Practical Python for AI Coding 2

Instructor: Youngsun Kwon

Skills you'll gain

  •   Development Environment
  •   Scikit Learn (Machine Learning Library)
  •   Pandas (Python Package)
  •   Python Programming
  •   Seaborn
  •   Object Oriented Programming (OOP)
  •   Data Visualization
  •   Keras (Neural Network Library)
  •   Artificial Intelligence
  •   NumPy
  •   Data Manipulation
  •   Tensorflow
  •   Matplotlib
  • There are 5 modules in this course

    This course is for a complete novice of Python coding, so no prior knowledge or experience in software coding is required. This course selects, introduces and explains Python syntaxes, functions and libraries that were frequently used in AI coding. In addition, this course introduces vital syntaxes, and functions often used in AI coding and explains the complementary relationship among NumPy, Pandas and TensorFlow, so this course is helpful for even seasoned python users. This course starts with building an AI coding environment without failures on learners’ desktop or notebook computers to enable them to start AI modeling and coding with Scikit-learn, TensorFlow and Keras upon completing this course. Because learners have an AI coding environment on their computers after taking this course, they can start AI coding and do not need to join or use the cloud-based services.

    Pandas library: Using DataFrames

    Strings and files

    Data visualization: matplotlib and seaborn

    Object oriented programming: introducing class object

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