Python AI Development: Practice Overview/Description Expected Duration Lesson Objectives Course Number Expertise Level Overview/Description In this course, you'll learn about development of AI with Python, starting with simple projects and ending with comprehensive systems. You'll examine various Python environments and ways to set them up and begin coding, leaving you with everything you need to begin building your own AI solutions in Python.
Expected Duration (hours)
1.4
Lesson Objectives Python AI Development: Practice
discover the key concepts covered in this course
configure the Python environment for developing AI
specify the role of Anaconda in keeping clear working environments
specify the advantages of Jupyter Notebooks and create Jupyter Notebook files connected to appropriate kernel environment
specify the advantages of the Google Colab environment and create files in the environment
use large datasets for exploring data and statistics
apply pre-processing techniques commonly used in AI development
describe the steps needed to create machine learning models and identify guidelines for using them
describe the steps needed to create deep learning models and identify guidelines for using them
work with a hand written digits dataset and implement a simple classification model in Python
work with a housing prices dataset and implement a simple regression model in Python
create a pilot distraction predictor by applying deep learning techniques
configure a distracted driver detection device in Python using the pilot distraction predictor
summarize the key concepts covered in this course
Course Number: it_aiappddj_02_enus
Expertise Level
Intermediate