AI study plan

• Fix this with free sources
  • freecodecamp.org

Week 1: Introduction to AI

• The History of Artificial Intelligence from the 1950s to Today
• Online course: Introduction to Artificial Intelligence by Stanford University on Coursera (4 hours)
• YouTube video: What is Artificial Intelligence? by ColdFusion (15 minutes)
• Programming project: Implement a basic AI algorithm in Python from scratch (2 hours)
  1. Choose an appropriate algorithm.
     • Decision Tree
     • K-Nearest Neighbors (KNN)
     • Linear Regression
  2. Use a dataset for training and testing.
  3. Evaluate the algorithm's performance.

Week 2: Machine Learning Fundamentals

• Online course: Machine Learning by Andrew Ng on Coursera (8 hours)
• YouTube video: How Machine Learning Works by freecodecamp.org (4 hours)
• Programming project: Build a linear regression model using scikit-learn in Python (3 hours)

Week 3: Deep Learning Basics

• Online course: Neural Networks and Deep Learning by deeplearning.ai on Coursera (8 hours)
• YouTube video: Introduction to Deep Learning by 3Blue1Brown (19 minutes)
• Programming project: Build a simple neural network using TensorFlow in Python (4 hours)

Week 4: Convolutional Neural Networks

• Online course: Convolutional Neural Networks by deeplearning.ai on Coursera (8 hours)
• YouTube video: Convolutional Neural Networks Explained by Brandon Rohrer (11 minutes)
• Programming project: Build a CNN to classify images using TensorFlow in Python (4 hours)

Week 5: Recurrent Neural Networks

• Online course: Sequence Models by deeplearning.ai on Coursera (8 hours)
• YouTube video: Recurrent Neural Networks Explained by Brandon Rohrer (10 minutes)
• Programming project: Build a simple RNN for language modeling using Keras in Python (4 hours)

Week 6: Natural Language Processing

• Online course: Natural Language Processing with Python by the University of Michigan on Coursera (8 hours)
• YouTube video: What is Natural Language Processing? by Tech With Tim (9 minutes)
• Programming project: Build a simple sentiment analysis model using NLTK in Python (4 hours)

Week 7: Reinforcement Learning

• Online course: Reinforcement Learning by David Silver on YouTube (8 hours)
• YouTube video: Reinforcement Learning Explained by CodeEmporium (15 minutes)
• Programming project: Implement Q-learning algorithm for a simple game using OpenAI Gym in Python (4 hours)

Week 8: Ethics in AI

• Online course: Ethics in AI by Oxford University on edX (8 hours)
• YouTube video: The Ethics of Artificial Intelligence by Harvard University (1 hour)
• Programming project: Write an essay on the ethical considerations of using AI in a specific industry (3 hours)

Week 9: Advanced Topics in Machine Learning

• Online course: Advanced Machine Learning Specialization by deeplearning.ai on Coursera (8 hours)
• YouTube video: Machine Learning Advanced Topics by Udacity (9 minutes)
• Programming project: Implement a GAN for image generation using TensorFlow in Python (4 hours)

Week 10: Reinforcement Learning Applications

• Online course: Deep Reinforcement Learning by Sergey Levine on YouTube (8 hours)
• YouTube video: Reinforcement Learning Applications by TechTalksTV (24 minutes)
• Programming project: Implement deep Q-learning algorithm for Atari game using OpenAI Gym in Python (4 hours)

Week 11: Natural Language Processing Applications

• Online course: Natural Language Processing with Deep Learning by Stanford University on Coursera (8 hours)
• YouTube video: Natural Language Processing Applications by deeplearning.ai (6 minutes)
• Programming project: Build a chatbot using a pre-trained transformer model in Python (4 hours)

Week 12: Capstone Project

• Programming project: Build an end-to end AI project that combines multiple techniques learned in the previous weeks, such as image recognition, natural language processing, and reinforcement learning. The project could be something like a virtual assistant that can recognize voice commands, answer questions, and interact with users in natural language. (10 hours)

Recommended Books

1. "Machine Learning Yearning" by Andrew Ng
2. "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
3. "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig.

Note: The time estimates for each week's activities are approximate and may vary depending on your learning pace. Also, the programming projects may require some prior programming experience in Python. If you are not familiar with Python, you may need to spend some additional time learning the basics of the language before starting the programming projects.