Workshops, Seminars

& Trainings


IT Security Workshops & Seminars

Our seminars & workshops on various IT security topics are not monologues. We respond to individual questions in an active and discussion-friendly atmosphere. Find out more about our range of courses.


Introduction to Cloud Security

  • Introduction to Cloud Computing (Crash Course)
  • Introduction to Cloud Security
  • Legal framework
  • IT Risk Management
  • Contracts and Service Level Agreements (SLA)
  • Steps for migration to cloud computing.


  • Why Cryptography?
  • What is cryptography?
  • Basics of Public Key Infrastructure
  • Literature recommendations on topics dealt with


  • Secure e-mail communication
  • Digital certificates and their management for small companies or departments
  • hard disk encryption
  • SAP (SNC) Security
  • SmartCard Management Systems
  • and other topics

Contact Person

Bernhard Borsch

Bernhard Borsch

Senior Consultant - IT Security

Since 2014 Bernhard Borsch is Senior Consultant in the area of security for mVISE AG. In addition to PKI and cryptography, his core competencies also include mobile security.
He and his team are currently supporting customers who are facing the challenge of securing mobile devices.

Data Science Trainings

The Data Science Unit of mVISE AG has prepared Data Science and Statistics courses to enable our customers to tap the full potential of their data. We present up-to-date methods and tools using practical examples, so participants of our courses can delve right into their own data and make the most of the topics covered.

Data Science Fundamentals

You will acquire a basic understanding of selected data science algorithms and tools. Using practical examples you will learn to successfully build, evaluate and use data models.

Deep Learning

You will learn how to optimally apply artificial neural networks and deep learning methods and familiarize yourself with state-of-the-art algorithms.

Time Series Analysis

We will teach you how to analyze sequential data to recognize trends and develop forecasting models


  • Artificial Neural Networks
  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Random Forest
  • Support Vector Machines
  • Bayesian Methods
  • Clustering Methods
Neural Networks
  • Artificial Neural Networks
  • Introduction Neural Networks
  • Multilayer Perceptrons (MLP)
  • Restricted Boltzmann Machines (RBM)
  • Convolutional Neural Networks (CNN)
  • Deep Reinforcement Learning (RL)
  • Video Analysis / Object Tracking
  • Recurrent Neural Networks and Long-Short-Term-Memory
  • Attention Models
  • Autoencoders
  • Remaining Useful Lifetime Models
  • Hands on – Relevant Deep Learning Libraries
Forecasting Models
  • Transformations
    • Resampling
    • Detrending
    • Decomposition
    • Smoothing
  • Frequency Transformation
  • Sequential Pattern Mining
    • Stochastic Time Series Models
    • Stationary Time Series Models
    • Non-Stationary Time Series Models
  • Recurrent Neural Networks and Long-Short-Term-Memory
  • Remaining Useful Lifetime Models

Contact Person

Dr. Alexander Kaul

Dr. Alexander Kaul

Head of Data Science Unit

Alexander Kaul leads the data science unit in Munich and has been working as a consultant for over 10 years. In the course of his career he accompanied different projects, from vision to first implementation till continuous development in an ongoing operation. Currently he develops new data driven business models with his clients.

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