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Artificial Intelligence for Schoolers

Everything about AI: strengths and weaknesses, ethics, neural networks, algorithms, training types, natural language processing, related professions

Experts: Miriam Drahina

Artificial intelligence has already taken over vacuum cleaners and Siri, not to mention ChatGPT!

 

AI doesn't rule the world, but it's already become the new normal — from Amazon Alexa to camera traps. It is used to select recommendations on social media, diagnose coronavirus in pneumonia, and recognize faces. These are just a few examples — you can hear more while watching the series.

 

And not only hear, but also understand how to create artificial intelligence! Learn how neural networks, natural language processing, and computer vision work. Separate episodes focus on classification algorithms, decision tree, logistic regression, linear discriminative analysis, support vector method and K-means, Stacking, Bagging, Random Forest, and Boosting.

 

If you want to make AI a part of your profession, this educational series is for you.

 

Course authors: Dmytro Chumachenko, Yaroslava Kutsai, Olesia Pavlyshyn, Daria Kuzyava.

 

A series of the Ministry of Digital Transformation of Ukraine with the support of the E-Governance for Accountability and Participation" (EGAP) Swiss-Ukrainian Program implemented by the Eastern Europe Foundation and funded by Switzerland, in cooperation with Kunsht, a popular science network.

Format:
Education series
EKTS:
0.2
Languages:
Ukrainian, English
Topic:
Artificial Intelligence
For:
For students
Skills:

HARD: AI Ethics, AI in art, AI in ecology, AI in medicine, Learning with a teacher, Learning without a teacher, Linear discriminant analysis, Natural language processing, Reinforcement learning, Strong and weak AI, the history of AI development, Understanding the difference between machine learning and human learning, Work with AI algorithms, Work with algorithms: boosting, Work with algorithms: decision tree, Work with algorithms: logistic regression, Work with algorithms: naive Bayes, Work with algorithms: random forest, Work with algorithms: stacking, Work with algorithms: the K-means method, Work with algorithms: the method of support vectors, Work with computer vision, Work with different types for machine learning, Work with neural networks

Invited experts

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Miriam Drahina

Product designer, creative producer, radio presenter, popularizer of science, poet, co-founder of popular science platform Brain&Ukraine

Partners

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EGAP

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Kunsht

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