Starting Up is an introductory level course about the central features of founding and running a startup company. The course is targeted for all students who want to learn more about the topic, regardless of their background and experience.

The course will provide the student with an understanding of the basics of entrepreneurship. To facilitate the thinking of starting a business, the students will sketch their own “Not-a-Business-Plan” – an outline of what their own business could look like by applying the tools presented in the course. Created by AVP, Kiuas Accelerator, Maki.vc and Reaktor, Starting Up is an introductory level online entrepreneurship course. During the course you’ll learn the fundamentals of startup entrepreneurship, company building, and how to create new products with real-life examples from successful entrepreneurs. After completing the course, the student

• can describe how startups differ from other types of companies
• can name the typical phases of building a startup
• can identify and state a problem that could serve a basis for a startup
• knows how to validate such a problem
• is familiar with the typical phases in identifying a product-market fit
• is familiar with the phases of the fundraising process and the differences between different funding instruments
• can create the outline of a business plan

In this course, you will learn the basics of setting up a small business of your own. You will follow a budding entrepreneur, Veera, on her path towards setting up her own business. In each session, Veera will talk about her journey and what challenges she is facing. The course instructors will then suggest how she could proceed in each situation. After the suggestions, there will be a couple of short lessons introducing key topics related to the session. You also need to answer some quizzes and questions to complete each session.

Good Life Engine is a hands-on self-leadership course that creates a framework for personal growth by providing a toolkit for connecting with your inner self and the community. The journey you are about to take will help you navigate life with more clarity and comfort and see opportunities for self-development. In addition, the course addresses modern life challenges such as lack of time, anxiety, self-criticism, FOMO, decision paralysis, monkey mind etc. The journey that you are about to take will help you to navigate through life with more clarity and comfort and see opportunities for self-development. It will be especially beneficial if you feel lost or being enslaved by your calendar and/or you want to learn yourself and others better.

Student learns to communicate the basic technology, design and business aspects of a product. Students work in interdisciplinary teams. Each team is assigned a product that is analyzed from the perspectives of design, business, and engineering. The analysis is supported with lectures and workshops related to manufacturing techniques, materials, services, users, etc. The outcome of the analysis is presented in a final gala.

The course is based on contact teaching and team work on topics related to the sustainable product development. After the course the student is

– able in figuring out a product life cycle and listing major life cycle impacts
– realizes the role of material choice and material efficiency in sustainable product development
– understands the role of user centred approach in sustainable product development
– is able in finding and critically applying the relevant guidance for sustainable product development
– has improved skills in communication on questions related to sustainability

In this course, we study the principles of efficient algorithm design and you will learn how to systematically approach new algorithmic problems. You will be able to formally argue why your algorithm works correctly and identify the challenges you need to overcome to solve a given problem. You will also learn to analyse the efficiency of algorithms and algorithmic approaches prior to their implementation.

The main focus of this course is on mathematical foundations of algorithms.

Algorithm design paradigms: divide-and-conquer, greedy algorithms, dynamic programming. Principles of analysis of algorithms: correctness, duality, randomization.

Pre-requisites: Basic knowledge and familiarity of mathematics including discrete mathematics, together with an introduction to probability theory, programming skills, and familiarity with basic data structures.

As computational systems have moved to become pervasive parts of our lives, it becomes even more important to consider how they can be best designed to be useful and useable by people (or “users”). But what is a “user”, how do we understand what they want, and how can we design user interfaces that are effective and efficient for them. This course covers the foundations of Human-Computer Interaction – the study of how computer systems can be designed to support the needs of the people who we intend to use them. The course provides an introduction to UI and UX design, focusing on the user-centered design process as a way of understanding user needs and requirements and testing designs. At a basic level we will cover Usability, User-centered design, prototyping, how this process fits into existing software product development, as well as looking to how the relationship between computers and humans is evolving, and how we might interact with computer systems in the future. At the end of this course the student should:

Understand key aspects of human perception and cognition, and how these impact on the design of Human-Computer Interfaces. Understand the importance of Human-Computer Interaction in the design of products and services. Be able to define and describe the key stages of a User Centered Design process. Understand the key techniques used at each stage of the User Centered Design Process and have practical experience in their application through exercises. Be able to compare and contrast qualitative and quantitative evaluation techniques. Be able to propose and justify an appropriate evaluation technique to a given problem

Have awareness of cutting edge interaction research and developments in user interaction paradigms, design and evaluation. Have awareness of practical issues in the application of Human-Computer Interaction in an industrial context. No pre-requisites.

Exploratory data analysis. Dimensionality reduction, PCA. Regression and classification. Clustering. Deep learning. Reinforcement learning. Learning outcomes: Students can formalize applications as ML problems and solve them using basic ML methods. Students can perform basic exploratory data analysis. Students understand the meaning of the train-validate-test approach in machine learning. Students can apply standard regression and classification models on a given data set. Students can apply simple clustering and dimensionality reduction techniques on a given data set. Students are familiar with and can explain the basic concepts of reinforcement learning.

Pre-requisites: Matrix Algebra, Probability Theory, Basic Programming Skills.

Student understands what web applications are, how they function, and how they are constructed. Student understands the responsibilities of client-side web applications and server-side web applications, and is able to design, implement, and test web applications. Student understands and applies up-to-date development and deployment strategies. 

The course is offered as a continuously available online course, where students can start the course at any time. Note that the materials (including assignments and projects) are updated periodically – completed assignments, in general, remain completed between material updates. The course staff may, however, remove and add assignments that can also influence course grading even while the course is running. The grading of the course is always based on the most recent version of the materials. Prerequisites: Basic know-how of programming, programming-related tools (e.g. IDEs), and databases is required.