This course is a foundational introduction to Python and how to apply it in data science . The course contains about 60 lectures and 7.5 hours of content taught by Praba . Use data analysis using Pandas and data visualization to implement supervised (regression and classification) & unsupervised (clustering) machine learning . Use various analysis and visualization tools associated with Python, such as Matplotlib, Seaborn etc. Use Python libraries and work on data manipulation, data preparation and data explorations . Use the NumPy package to understand how to use the various Python libraries to manipulate data, like Numpy and Scikit-Learn .API quota exceeded. You can make 500 requests per day.
Who this course is for:
New Python developers looking to quickly develop and keen understanding of the power of Python
Early stage users of Python who need to use Python in serious, enterprise level applications
Individuals who are familiar with data science and need to understand the optimal uses for Python
