses are, and how they can train and utilize neural ...
AI & Analytics
Introduction to Machine Learning in R
This course starts by introducing Artificial Intelligence in general, and shortly dives into a high-level overview of R-basics. Many important data analytic topics are introduced: text mining, linear modelling, polynomial ...
AI & Analytics
Algorithm selection
Data Scientists usually boast about one particular algorithm to be used on each and every occasion. But aren't various algorithms more or less suitable to different problems? While many of focus on building trees or ...
AI & Analytics
Programming Introduction - applied learning using a small Robot
This course provides an introduction to programming for non-programmers. Using robots (Q-Edison), that can be programmed in Python or in an easy, visual block-diagram fashion, participants learn about good programming ...
AI & Analytics
Introduction to programming with Python
This course introduces the basics of programming in Python, making participants familiar with concepts such as: data types, lists, dictionaries, loops, and functions.
AI & Analytics
Logistic regression with an application in R
This training provides a general introduction into logistic regression as a method for classification. It discusses the difference between linear and logistic regression, the algorithm underlying logistic regression, and ...
AI & Analytics
Introduction to machine learning in Python
This course consists of two parts. In part I, participants learn about statistical analysis using logistic regression, focusing on issues such as data manipulation, gauging statistical significance, and interpreting ...
AI & Analytics
AI for dummies
This course introduces the fundamentals of AI, its history, its application areas and examples of successful AI applications in a business context.
AI & Analytics
Classification trees and ensemble techniques with an application in R
This course introduces Classification trees and Ensemble Techniques. Classification trees are popular because they provide intuitive results - which helps both fine-tuning and end-user acceptance. This course explains how ...
AI & Analytics
Feature selection
So you've collected at lot of data, and found or built a large number of features to explain the phenomenon of interest. How do you make sure your models do not become too big and unwieldy, while maintaining good ...
AI & Analytics
Docker
This course explains how to create a Docker container, and how to share it, run it and work with it.

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