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- Research and study the basics of data labs, focusing on end-to-end processes.
- Utilize YouTube tutorials on data pipelines, specifically on deploying to Azure.
- Practice building a simple data pipeline.
- [Azure Data Factory project ] (https://www.youtube.com/watch?v=IaA9YNlg5hM&t=303s)
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- Set up a virtual desktop or deploy a dummy tech stack at home to simulate an on-premises environment. (Kasm Workspaces)
- Work on setting up and configuring ADB (Azure Database?).
- Explore Kubernetes (K8s) as a container orchestration tool.
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- Engage in AI/ML training through platforms like O'Reilly.
- Get hands-on experience with AI/ML tools and techniques.
- Practice with Jupyter Notebooks for interactive computing and development.
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- Study and implement network automation (potentially using VPN).
- Explore R&D on modern automation tools and practices.
- Create a home automation assistant project.
- Look into WAN optimization techniques.
- Explore n8n
- Explore node red
- [n8n Docs] (https://docs.n8n.io/)
- [node-red] (https://nodered.org/)
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- Learn about observability in systems and networks.
- Implement monitoring tools like Telegraf in a lab environment.
- [Network Monitoring Solution - Telegraf] (https://www.linkedin.com/pulse/network-monitoring-solutions-demo-simple-robust-vijay-kumar-devunuri/)
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- Dive into DevOps principles and practices.
- Work on a project that incorporates CI/CD pipelines.
- [Model-Driven DevOps] (https://learning.oreilly.com/library/view/model-driven-devops-increasing/9780137644711/)