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You've covered a lot of ground in the past there weeks, learning about making queries with SQL basics, control flow and data structures in Python Useful Python libraries: numpy, matplotlib, and pandas. Basic R R data structures: vectors, matrices, lists, and data frames Graphics using RIn your second project you're going to be applying these skills in to explore baseball statistics.
In the process you'll practice a vital data science skill the ability to research new tools and read documentation. You may choose to do this project in either R or Python.
|Learning Style||Self-Paced Learning|
|Course Duration||14 Days|
(Data Science Enthusiast)
Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.
Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.