Embrace the future with our Artificial Intelligence A course designed to equip you with the essential skills to thrive in today’s rapidly evolving tech landscape. As AI continues to revolutionise industries, the demand for skilled professionals is soaring. This course offers a comprehensive introduction to the fascinating world of AI, exploring its different types and delving into the intricacies of machine learning algorithms. With a focus on real-world applications, you’ll gain valuable insights to tackle turnkey projects confidently. By enrolling, you’ll place yourself at the forefront of innovation, boosting your career prospects and contributing to transformative advances. Seize this opportunity to become part of the AI-driven future, where your expertise will be pivotal in shaping a a smarter world.
Artificial Intelligence
Introduction
Objectives
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Understand the fundamental concepts of artificial intelligence.
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Distinguish between various types of artificial intelligence.
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Understand the basics of machine learning algorithms and their applications.
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Identify real-world solvable problems by artificial intelligence.
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Analysis the impact the impact of artificial intelligence on various industries.
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Explore ethical considerations in the development of AI technologies.
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Develop critical thinking skills to evaluate AI-based solutions.
Table of Contents
UNIT 1. INTRODUCTION TO ARTIFICIAL INTELLIGENCE
The current state of the art in artificial intelligence
Philosophy of artificial intelligence
The Future of Artificial Intelligence
Project development process using artificial intelligence
Data, your greatest asset
UNIT 2. TYPES OF ARTIFICIAL INTELLIGENCE
Machine learning
Deep learning
Transformers
Generation of synthetic data
Hyperparameters in artificial intelligence models
UNIT 3. INTRODUCTION TO MACHINE LEARNING ALGORITHMS
Linear regression
Non-linear regression and support vector machines (SVM)
Decision trees, random forests
Fuse logic and gradient down
Recommendation systems
UNIT 4. TURNKEY PROJECT
Setting up the working environment: Anaconda, Visual Studio Code and Python
Input dataset and data pre-processing
TensorHub, TensorFlow and Keras
Image processing
Generation of artificial intelligence models