Python

Artificial Intelligence Tutorial

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  • 0 Students
  • 20h 10m
  • Intermediate
  • Certificate of completion Pass mark 60%
  • 5 Modules
  • 30 Lessons

Instructor: Artificial Intelligence Instructor

Course Code: AITUT

Course description

A complete artificial intelligence course spanning introduction to AI, core AI concepts such as search and knowledge representation, machine learning, robotics and automation, and generative AI. Interview Q&A and project guides ship as downloadable PDF course materials. Each lesson ends with a three-question check.

What You'll Learn

  • Explain what AI is, how it relates to machine learning and deep learning, and where it is applied
  • Describe search, knowledge representation, reasoning and planning methods used in intelligent agents
  • Outline machine learning, deep learning, NLP and computer vision building blocks inside AI systems
  • Discuss robotics, RPA, and AI uses in transportation and manufacturing
  • Compare generative models such as GANs, GPT and BERT and list practical generative AI applications
  • Use the downloadable interview and project PDFs to prepare for AI roles

Requirements

  • Python basics: variables, loops, functions, lists and dictionaries
  • Curiosity about algorithms and data-driven systems; mathematics is introduced gently in context
  • A modern web browser for lessons and checks; PDF materials are downloadable from the course page

Who this course is for

  • College students of computer science, data science or engineering taking a first AI course
  • Coaching and training institutes that want a structured AI track with checks per lesson
  • Developers moving into AI who already know some Python

Curriculum

Introduction to AI

  1. 1 Reading What is Artificial Intelligence (AI) 45m
  2. 2 Reading Types of Artificial Intelligence (AI) 40m
  3. 3 Reading Types of AI Based on Functionalities 40m
  4. 4 Reading Agents in AI 45m
  5. 5 Reading Artificial intelligence vs Machine Learning vs Deep Learning 30m
  6. 6 Reading Problem Solving in Artificial Intelligence 40m
  7. 7 Reading Applications of Artificial Intelligence (AI) 40m

AI Concepts

  1. 1 Reading Search Algorithms in AI 45m
  2. 2 Reading Local Search Algorithm in Artificial Intelligence 40m
  3. 3 Reading Adversarial Search Algorithms in Artificial Intelligence (AI) 45m
  4. 4 Reading Constraint Satisfaction Problems (CSP) in AI 40m
  5. 5 Reading Knowledge Representation in AI 40m
  6. 6 Reading First-Order Logic in Artificial Intelligence 40m
  7. 7 Reading Reasoning Mechanisms in AI 40m

Machine Learning in AI

  1. 1 Reading Machine Learning Tutorial 40m
  2. 2 Reading Deep Learning Tutorial 30m
  3. 3 Reading Natural Language Processing (NLP) Tutorial 40m
  4. 4 Reading Computer Vision Tutorial 40m

Robotics and AI

  1. 1 Reading Artificial Intelligence in Robotics 45m
  2. 2 Reading What is Robotics Process Automation 45m
  3. 3 Reading Automated Planning in AI 30m
  4. 4 Reading AI in Transportation 45m
  5. 5 Reading AI in Manufacturing : Revolutionizing the Industry 40m

Generative AI

  1. 1 Reading What is Generative AI 45m
  2. 2 Reading Generative Adversarial Network (GAN) 45m
  3. 3 Reading Cycle Generative Adversarial Network (CycleGAN) 45m
  4. 4 Reading StyleGAN - Style Generative Adversarial Networks 40m
  5. 5 Reading Introduction to Generative Pre-trained Transformer (GPT) 40m
  6. 6 Reading BERT Model - NLP 40m
  7. 7 Reading Generative AI Applications 30m

About Your Instructor

Artificial Intelligence Instructor

Artificial Intelligence Instructor

  • 0 Learners
  • 1 Course

Teaches Artificial Intelligence from foundational concepts and robotics through generative AI.
Each lesson ends with a short check; interview Q&A and project guides are downloadable PDFs.

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Modules 5
Lessons 30
Duration 20h 10m
Students 0
Language Python
Enrollment Open
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