From machine learning to AI

Course

Booking no:

42573

From machine learning to AI

Machine learning goals vary depending on the company. Learn how to design, train, evaluate, and deploy your own ML models in your company. In this course, you will learn about ML basics and different model types (including simple neural networks). Gain insights into common applications of (generative) AI in business and the basics of LLMs and applications based on them (RAGs, AI apps such as ChatGPT, automation, agents). At the heart of the course is a continuous practical project in which you carry out all phases of an ML project yourself.

4 weeks

approx. 20 hours

Online

German

Professional and Master Class

Date preview

Start date

Last module

Availability

Location

13.8.2026

3.9.2026

Places free

Maximum planning security

Implementation already secured

Hook on!

Next booking secures the
implementation

Live-Online

27.8.2026

1.10.2026

Places free

Maximum planning security

Implementation already secured

Hook on!

Next booking secures the
implementation

Live-Online

Book course individually

Module overview

The following module overview shows dates for the course start on

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Module

Fundamentals of Machine Learning

Basic concepts of machine learning
KNIME introduction and basic task (familiarization with data set)
Group task: Develop a business case from the (still incomplete) data set.

Webinar

180 minutes

Thursday, 13.08.2026
09:00 am - 12:00 pm

61454555

Module

Fundamentals of Machine Learning

Basic concepts of machine learning
KNIME introduction and basic task (familiarization with data set)
Group task: Develop a business case from the (still incomplete) data set.

Webinar

180 minutes

Thursday, 27.08.2026
09:00 am - 12:00 pm

61454483

Module

Self-study phase 1

Basic concepts & fundamentals

Crisp DM
- Business Understanding
- Data Understanding
- Data preparation
Exercise: Import, connect, and clean up data set
Outlook: Supervised learning and train-test splits

Self-study phase

approx. 4 hours

61454555

Module

Self-study phase 1

Basic concepts & fundamentals

Crisp DM
- Business Understanding
- Data Understanding
- Data preparation
Exercise: Import, connect, and clean up data set
Outlook: Supervised learning and train-test splits

Self-study phase

approx. 4 hours

61454483

Module

Model and evaluate

Recap of the first self-study phase
Preparation Exercise: Modeling and Evaluation
Exercise: Basic supervised learning workflow
Outlook on modeling and evaluation

Webinar

240 minutes

Thursday, August 20, 2026
, 11:30 a.m. – 3:30 p.m.

61454555

Module

Model and evaluate

Recap of the first self-study phase
Preparation Exercise: Modeling and Evaluation
Exercise: Basic supervised learning workflow
Outlook on modeling and evaluation

Webinar

240 minutes

Thursday, September 17, 2026
, 1:00 p.m. – 5:00 p.m.

61454483

Module

Self-study phase 2

Machine learning in action – From data set to intelligent model

CRISP-DM Evaluation: Assessing the Quality of Models
Linear/logarithmic regression, decision trees, neural networks presented as classification and regression
Evaluation of classification models. Metrics and ROC curves
Exercise: Build the classification workflow for a decision tree
Evaluate errors in regression models
Advanced: Neural Networks
Outlook: ML Operations

Self-study phase

approx. 5 hours

61454555

Module

Self-study phase 2

Machine learning in action – From data set to intelligent model

CRISP-DM Evaluation: Assessing the Quality of Models
Linear/logarithmic regression, decision trees, neural networks presented as classification and regression
Evaluation of classification models. Metrics and ROC curves
Exercise: Build the classification workflow for a decision tree
Evaluate errors in regression models
Advanced: Neural Networks
Outlook: ML Operations

Self-study phase

approx. 5 hours

61454483

Module

From ML to LLMs and AI in business

Recap of the second self-study phase
Practical example of explainable classification
What does all this have to do with AI? LLMs, RAGs, AI as an automation component
Relevant issues within the company (compliance, EU AI Act, cloud, AI implementation)

Webinar

240 minutes

Thursday, September 3, 2026
, 1:00 p.m. – 5:00 p.m.

61454555

Module

From ML to LLMs and AI in business

Recap of the second self-study phase
Practical example of explainable classification
What does all this have to do with AI? LLMs, RAGs, AI as an automation component
Relevant issues within the company (compliance, EU AI Act, cloud, AI implementation)

Webinar

240 minutes

Thursday, October 1, 2026
, 9:00 a.m. – 1:00 p.m.

61454483

Course overview

Contents and course schedule

1. Basic concepts: from AI to machine learning models

The most important basics
important learning methods
Implementing machine learning projects with CRISP-DM

2. ML Projects I: Setting up projects and preparing data

Understanding requirements and setting up a project correctly
Understanding data and preparing it for machine learning using pipelines

3. ML Projects II: Modeling and Evaluation

How can I model the data in a meaningful way?
Getting to know the common models: from simple linear regression to decision trees and neural networks
Model selection: Which model should be used when?
Model evaluation: Systematic evaluation of different models

4. ML Projects III: Making ML and AI usable in companies

How are machine learning models put to use in companies?
How can LLMs be utilized within a company?
Brief outlook: Data protection & EU AI Act

This is how you learn in this course

This course offers you a digital blended concept that has been developed for part-time learning. Thanks to a flexible mix of online seminars and self-study phases, you are sure to reach your goal. This is how you learn in this course:

Learning environment: In your online learning environment, you will find useful information, downloads and extra services for this training course after you have registered.

Self-study phases: Learn independently, at your own pace and whenever you want. Our courses offer you didactically high-quality learning material.

Live webinars: In regular online seminars, you will meet your trainers in person. You will receive answers to your questions, specific assistance and instructions on how to deepen your knowledge and apply the skills you have acquired in practical exercises.

Learning community: A digital learning community is available to you throughout the course. Exchange ideas with other participants and the trainers and ask questions.

Future Jobs Club: Get exclusive access to a business network, news, and future work hacks.

Certificate of completion and Open Badge: As a graduate of the course, you will receive a certificate of completion and an Open Badge, which you can easily share on professional networks (including LinkedIn).