Data is at the very core of all business decisions. Machine Learning is gaining increased attention as a tool for extracting crucial insights from data to make improved decisions that will ultimately enable your company to stay ahead of the competition.
During this course, you’ll get an introduction to the most common concepts and applications of Machine Learning. You will learn various supervised and unsupervised ML algorithms and prediction tasks which will be applied to different data. Additionally, this course will improve your ability to understand how you can choose the proper model for your data.
The two-day course will vary between an instructor-led approach and hands-on exercises. The main areas of focus will be on providing the participants with the necessary knowledge and confidence to apply Machine Learning in their work. The course will have a broad perspective on Machine Learning, but it will focus on classification tasks.
Participants are expected to bring their laptops, but everything else is provided.
The hands-on exercises will be browser-based, so there is no requirement to install software, but participants should be willing to sign-up for a free Google account if they do not have one already.
The course and course material will be conducted and provided in English.
During this course, you will be working on:
This course is an introductory course and therefore aimed at anyone who is curious to learn more about Machine Learning and searching for an understanding of simple yet effective Machine Learning tools.
Everyone can participate in the course, but the course has more relevance if you are already working with a great deal of data and want to learn how to optimise the value from these.
Basic coding or scripting knowledge is required.
When you participate in this course, you will not only gain personal skills, but also skills that your company or organisation can greatly benefit from.
Recognise and define business problems that could be addressed with Machine Learning and Artificial Intelligence.
Identify when Machine Learning can be applied to explain specific behaviors and when it can be applied to predict future outcomes.
Recognise how Machine Learning can be applied to numerical, text, and image data.
Clean and prepare data, perform Exploratory Data Analysis (EDA), and train classification models.
Understand and identify the differences between some of the most implemented Machine Learning models.
Evaluate a Machine Learning model and decide how to incorporate best practices.
Gain a sustainable competitive advantage by having employees with crucial Machine Learning knowledge.
Be able to prepare for the future by attempting to collect data suitable for Machine Learning.
Not sure if this course is right for you?
Let me give you a call for personal sparring.
You are always welcome to contact me for advice on which course or programme will suit your needs the best.
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With an in-house programme, you can choose any course from our broad portfolio. We will conduct the course for your employees only – adapted to your specific needs, wishes, and business goals.
Mannaz works in close collaboration with IDA, THE DANISH SOCIETY OF ENGINEERS.
When you sign up for this course, Mannaz handles your registration, while IDA manages the course execution.
Your name, e-mail and telephone number will be passed on to IDA. The contact information is used exclusively in connection with the course.
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