MACHINE LEARNING – FROM ZERO TO HERO

You've already made the first step - data collection. You've gathered lots of it but don't know how to utilise it in order to predict, optimise and control the future. Infotiv has developed a new hands-on course to get you started on your quest for mining value out of your precious data. 

The data doesn't lie, and you know it. Applying machine learning algorithms to analyse your data enables you to extract complex information otherwise not possible to comprehend. 

With trained software instead of coded software you can develop truly smart functionality. Let data drive your decisions and you'll be ahead of the curve. Data-driven businesses provide more value to their customers while keeping development costs low. 

Course description 

This course aims to give deep knowledge about  Machine Learning (ML):

• What it is.
• What it is not.
• When to apply it.
• How to apply it.

Upon completion of the course, the user should be comfortable in training and applying ML.   

• The course covers every stage of the Data Science Lifecycle, including verification & validation of ML.
• Learn how to put Machine Learning into practice and how to verify your Machine Learning solution.
• Apply ML in practice, both virtually and on embedded target environment.

Prerequisites   

To get the most from the course basic knowledge in Python as well as in concepts surrounding software development is desired.    

Course content   

• Introduction to AI/ML​   
• Development environment   
• Selection of algorithm and training ​   
• Data​ management​   
• Verification & Validation​ of ML functionality   
• Apply ML in practice, both virtually and on embedded target environment   
• ​Risks​ surrounding the use of ML   

Course language

The course will be held in english.

Course Schedule

During the course, the participants will be able to practice on all steps necessary to train, test (verify), integrate (on HW), and validate a machine learning model.

The exercises will be split over the two days. The first day covers exercise setting up the workflow and training an initial model and the second day handles testing and deployment. After completing the course, each participant will be allowed to bring home the Raspberry Pi containing their trained and tested model. 

Click here to see a detailed schedule for the 2 days

Course completion   

The Infotiv Machine Learning course gives the student the theoretical and practical knowledge in training models. The student will also get basic understanding on the challenges in testing functionality based on ML.   

Estimated completion time: 2 days 

NEXT COURSE DATES

Register your interest right now. Contact Magnus de Canesie at magnus.de.canesie@infotiv.se or by phone: +46 76 651 11 33.

PRICE

The price for one (1) person is: SEK 16.500.

CUSTOMIZED COURSE FOR YOUR COMPANY

Are you interested in a course customized to your company? Of course, we offer you that. Please contact us for a quote.

REGISTRATION

Send an email to magnus.de.canesie@infotiv.se to either sign up or ask for more details.

COURSE LEADERS

Martin Karsberg: 

Competence Leader for Test Methodologies at Infotiv. Working with testing of IT in a variety of fields, from the defence industry to municipalities. Martin also teaches methodology. 

Martin knows his way around both traditional and new testing methods. He is currently Infotiv's project leader for two research projects focused on the task of V&V on Machine Learning. 

During weekends Martin listens to his broad collection of LP:s, grill burgers and lets his mind wander back to his punk days in Ireland.

Hamid Ebadi, PhD: 

He is exploring the challenges in introducing machine learning‐based systems to automated driving within SMILE (Safety analysis and verification/validation of MachIne LEarning based systems) and VALU3S (Verification and Validation of Automated Systems’ Safety and Security) projects. 

He has a passion for sharing knowledge gained, which he refined by taking courses such as "Applied Project Management" and "Teaching, Learning and Evaluation" while performing his Ph.D. studies at Chalmers. He also taught in Master's level courses, including Cryptography and Model-Based Testing. 

During his work he has supervised 6 master students thesis from Chalmers university and is course leader for Infotivs "Machine Learning – from Zero to Hero" course.