Lesson 1: Introduction to Artificial Intelligence
Lesson 2: History and Evolution
Lesson 3: Problem-solving methods
Lesson 4: AI applications across industries

Lesson 1: Introduction to Machine Learning
Lesson 2: Supervised Learning: Regression, Classification
Lesson 3: Unsupervised Learning: Clustering, Dimensionality Reduction
Lesson 4: Ensemble Learning
Lesson 5: Reinforcement Learning
Lesson 6: Model Evaluation and Validation

Lesson 1: Introduction to Deep Learning
Lesson 2: Artificial Neural Networks (ANNs)
Lesson 3: Convolutional Neural Networks (CNNs)
Lesson 4: Recurrent Neural Networks (RNNs) and LSTM
Lesson 5: Generative Adversarial Networks (GANs)
Lesson 6: Transfer Learning
Lesson 7: Hyperparameter Tuning

Lesson 1: Introduction to Natural Language Processing
Lesson 2: Text Preprocessing
Lesson 3: Text Classification
Lesson 4: Named Entity Recognition (NER)
Lesson 5: Sentiment Analysis
Lesson 6: Word Embeddings
Lesson 7: Sequence-to-Sequence Models
Lesson 8: Machine Translation

Lesson 1: Introduction to Computer Vision
Lesson 2: Image Processing Basics
Lesson 3: Image Classification
Lesson 4: Object Detection
Lesson 5: Image Segmentation
Lesson 6: Face Recognition
Lesson 7: Image Generation

Lesson 1: Ethics in AI Development
Lesson 2: Bias and Fairness in AI
Lesson 3: Explainable AI
Lesson 4: Privacy and Security Concerns
Lesson 5: Regulatory Landscape

Lesson 1: AI in Healthcare
Lesson 2: AI in Finance
Lesson 3: AI in Marketing and Sales
Lesson 4: AI in Autonomous Vehicles
Lesson 5: AI in Robotics
Lesson 6: AI in Gaming
Lesson 7: AI in Customer Service