AI/ML Basic Course – Hybrid Classroom + Online Training [AI100]

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About Course

AI/ML Basic [AI100] is a 36-clock-hour, short-term, non-degree training program designed to introduce students to artificial intelligence, machine learning, Python, data fundamentals, and practical AI tools.

Students begin with computer and information-technology fundamentals, progress to introductory Python and data concepts, and learn foundational machine-learning concepts through instructor-led instruction, demonstrations, exercises, and hands-on activities.

Learning Objectives

Upon successful completion, students should be able to:

• Explain fundamental artificial intelligence and machine-learning concepts.
• Distinguish between AI, machine learning, deep learning, and generative AI at an introductory level.
• Apply basic Python programming concepts.
• Work with basic data structures and data-processing concepts.
• Explain supervised and unsupervised machine-learning concepts.
• Identify common machine-learning applications and use cases.
• Use selected AI tools for instructor-guided exercises.
• Apply introductory AI/ML concepts through hands-on exercises and a basic project.

Program Information

Course Code: AI100
Duration: 36 Clock Hours
Delivery Method: Hybrid – Classroom + Online
Credential: AITE Certificate of Completion

Program Disclosure

This is a short-term, non-degree training program. Successful completion results in an AITE Certificate of Completion. AITE does not guarantee employment, job placement, salary, professional licensure, or third-party certification.

Prerequisites

Basic computer and internet skills are recommended. Prior programming, artificial intelligence, or machine-learning experience is not required.

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What Will You Learn?

  • Artificial intelligence and machine-learning fundamentals
  • Differences between AI, machine learning, deep learning, and generative AI
  • Practical uses and limitations of AI systems
  • Responsible AI, privacy, and ethical-use concepts
  • Python programming fundamentals
  • Variables, data types, conditions, loops, functions, and data structures
  • Basic data-analysis and data-preparation concepts
  • Supervised and unsupervised machine-learning fundamentals
  • Classification and regression concepts
  • Model training and evaluation fundamentals
  • Practical use of selected AI tools
  • Hands-on Python and AI/ML exercises
  • Introductory instructor-guided AI/ML project

Course Content

Weekend 1: IT, Computer & AI Fundamentals – 12 Clock Hours
Goal: Build foundational computer, technology, and programming skills for AI/ML study

  • Modern Computing Environment (2 hrs)
  • Networking & Internet Basics (2 hrs)
  • Programming Fundamentals (4 hrs)
  • Data & Databases (2 hrs)
  • Version Control & Collaboration (2 hrs)
  • Computer & IT Fundamentals

Weekend 2: Python, Data & Machine Learning Foundations – 12 Clock Hours
Goal: Build Python, data, and mathematical foundations for machine learning.

Weekend 3: Applied AI/ML Fundamentals & Project – 12 Clock Hours
Goal: Build hands-on skills with classical ML algorithms.