Curriculum Vitae
Farah Tri Nurul Hayati
Portfolio
Seorang fresh graduate Statistika dari Universitas Indonesia dengan minor data science. Dengan keahlian dalam analisa data, Farah berkomitmen untuk terus belajar dan berkembang dalam data science, serta berkontribusi pada inovasi dan pengalaman.
Januari 2024
Universitas Indonesia
S1 • Statistika • IPK 3.4
September 2024 - Agustus 2025
INTERNSHIP HOLDING 2024 - Fungsi Organization Capability (Quality Management & Standardization)
PT Pertamina (Persero) • Magang
Desember 2023 - Februari 2024
Data Analytics Intern
Ivosights • Magang
Saya menganalisis data social dan online media stream untuk empat perusahaan dan lima proyek, termasuk Astra, PLN, Pos Indonesia, Indofood, Vinfast, dan proyek pemerintah seperti Kawasan Ekonomi Eksklusif (KEK). Saya menerapkan data analytics untuk mengidentifikasi customer trends dan menyusun outreach strategies. Selain itu, saya membuat dan merangkum data visualizations untuk menyaring key trends, membantu dalam decision-making, dan meningkatkan pemahaman tentang customer behavior bagi client brands.
Maret 2021 - Februari 2023
Staf Ahli
Himpunan Mahasiswa Departemen Matematika FMIPA UI • Organisasi
Saya bertanggung jawab untuk menganalisis dan menyiapkan 20% laporan, undangan, dan sertifikat sebagai intern di biro kesekretariatan. Selain itu, saya mengelola akun Line dan Instagram resmi untuk departemen keislaman, dengan rutin membagikan postingan konten keislaman di media sosial setiap minggu untuk menjaga engagement secara online.
Mei 2023
TensorFlow: Data and Deployment
DeepLearning.AI • BDK6JG5AE5DN
In this specialization, I continued to develop my understanding of machine learning with TensorFlow: Data and Deployment. I have gone beyond basic modeling and learned how to train and run my models within a browser, optimize machine learning models for mobile devices, and create effective data pipelines with TensorFlow Data
Services.
Media
Mei 2023
DeepLearning.AI TensorFlow Developer
DeepLearning.AI • NVPP852K8H3E
Build and train neural networks using TensorFlow,
how to improve network performance using convolutions as i train it to identify real-world images, how to teach machines to understand, analyze, and respond to human speech with natural language processing systems, and more.
Media
April 2023
Machine Learning Specialization
DeepLearning.AI • ZMVCRFQ2EJTQ
Modern machine learning concepts, including supervised learning (linear regression, logistic regression, neural networks, decision trees), unsupervised learning clustering, anomaly detection), recommender systems, and reinforcement learning.
Media
Maret 2023
Mathematics for Machine Learning Specialization
Imperial College London • GJCKMNSEDSY3
A sequence of 3 courses on the prerequisite mathematics for applications in data science and machine learning. Successful participants learn how to represent data in a linear algebra context and manipulate these objects mathematically.