Artificial Intelligence & Machine Learning Application

Our company is a platform for creating data products enabled by AI, and we want to leverage the latest technology to gain market advantage. Applications of this technology to build data products include recommendation algorithms, predictive analytics like lifetime values, fraud detections, cyber security analytics and classifications. We would like to collaborate with students to apply the latest artificial intelligence (AI) and machine learning (ML) techniques to our existing dataset. Students will develop an AI / ML model related to any of the aforementioned applications. This will involve several different steps for the students, including: Conducting background research for specific problem domains (Will provide at the beginning of project) Analyzing the dataset (identify data requirements) Researching the latest AI / ML techniques and how they could be applied to our data. Developing an AI / ML model that provides unique outcomes or insights into our data. Providing multiple solutions that can be applied to solve the same problem. (Key is to build a "deployable" solution

Knorket.AI Terraform Automation Project

The main goal of this project is to build terraform based automation for setting up infrastructure in the cloud to help set up big data infrastructure. This will involve several different steps for the students, including: - Learning about terraform and its capabilities. - Setting up terraform scripts for the cloud infrastructure. - Configuring helm charts for the big data infrastructure. - Setting up load balancers and ingress. - Testing the automation scripts and making improvements based on additional data.

Cyber Security Data Products - Design and Development

The main goal of this project is to research and analyze security related queries from some of open source solutions designed to perform a range of security tests and compile them all as well build additional to enable roll-out comprehensive data products. This will involve several different steps for the students, including: - Researching and analyzing existing open source security solutions. - Developing a comprehensive data product that can be rolled out. - Optimizing the security data product for performance. - Testing the developed product and making improvements based on additional data.

Data Modeling and ER Diagrams for SaaS API Tables

The main goal for the project is to convert the list of data tables of various SaaS based API's into proper data models using cube.dev or a similar approach. Additionally, the project aims to build ER models of the same to ensure efficient data organization and management. This will involve several different steps for the learners, including: - Analyzing the existing data tables and understanding the structure and relationships of the data. - Utilizing cube.dev or similar tools to create data models that accurately represent the SaaS API data. - Building ER models to visually represent the relationships between different entities in the data. - Testing the data models and ER diagrams to ensure they accurately capture the original data and its relationships.