For this event
— When and for how long? —
3 sessions, 3 hrs each online via video chat tools . Three dates:
Session 1: 22.04.2021, 16:00 – 19:00 h
Session 2: 29.04.2021, 16:00 – 19:00 h
Session 3: 06.05.2021, 16:00 – 19:00 hrs
Details for interactive online participation will be provided after registration.
— For whom? —
This offer is aimed at beginners with Python knowledge or at least programming knowledge who are looking for a practical introduction to the topic of artificial intelligence and machine learning.
— Keywords —
Learning Paradigms of AI, Supervised, Unsupervised, and Reinforcement Learning, k-Means, DBSCAN, Regression, MLP, Q-Learning, Actor-Critic Learning
— What’s being taught? —
The workshop will focus on three different learning methods of data-driven AI in three sessions: supervised, unsupervised, and reinforcement learning. In each case, the theoretical foundations of the respective learning methods and their areas of application are explained. Participants will learn 1-2 representative methods for each learning method: k-Means and DBSCAN (unsupervised), Regression and Multi-Layer Perceptron Network (MLP) (supervised), and Q-Learning (reinforcement learning). The selection of methods follows both didactic and application-oriented criteria, i.e. they are simple enough to understand the principles quickly and are the basis of many methods used in practice.
— How is it taught? —
Each session includes a theoretical part, in which the basics are first discussed to create a foundation, as well as a practical part, in which prepared tasks are implemented together and discussed once the basics are understood. This deepens the understanding of the theory and gives all participants practical experience with the respective methods. The examples used are based on freely available datasets and software frameworks to allow for easy self-study after each session. This ensures that each participant can apply what they have learned to their own problems.
The language of instruction is English. The room is streamed online via a video chat tool and online attendees can participate interactively.
— What are the requirements? —
Since all practical examples are provided in Python, basic programming knowledge is necessary (optimally already experience with Python). The practical part takes place online, using Google Collaboratory, which requires a working Google Account. Basic mathematical knowledge (solid school knowledge) is advantageous to understand the mathematical basics of the respective methods.
— tickets —
The prices differ between ARIC e.V. member, single booking of only this workshop or booking as an additional workshop (if another HITeC workshop is booked at the same time at full price). Prices can be found on the event website under the LINKcan be viewed.
