Introduction to Artificial Intelligence

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About Course

This course introduces students to the fundamentals of Artificial Intelligence (AI). It covers the history, concepts, and applications of AI, including an overview of machine learning, neural networks, natural language processing, and computer vision. Students will gain a broad understanding of AI’s potential, limitations, and ethical implications, and will work on basic projects to apply AI concepts practically.

What Will You Learn?

  • Understand the fundamentals and history of Artificial Intelligence
  • Differentiate between types of AI and machine learning methods
  • Preprocess and analyze data for AI applications
  • Build and evaluate simple machine learning models
  • Gain foundational knowledge of neural networks and deep learning
  • Develop an understanding of Natural Language Processing (NLP) techniques
  • Identify ethical considerations and challenges in AI development
  • Work with Python libraries and tools for AI (e.g., TensorFlow, Scikit-Learn)
  • Create an AI project from scratch, applying key concepts learned

Course Content

Introduction to Artificial Intelligence
Gain an understanding of what Artificial Intelligence (AI) is, its history, and its types. Explore the different applications of AI in various industries and its potential impact on the future. This module builds a foundational understanding of AI concepts and introduces students to key terminology.

Fundamentals of Machine Learning
Discover the core concepts of machine learning, including different types such as supervised, unsupervised, and reinforcement learning. Learn how data plays a crucial role in AI, and explore essential techniques for data preprocessing, model building, and algorithm selection. This module provides hands-on knowledge of working with data in AI contexts.

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