Kursus Machine Learning: Training Machine Learning Master Class Selama 3 Hari

Silabus 3 Hari Machine Learning Master Class

Durasi: 3 hari (09:00 – 16:00) Istirahat: 12:00 – 13:00 Level: Master Class (Tingkat Lanjut) Metode: Teori, Hands-on Coding, Studi Kasus, Diskusi

Hari 1: Fundamentals & Feature Engineering

Sesi 1: Introduction to Advanced Machine Learning (09:00 – 10:30)

• Tren terbaru dalam Machine Learning

• Perbedaan Traditional ML vs. Deep Learning

• Pipeline Machine Learning yang optimal

• Best practices dalam pengolahan dataset besar

Sesi 2: Feature Engineering & Data Preprocessing (10:30 – 12:00)

• Data preprocessing untuk model high-performance

• Teknik Feature Engineering: Scaling, Encoding, Transformasi

• Feature Selection & Dimensionality Reduction (PCA, LDA)

Istirahat (12:00 – 13:00)

Sesi 3: Model Selection & Hyperparameter Tuning (13:00 – 14:30)

• Pemilihan model optimal berdasarkan karakteristik data

• Grid Search vs. Random Search vs. Bayesian Optimization

• Tuning model untuk meningkatkan akurasi

Sesi 4: Model Evaluation & Interpretability (14:30 – 16:00)

• Evaluasi model dengan metrik yang tepat

• SHAP & LIME untuk interpretasi model

• Model deployment considerations

Hari 2: Deep Learning & Computer Vision

Sesi 1: Introduction to Deep Learning & Neural Networks (09:00 – 10:30)

• Arsitektur Neural Networks (CNN, RNN, Transformer)

• Optimasi model Deep Learning (Adam, RMSprop, SGD)

• Implementasi Feedforward Neural Network (Hands-on)

Sesi 2: Computer Vision with Convolutional Neural Networks (CNN) (10:30 – 12:00)

• Konsep CNN: Convolution, Pooling, Fully Connected Layer