Terraform based DevOps for Infrastructure as a code deployment

The main goal for the project is to utilize cloud technologies to build a Terraform based DevOps system for Infrastructure as a code deployment across multiple clouds. This will involve several different steps for the learners, including: - Understanding the current infrastructure and cloud technologies being used by the company. - Researching and learning about Terraform and its capabilities for Infrastructure as a code deployment. - Developing a DevOps system that integrates Terraform and cloud technologies for seamless deployment. - Testing the developed system and making improvements based on feedback and additional research.

SaaS Integrations Testing Project

The main goal for the project is to perform testing of various connectors to various SaaS applications and ensure that they are functioning properly. This will involve several different steps for the learners, including: - Understanding the different types of connectors and SaaS applications. - Developing test cases for each connector and SaaS application combination. - Executing the test cases and documenting the results. - Identifying and reporting any issues or bugs found during testing. - Collaborating with the development team to ensure that any issues are resolved. - Providing a final report on the testing process and outcomes.

Artificial Intelligence & Machine Learning Application

Our company is building a platform with focus on Software AI Agents as a a Service and we want to leverage the latest technology to gain market advantage. Applications of this technology include building range of AI agents using latest frameworks like llangchain and llamaindex. 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 AI / ML models and AI agents related to any of the aforementioned applications. This will involve several different steps for the students, including: Conducting background research on our existing products and the dataset. Analyzing our current dataset. Researching the latest AI / ML techniques and how they could be applied to our data. Developing an AI / ML model and agents that provides unique outcomes or insights into our data. Providing multiple solutions that can be applied to solve the same problem.