Software development is a team game. As you progress through your career, you might end up in a leadership role, taking care of your own team, or even of multiple teams. As a team lead, it’s up to you to establish a good working rhythm, set the right expectations, communicate up and down the chain of command and effectively help your team grow in both technical and non-technical terms. As a team lead, you want to enable your team to reach its full potential. The main goal of this talk is to provide pragmatic real-life examples, about how to achieve those things. We are going to cover the following topics: 1. What’s the role of a team lead?
2. Managing expectations & responsibilities.
3. Establishing a good work rhythm.
4. Establishing a good form of communication.
5. What does team growth look like? PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=MO5U_whP7C0 https://www.youtube.com/watch?v=7jRRKOrPLRo

Kubernetes’ inception was essentially a response to the arduous and unreliable nature of the deployment process. The GitOps workflow and its intersection between platform engineering and the developer is particularly significant for programmers who prefer not to be bogged down by the intricacies of deploying their code into Kubernetes. Irrespective of their preferred programming language — be it Java, Python, Dotnet, Rust, or Go — they simply want to push their code, generate a container image, and have it deployed immediately. GitOps enables them to do this. PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com/watch?v=LHVjp7JeKzE https://www.youtube.com/watch?v=IwipqLTWIs4

Probabilistic Programming as a field is moving at breakneck speed, with innovations being driven on all levels: language, algorithms, compilers, computation, hardware. In this expert briefing I will give a brief overview of where the field is today and where it is headed. One big trend is what I call The Great Decoupling: rather than monolithic PPL systems, we are seeing how various layers of abstraction are introduced and separated. This allows more interoperability, as well as innovation to occur at every level of the stack. Finally, I will talk about a convergence of Bayesian modeling and Causal Inference to a new paradigm called Bayesian Causal Inference. PUBLICATION PERMISSIONS:
PyData provided Coding Tech with their permission to republish PyData talks on Coding Tech channel. CREDITS:
PyData YouTube channel: https://www.youtube.com/@PyDataTV https://www.youtube.com/watch?v=_RdO56bbkcY