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Learn Python programming fundamentals specifically tailored for data science applications in this comprehensive 2 hour and 38 minute course. Master the essential Python environment setup including Unix shell, Anaconda, and Git configuration for data science projects. Explore Jupyter Notebooks interface, IPython kernel functionality, and sharing capabilities through GitHub integration. Build a solid foundation in Python data types, strings, and lists before advancing to dictionaries, conditionals, loops, and functions. Develop object-oriented programming skills and learn to work effectively with external libraries and modules. Gain hands-on experience with NumPy essentials, focusing on one-dimensional arrays and their applications in data science. Discover practical hacks and specialized libraries to accelerate your data analysis workflow and improve productivity in data science projects.
