Bab 1: Pengenalan AI
Apa itu AI? Weak AI vs Strong AI, sejarah, aplikasi di kehidupan sehari-hari.
Bab 2: Machine Learning Dasar
Supervised, Unsupervised, Reinforcement Learning. Dataset, training, testing.
# Contoh Python scikit-learn
from sklearn.model_selection import train_test_split
X_train, X_test = train_test_split(data, test_size=0.2)
Bab 3: Neural Networks
Perceptron, activation function, backpropagation, layers.
Bab 4: Deep Learning
CNN, RNN, LSTM, Transformers. Framework: TensorFlow, PyTorch.
Bab 5: Computer Vision
Image classification, object detection (YOLO), face recognition.
Bab 6: Natural Language Processing
Text processing, sentiment analysis, chatbots, translation.
Bab 7: AI Ethics & Deployment
Bias, privacy, deployment (Docker, cloud), MLOps.
Bab 8: Proyek AI
Membuat chatbot, image classifier, recommendation system.