Full Stack Data Science with Python, Numpy and R Programming

Learn data science with R programming and Python. Use NumPy, Pandas to manipulate the data and produce outcomes



What you'll learn

  • Learn R programming without any programming or data science experience
  • If you are with a computer science or software development background you might feel more comfortable using Python for data science
  • In this course you will learn R programming, Python and Numpy from the beginning
  • Learn Fundamentals of Python for effectively using Data Science
  • Fundamentals of Numpy Library and a little bit more
  • Data Manipulation
  • Learn how to handle with big data
  • Learn how to manipulate the data
  • Learn how to produce meaningful outcomes
  • Learn Fundamentals of Python for effectively using Data Science
  • Learn Fundamentals of Python for effectively using Numpy Library
  • Numpy arrays
  • Numpy functions
  • Linear Algebra
  • Combining Dataframes, Data Munging and how to deal with Missing Data
  • How to use Matplotlib library and start to journey in Data Visualization
  • Also, why you should learn Python and Pandas Library
  • Learn Data Science with Python
  • Examine and manage data structures
  • Handle wide variety of data science challenges
  • Create, subset, convert or change any element within a vector or data frame
  • Most importantly you will learn the Mathematics beyond the Neural Network
  • The most important aspect of Numpy arrays is that they are optimized for speed. We’re going to do a demo where I prove to you that using a Numpy vectorized operation is faster than using a Python list.
  • You will learn how to use the Python in Linear Algebra, and Neural Network concept, and use powerful machine learning algorithms
  • Use the “tidyverse” package, which involves “dplyr”, and other necessary data analysis package




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