ResilientML – Gateway to Ocean: Introductory, Intermediate, and Advanced AI/ML Data Science Courses

Overview

We propose to create an AI/Machine Learning certificate series that embeds the use of Ocean data marketplace into an interactive syllabus of modules to provide a gateway for aspiring and current data scientists into the exciting world of blockchain and the data economy.

Full Proposal

https://port.oceanprotocol.com/t/proposal-round-5-resilientml-gateway-to-ocean-introductory-intermediate-and-advanced-ai-ml-data-science-courses/605

Grant Deliverables

Together with course notes explaining the methodologies and concepts, we will provide R and Python code with examples of applications. All scripts and examples as well as course notes will be provided in advance of the course. Part I of the course will focus on R via RStudio and the tidyverse framework. Part II of the course will be demonstrated in Python. We will publish the datasets required in the course to the Ocean marketplace, and provide datatoken/mOCEAN airdrops, to enable participants to gain hands-on experience interacting with Web3.0 technologies. On completion of the course, the participants will have obtained a substantial understanding of data preparation and feature extraction methods and will have been introduced to kernel learning concepts. In addition, participants will be in a position to recognize a broad range of supervised learning problems and address them under the common framework of Generalized Eigenvalue problems. Furthermore, course participants will have acquired a solid knowledge of how to curate text data collections in such a way as to maintain the important information whilst removing information noise. They will be able to understand the sources of noise in text data and the risks involved if they are not addressed. Consequently, participants will be equipped with the basic knowledge to begin working confidently on any text processing application and be able to prepare their data for basic feature extraction (e.g. Bag-of-Words) and statistical modelling. Generally, the level of the course will tend to focus on methodology and providing an introduction for participants to concepts and statistical modelling approaches in the topics mentioned above. Proofs of concepts discussed will be referenced in the slides for participants to follow up afterwards should they wish to explore more technical details.

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