Hi @CatalinaAlbornoz,
I’ve been following your lectures on PennyLane via the Wiser platform and found them incredibly insightful. The way you bridge the gap between quantum theory and differentiable programming is amazing.
I am very keen to dive deeper and experiment with the code locally to reinforce what I’ve learned. Would it be possible to share the Jupyter Notebooks used in those lectures? Having the source code would be a massive help in my journey to mastering PennyLane for Quantum Machine Learning.
Thank you for the great educational content
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Hi @ajcodes ,
Welcome to the Forum, and thank you for your kind words!
We’re working on making them available to you very soon. I’ll share them here with you as soon as we can share the link to download them.
What did you like the most about the sessions?
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hi @CatalinaAlbornoz ,
Thank you for the warm welcome!
To answer your question, what I appreciated most was the focus on differentiable programming. Since I currently work with classical Machine Learning and Deep Learning, I often found quantum computing theory a bit abstract. Your sessions showed how a @qnode can be treated as a native differentiable layer within a standard AI pipeline. That was a real “lightbulb” moment for me,it made PennyLane feel like a natural extension of my current AI toolkit rather than a completely separate field.
I also really enjoyed the sections on templates like BasisEmbedding and the use of transforms.decompose. Being able to see those high-level operations broken down into fundamental gates made the transition from theoretical concepts to actual implementation much clearer. It also gave me a lot of inspiration for how I can start experimenting with quantum circuits for my own AI related tasks.
I’m really excited to continue exploring the PennyLane ecosystem and hopefully contribute to the community as I progress further in this journey.
Also, as someone coming from an AI/ML background and becoming increasingly interested in Quantum ML, I’d love to learn more about the kinds of roles or contribution opportunities that exist within the PennyLane ecosystem or your team. Even guidance on the skills or projects you’d recommend focusing on would be incredibly valuable.
Looking forward to the notebooks, and thank you again for the excellent sessions!
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I love to hear this @ajcodes !
We’ve made the notebooks accessible through this website: Quantum Optimization with PennyLane - Wiser Quantum Algorithms Fundamentals & Hands-on Training | PennyLane
There you’ll find the notebooks and other resources to keep learning.
If you’re interested in contributing I encourage you to take part in unitaryHACK! It’s a developer event where you can submit your solution to certain GitHub issues and compete for bounties.
Let me know if you have any trouble downloading the notebooks and feel free to share any questions about them here!
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