The AI Artificial Intelligence Course From Beginner to Expert

By Asomoo.Net and Victor Montas

This book is number 1 in sales for its important content for the learning and development that this book has for each person, learning everything related to artificial intelligence for commercial or personal use.

"Artificial intelligence is rapidly transforming the world we

• Language: English
• Publisher: Asomoo.Net
• Release date: Sep 12, 2023
• ISBN: 9781088265444

Book preview

THE

AI

Artificial Intelligence Course

From Beginner to Expert

This book is number 1 in sales for its important content for the learning and development that this book has for each person, learning everything related to artificial intelligence for commercial or personal use.

By: Asomoo.Net and Victor Montas

Copyright © 2023 Asomoo.Net and Victor Montas All rights reserved. | www.asomoo.net

Index

MODULES 1

Module 1: Fundamentals of Artificial Intelligence

• Lesson 1: Introduction to Artificial Intelligence

• Definition and basic concepts.

• History of AI.

• AI applications.

• Lesson 2: Machine Learning

• Supervised, unsupervised and reinforcement learning.

• Algorithms and examples.

• Lesson 3: Artificial Neural Networks

• Basic concepts of neural networks.

• Training of neural networks.

Module 2: AI Tools and Technologies

• Lesson 4: Python for AI

• Introduction to Python and relevant libraries (NumPy, pandas, scikit-learn).

• Lesson 5: Machine Learning Libraries

• TensorFlow and Keras.

• PyTorch.

• Lesson 6: AI Project Development

• Use of Jupyter Notebooks.

• Configuration of development environments.

Module 3: Practical Applications of AI

• Lesson 7: Computer Vision

• Object detection.

• Image recognition.

• Lesson 8: Natural Language Processing (NLP)

• Text processing.

• Language models.

Module 4: Ethics and Considerations in AI

• Lesson 9: Ethics in Artificial Intelligence

• Biases in data and algorithms.

• Privacy & Security.

Module 5: Final Project

• Students can apply what they learn in a final project, which may be an AI application or data analysis.

Resources and Tools:

• Python: It is the most used programming language in AI due to its large number of libraries and resources.

• Jupyter Notebooks: For interactive experimentation.

• TensorFlow and Keras: Popular tools for neural network development.

• PyTorch: Another powerful library for neural networks.

• Scikit-learn: For classical machine learning algorithms.

• Public databases and datasets: Such as MNIST, CIFAR-10, IMDB, etc.

• Cloud platforms: Such as Google Colab, AWS, or Microsoft Azure for access to computing resources.

• Books and online courses: Like Machine Learning by Andrew Ng on Coursera or Deep Learning by Ian Goodfellow.

• Online forums and communities: Such as Stack Overflow, Reddit (r/MachineLearning), and GitHub for additional resources and help.

Remember that AI is a constantly evolving field, so it is important to keep the course updated and encourage research and continuous learning among students. Good luck with your AI course!

Module 1: Fundamentals of Artificial Intelligence

Lesson 1: Introduction to Artificial Intelligence

Artificial intelligence (AI)