Course Overview

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Course Description

Upon completion of this course, participants will have the expertise to:

  1. Strategically collect, manipulate, and mine data sets to drive organizational success.
  2. Identify and implement cutting-edge artificial intelligence and machine learning techniques tailored to enhance specific business operations.
  3. Design and deploy advanced data models that optimize operational efficiency and meet targeted business goals.
  4. Develop robust software applications for data manipulation, correlation, and comprehensive reporting.
  5. Create visually compelling data visualizations using industry-standard tools like Matplotlib, Folium, and Seaborn.
  6. Master essential Python skills, including data structures, control structures, user-defined functions, and lambda expressions, to solve complex business challenges.
  • Explain the hardware and software constraints in AI algorithms.
  • Connect business problems to Python-based solutions.
  • Map business requirements to programming structures.
  • Select and apply appropriate AI and ML techniques for business processes.
  • Design programs with input, output, and processing considerations.
  • Model business relations through input-output correlation.
  • Format and display output effectively.
  • Apply data models to business processes.
  • Implement conditionals and manage case scenarios.
  • Use comparison operators and nested structures.
  • Develop control structures for complex process simulations.
  • Understand data structures, control structures, and lambda expressions in Python.
  • Create modular programs with functions.
  • Use functions for data intake, processing, and output.
  • Implement value-returning functions and the math module.
  • Develop data storage structures using modular functions.
  • Practice file control for data transport, processing, and reporting.
  • Create and store algorithmic models in files.
  • Handle model weights storage and transformation.
  • Manage exceptions in model and program execution.
  • Create advanced data visualizations using matplotlib, folium, and seaborn.
  • Implement and manipulate arrays with NumPy.
  • Handle data indexing and operations with Pandas.
  • Develop software applications for data manipulation and reporting.