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, and Julia.
Jupyter & Python: Visualize, Optimize & Accelerate
您将学到什么
Configure Jupyter/IPython and create advanced visualizations with Matplotlib & Seaborn.
Optimize Python performance with profiling, memory mapping, Numba, and Cython.
Implement parallel/distributed computing and integrate next-gen visualization tools.
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添加到您的领英档案
最近已更新！
October 2025
作业
23 项作业
授课语言：英语（English）
了解顶级公司的员工如何掌握热门技能
该课程共有6个模块
This module introduces learners to Jupyter and IPython environments, focusing on setup, configuration, and basic operations. Students will gain confidence in using notebooks for code execution, documentation, and fundamental computations.
涵盖的内容
10个视频3个作业
This module covers the foundations of data visualization using Matplotlib and NumPy. Learners will explore different chart types and understand how to enhance them for meaningful insights.
涵盖的内容
17个视频4个作业
This module emphasizes advanced plotting skills, including annotations, multi-axis visualizations, and scientific plotting features. Learners will be able to design professional-quality graphs for analytical and presentation purposes.
涵盖的内容
13个视频4个作业
This module explores advanced IPython features including HTML/JavaScript rendering, magic commands, and kernel management. Learners will also discover automated testing for reliable and reproducible workflows.
涵盖的内容
13个视频4个作业
This module introduces optimization methods, interactive widgets, and profiling techniques. Learners will improve code efficiency and handle large datasets effectively using NumPy and real-time interactions.
涵盖的内容
18个视频4个作业
This module focuses on high-performance computing with Numba, Cython, and parallel computing strategies. Learners will also explore advanced visualizations and Julia integration for next-generation numerical computing.
涵盖的内容
26个视频4个作业
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状态：免费试用
状态：预览
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To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
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Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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