DEEP LEARNING

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Start 21 February 2026

Course description

Mata kuliah ini menyajikan materi tentang metode pembelajaran mendalam (deep learning) dengan aplikasi untuk visi komputer, pemrosesan bahasa alami, biologi, dan banyak lagi. Mahasiswa akan memperoleh pengetahuan dasar tentang algoritma pembelajaran mendalam (deep learning) yang meliputi deep feedforward neural networks, deep sequence modelling, deep convolution network serta deep generative modelling dan mendapatkan pengalaman praktis dalam membangun jaringan saraf di TensorFlow. Pada minggu-minggu pertama, mahasiswa diajak mengingat kembali konsep matematika aljabar linier serta jaringan saraf tiruan yang merupakan dasar dari algoritma-algoritma deep learning.

What you’ll learn

MK Deep Learning - 14624533 - 3 SKS
1. Konsep Dasar Deep Learning
2. Dasar Matematika Untuk Mesin Pemelajar
3. Deep Feedforward Networks
4. Regularization For Deep Learning
5. Optimization for Deep Learning
6. Deep Convolutional Networks
7. Deep Sequence Modelling
8. Evaluasi Tengah Semester

9. Deep Generative Modeling
10. Practical Methodology
11. Application Deep Feedforward Network in TensorFlow
12. Application Convolutional Neural Network in Tensor Flow
13. Application Recurrent Neural Network in Tensor Flow
14. Application Deep Convolution Generative Adversarial Network (DC-GAN) in Tensor Flow
15. Ujicoba / Implementasi Hasil Proyek
16. Seminar Hasil Proyek Akhir (Deep Learning Day)

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