Foundations of Artificial Intelligence

Explore the fundamentals to work with Artificial Intelligence (AI) systems.

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Course details

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Registration details

Foundations of Artificial Intelligence

Explore the fundamentals to work with Artificial Intelligence (AI) systems.

What you’ll be able to do — competencies

  • Explore AI use cases, trends and career opportunities
  • Discover how AI impacts business
  • Demonstrate how to use Python as an AI Tool
  • Create data visualizations with Python
  • Evaluate the different forms of graphs
  • Demonstrate the impact statistics has on AI research
  • Evaluate the fundamentals of SQL and data structures

Course Description

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Designed for individuals interested in learning and exploring career opportunities in Artificial Intelligence.

Learn critical knowledge and skills in AI technologies and concept that are applicable across every stage of career advancement, from the college graduate looking to land their first job, to an experienced developer looking to increase their AI skills.

Prerequisites

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  • Familiarity with Microsoft Office, is recommended
  • Knowledge of high school level math, is recommended

Syllabus

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This course schedule may be modified by the instructor based on the needs of the class.

Module 1: The Foundations of Artificial Intelligence 

  • Evolution of AI 
  • Difference between narrow, general and super AI. 
  • Applications of AI across industries 
  • Opportunities in AI for individuals, organizations and the ecosystem 
  • Principles of Machine Learning 
  • Machine Learning Fundamentals 

Module 2: AI Database Concepts 

  • SQL Relational Database models 
  • Types of SQL Relationships 
  • Typical data types and formats  
  • NoSQL Database models 

Module 3: AI Programming Fundamentals – Python 

  • Foundations of data structures 
  • Implementation of data structures:  
  • Algorithms
  • Python

Module 4: AI Statistics  

  • Basic concepts of descriptive statistics 
  • Measures of central tendency (mean, median, mode) 
  • Measures of central dispersion (range, interquartile range variance, standard deviation) 
  • Statistical anomalies and regressions 

Module 5: Data Visualization Fundamentals with Python 

  • Fundamentals of data visualization: 
  • Graph types: pie charts, line graphs, scatter graphs, bar charts, column graphs, ring plots 
  • Introduction to some of the popular tools: Tableau, Power BI, QlikView, Ggplot, Bokeh, and Geoplotlib 

Module 6: Capstone Project 

  • Select one of 3 different Data Sets and apply the various statistic concepts and tools, and Jupyter Notebook to analyze and create the code to visualize specific statistical data. 
  • Determine the Mean and Standard Deviation of your data and then write the Python code to produce a visual representation of the statistical data from your spreadsheet into meaningful visualizations.  
  • Once you have the data and visualizations you will create 2-4 PowerPoint slides that presents your analysis of the data. 
  • Save your data and PowerPoint presentation for use in the Building Your Personal and Professional Brand. 

Module 7: Introduction to Building your Personal and Professional Brand 

  • Introduce the Building your Personal and Professional Brand course. 

Next available start dates

Online — Evenings

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Foundations of Artificial Intelligence
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Total classroom hours

15 hours

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Schedule

Online

Evenings, 6:00 PM - 7:30 PM, 10 T Th - 2/21/2023 - 3/23/2023

Quarter: Winter

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Total cost

$975

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Instructor: Dean Gilbert

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