Introduction to Artificial Intelligence

P. V. Logics . February 18, 2023

 Introduction to Artificial Intelligence


Course Description: 

This course is designed to provide an overview of the field of artificial intelligence (AI), including its history, current applications, and future potential. Students will learn the fundamental concepts and techniques of AI, including machine learning, natural language processing, computer vision, and robotics. The course will also cover ethical considerations, such as bias and fairness, privacy, and accountability in AI.

Introduction to Artificial Intelligence Course Description: This course is designed to provide an overview of the field of artificial intelligence (AI), including its history, current applications, and future potential. Students will learn the fundamental concepts and techniques of AI, including machine learning, natural language processing, computer vision, and robotics. The course will also cover ethical considerations, such as bias and fairness, privacy, and accountability in AI. Course Outline: Introduction to Artificial Intelligence Definition of AI History of AI Current and future applications of AI Machine Learning Introduction to machine learning Supervised learning Unsupervised learning Reinforcement learning Natural Language Processing (NLP) Introduction to NLP Text preprocessing Sentiment analysis Topic modeling Computer Vision Introduction to computer vision Image preprocessing Object detection Image segmentation Robotics Introduction to robotics Types of robots Robot kinematics and dynamics Robot control Ethical Considerations in AI Bias and fairness in AI Privacy concerns in AI Accountability in AI Future of AI Current trends in AI Future potential of AI Implications for society Course Goals and Learning Outcomes: By the end of this course, students will: Understand the fundamental concepts and techniques of artificial intelligence Be able to identify current and future applications of AI Be able to use machine learning, NLP, computer vision, and robotics techniques Understand the ethical considerations in AI, including bias, fairness, privacy, and accountability Be aware of current trends in AI and the potential implications for society Assessment and Evaluation: Assessment will be based on quizzes, assignments, and a final project. The final project will involve applying the concepts and techniques learned in the course to a real-world problem in AI. The project will be evaluated based on the quality of the solution and the ability to articulate the ethical considerations involved.


Course Outline:


  • Introduction to Artificial Intelligence
  • Definition of AI
  • History of AI
  • Current and future applications of AI
  • Machine Learning
  • Introduction to machine learning
  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning
  • Natural Language Processing (NLP)
  • Introduction to NLP
  • Text preprocessing
  • Sentiment analysis
  • Topic modeling
  • Computer Vision
  • Introduction to computer vision
  • Image preprocessing
  • Object detection
  • Image segmentation
  • Robotics
  • Introduction to robotics
  • Types of robots
  • Robot kinematics and dynamics
  • Robot control
  • Ethical Considerations in AI
  • Bias and fairness in AI
  • Privacy concerns in AI
  • Accountability in AI
  • Future of AI
  • Current trends in AI
  • Future potential of AI
  • Implications for society

Course Goals and Learning Outcomes:


By the end of this course, students will:

  • Understand the fundamental concepts and techniques of artificial intelligence
  • Be able to identify current and future applications of AI
  • Be able to use machine learning, NLP, computer vision, and robotics techniques
  • Understand the ethical considerations in AI, including bias, fairness, privacy, and accountability
  • Be aware of current trends in AI and the potential implications for society


Assessment and Evaluation:

Assessment will be based on quizzes, assignments, and a final project. The final project will involve applying the concepts and techniques learned in the course to a real-world problem in AI. The project will be evaluated based on the quality of the solution and the ability to articulate the ethical considerations involved.



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