This year's SciPy conference concluded recently and the list of videos are available on YouTube. Here is a list of tutorials that I would like to watch:

1. An Introduction to Julia
2. PyViz: Easy Visualization and Exploration for all your Data
3. Parallelizing Scientific Python with Dask
4. Machine Learning with Scikit-Learn, Parts 1 and 2
5. The Jupyter Interactive Widget Ecosystem
6. Software Engineering Techniques
7. Pandas .head() to .tail()
8. Setting Up Your Own Open Source Project
9. The Sheer Joy of Packaging
10. Getting Started with TensorFlow and Deep Learning
11. Bayesian Data Science Two-Ways: Simulation and Probabilistic Programming
12. Getting Started with JupyterLab

And here is a list of talks that I watched or would like to watch:

1. Apache Arrow: A Cross-Language Development Platform for In-Memory Data
2. Inside the Cheeseshop: How Python Packaging Works
3. Detecting Anomalies Using Statistical Distances
4. Connecting Scientific Models across Scales & Languages with Python
5. Sparse: A More Modern Sparse Array Library
6. The Past, Present, and Future of Automated Machine Learning
7. Resurrecting Ancient Proteins in Python
8. Should this drug be approved? A Bayesian's Answer with Stan
9. Physics: A Gateway to Bayesian Deep Learning
10. Ray: A Distributed Executing Framework
11. SimuPy: A Python Framework for Modeling and Simulating Dynamical Systems
12. Exploring Molecular Space with Deep Generative Models and Python
13. Evaluating Niching in the GAtor Genetic Algorithm for Molecular Crystal Structure
14. Scikit-Learn and Tabular Data Closing the Gap
15. Scalable Machine Learning with Dask
16. Safe Handling Instructions for Missing Data
17. PyQuil: Easy, Hybrid Quantum Programming

Not enough time!