Develop essential data science & ai skills with expert instruction and practical examples.
Become a Master in Data Acquisition and Visualization with Python 3 and acquire employers' one of the most requested skills of 21st Century. An expert level Data Science Professional can earn minimum $100000 (that's five zeros after 1) in today's economy. This is the most comprehensive, yet straight-forward course for the Data Science with Python 3 on Udemy.
Whether you have never worked with Data Science before, already know basics of Python, or want to learn the advanced features of Altair with Python 3, this course is for you. In this course we will teach you Data Science with Python 3, Jupyter, NumPy, Pandas, Matplotlib, and Altair. (Note, we also provide you PDFs and Jupyter Notebooks in case you need them)With over 105 lectures and more than 14.
5 hours of video this comprehensive course leaves no stone unturned in teaching you Data Science with Python 3, Pandas, and Altair. This course will teach you Data Science in a very practical manner, with every lecture comes a programming video and a corresponding Jupyter notebook that has Python 3 code. Learn in whatever manner is the best for you.
We will start by helping you get Python3, NumPy, matplotlib, Jupyter, Pandas, and Altair installed on your Windows computer and Raspberry Pi. We cover a wide variety of topics, including:Basics of Scientific Python EcosystemBasics of PandasBasics of NumPy and MatplotlibInstallation of Python 3 on WindowsSetting up Raspberry PiTour of Python 3 environment on Raspberry PiJupyter installation and basicsNumPy NdarraysArray Creation RoutinesBasic Visualization with MatplotlibNdarray ManipulationRandom Array GenerationBitwise OperationsStatistical FunctionsBasics of MatplotlibInstallation of SciPy and PandasLinear Algebra with NumPy and SciPyData Acquisition with Python 3MySQL and Python 3Data Acquisition with PandasBasics of Altair and Vega DatasetsData Visualization with AltairYou will get lifetime access to over 105 lectures plus corresponding PDFs, Image Datasets, and the Jupyter notebooks for the lectures. So what are you waiting for.
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