Jupyter & Python: Visualize, Optimize & Accelerate

By the end of this course, learners will be able to configure Jupyter and IPython environments, create professional data visualizations with Matplotlib, enhance graphs with NumPy, and apply advanced scientific plotting techniques. They will also master IPython functionalities such as widgets, magic commands, kernels, and unit testing while optimizing Python performance with profiling tools, memory mapping, and conversions. Finally, learners will accelerate Python with Numba and Cython, implement parallel and distributed computing, and explore next-generation visualization with Seaborn, D3.js, …