Below the AIBA course program. Please note the sessions that are marked with the green color: These are sessions where we concentrate on your business idea and demos.
It is of help if you study the various links that you find in the course program. The first part is a general AI introduction and the second part will focus on your AI idea.

You need to have an idea of an AI service or product to attend the second part of the course. This idea can be at any stage of development. You will get help to define your idea throughout the course.

Program Autumn 2020

1. General part

The first day is about where AI started, the pilot funding principals and standards.
Course introduction and a field map – General information about the course
AI history – Where did it start and why is it possible today?
Data science – What is this?
Ethics – Is one of the key things in AI development

Company presentations
AI and law


The Finnish AI Accelerator with business examples
Meet the company presenter on-line. Ask questions and discuss topics.


2. AI project specialties and quirks, Crisp-DM

What is the project plan all about? Own project plan home work go through.
Data specification homework handed out, concerns those who continue to the part 2.
CRISP-DM – Cross-industry standard process for data mining: resources, limitations, pitfalls, case studies, successes and failures. Check for more info about CRISP-DM here.
AI Project management
AI project plan

3. Project Management and AI project plan

The business plan and improving these is the focus of the last part. Prepare to talk about your AI idea and your plan.

AI Project management
AI project plan

A real project example From RaisoAqua / Tomi Kantola

4. Data

More in detail about data
Data – Customer data specifics, data preparation
Data specification homework, presentations

Turku City Data

Company presentation
AI project specialties and quirks

AI project plan homework

5. Machine learning and demos

Machine Learning (ML) methods is the content of this session. ML is a set of core routines used in AI projects. Here you will learn more about it.
Machine Learning an neural networks – model validation and cost function
customer data specifics survival analysis, recommendation and tournament methods
DL – Deep Learning
Deep Fake and Adversarial Attacks

6. Tools and platforms

We learn about practical tools and platforms as well as data driven AI.
Azure – Microsoft platform for running AI projects
Jyputer – For handling machine learning development

Company presentation
Hear how to control a program with voice
Meet company presenters on-line Ask questions and discuss topics.

7. Natural language processing

Using text analytics in various projects is useful and not too hard. NLP (Natural Language Processing) is in focus in this session
Natural language processing and AI – What is natural language processing and to what can it be used? Classification and clusterization or tf-idf?


AI project plans
Company presentation

Michael Stormbom will tell us about real life NLP solutions.

8. Project plan pitching – End of the course

AI project plan pitching
Business Finland, FAIA and other possible project funding / help. Ask questions and discuss topics.

Attending to at least 100% in the first part and 90% of the second part will give you a personal diploma. One diploma for the first part or one for both parts. Materials are handled out after the sessions.The maps to the different places for the studies are found below the timeline. Move back to the Turku AI HUB page here.