Introduction to Machine Learning

Many organizations have to deal with more and more data. Machine learning is gaining attention as a tool for extracting value from all this data. This course is an introduction to the concepts and applications of machine learning.

Tid og sted

  • 07.10.19


  • 15.01.20


  • 02.04.20


  • 26.05.20


Se flere tider og steder under tilmelding

Varighed: 2 dage


Understand the concepts of Machine Learning

Machine Learning is not a new field, but it has received a lot of attention in recent years as an important tool when it comes to handling big data and building the AI applications of the future. Machine Learning models are now being used to solve many different problems, from predicting when industrial machinery needs replacement to focusing cameras on mobile phones.

With machine learning it becomes possible to build systems that improves with more data, which is a fundamentally different approach compared to traditional rule-based programming. This course will introduce the concepts of machine learning to allow participants to recognize problems that are best approached with machine learning.

The course has a number of hands-on exercises that will allow participants to gain practical experience with training and evaluating machine learning models for a range of different types of problems.


The course is suited for software developers or engineers

The course is well-suited for software developers or engineers wishing to add machine learning to their toolbox.
Participants should be interested in working with data and willing to learn how to extract value from data.

Participants should be comfortable writing code and ideally have some familiarity with Python. It is not necessary to have any prior experience with machine learning and only basic mathematics are required.

After this course you will be able to:

  • Recognize problems that are suitable for machine learning.
  • Prepare data and train a classification model.
  • Understand the differences between some of the most popular machine learning models.
  • Evaluate how good a machine learning model is.
  • Understand how machine learning can be applied to numerical, text and image data.

After this course, the organization will:

  • Gain a competitive advantage by having employees with machine learning knowledge
  • Be able to prepare for the future by collecting data suitable for machine learning

Course agenda on Machine Learning

The two-day course will be instructor led with hands-on exercises. The focus will be on giving the participants the knowledge and the confidence to apply machine learning to problems that they face in their own work. The course will touch upon many aspects of machine learning, but emphasis will be on classification tasks

Participants are expected to bring own laptop to the class, everything else needed for course is provided.
The hands-on exercises will be browser-based, so there is no need to install software, but participants should either have or be willing to sign-up for a free Google account.

Day 1

  • Concepts of Machine Learning
  • Data preparation
  • Logistic regression
  • Overfitting
  • Python, NumPy, Tensorflow
  • Multilayer perceptron

Day 2

  • Working with natural language
  • Bag of words
  • Deep Learning
  • Image recognition
  • Neural networks



2 dage

Pris ekskl. moms


9.900 kr.

Ikke IDA-medlem:

11.900 kr.

Vælg sted og dato




7. okt. - 8. okt. 2019
Kl. 09:00 - 16:00


Tivoli Hotel & Congress Center

Arni Magnussons Gade 2

1577 København



Tilmeldingsfrist 03. okt. 2019 - kl. 23:59


Se datoer



2. apr. - 3. apr. 2020
Kl. 09:00 - 16:00






Tilmeldingsfrist 30. mar. 2020 - kl. 23:59


Trainer on Machine Learning

Andreas Koch

Andreas Koch has a background in data science and has substantial experience with both analysing data and productionizing machine learning models. Currently, Andreas is working as a data science consultant advising organisations on how to best leverage their data.

The training language and the study material will be in English at this course.



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Billede af Rikke Waldorff Jensen

Rikke Waldorff Jensen