Dev Certification for Machine Learning with Tensorflow (DCML) Preparation

Teknologi:

AI/Kognitif Machine Learning

Level: Kompetensi Sertifikasi 25 Jam Belajar

431

Siswa Terdaftar

Preparation course for taking the Dev Certification for Machine Learning with Tensorflow (DCML) by the dev.cert program.

Dev Certification for Machine Learning with Tensorflow (DCML) Preparation Partner

Belajar Sekarang

Informasi kelas Lihat silabus

Apa yang akan Anda dapatkan

Code Review

Kode yang Anda kerjakan akan di-review secara komprehensif oleh Reviewer.

Forum Diskusi

Diskusikan materi belajar dengan siswa lainnya.

Modul Tutorial

Materi bacaan elektronik disajikan dengan bahasa yang mudah dipahami.

Submission

Uji kemampuan teknis Anda dengan mengerjakan tugas submission.

Deskripsi

This course does not have graduation stages and certificates, you can only study in this course as long as your subscription or token is active.

Dev Certification for Machine Learning with Tensorflow (DCML) is part of the dev.id certification or dev.cert which aims to test your skills and help you achieve your dream career with project-based certifications.

As a Dev Certified for Machine Learning, you are expected to be able to use TensorFlow to demonstrate the skills needed to work on machine learning and deep learning. This preparation course has been designed by Dicoding as a partner of dev.id so that you can prepare yourself thoroughly before taking the Dev Certification for Machine Learning with Tensorflow (DCML).

DCML can increase your value to hiring partners.
DCML has been trusted directly by Google as a certification platform to test machine learning skills.
DCML graduates can feel confident when entering industry because they have validation and real proof of competence.
This preparation course has been created according to professional competence.
Curriculum Developers from this courses are graduates of the certification, so this course can be as similar as possible to the original certification.

Student Targets and Objectives

The course is intended for Machine Learning Engineers who want to take Dev Certification for Machine Learning with Tensorflow (DCML).
Before taking this preparation course, you are expected to have experience implementing machine learning. You can learn about implementing machine learning in the Machine Learning Engineer learning path from Dicoding.
At the end of the class, students can prepare themselves to take the Dev Certification for Machine Learning with Tensorflow (DCML).

Selengkapnya

Sembunyikan

Peralatan Belajar

Spesifikasi minimal perangkat:

Prosesor

Intel i3 (Recommended: Core i5 or higher)

Tools yang dibutuhkan untuk belajar:

PyCharm IDE

Lihat semua peralatan belajar

Peralatan Belajar

Spesifikasi minimal perangkat

Kelas ini membutuhkan spesifikasi perangkat seperti berikut:

RAM

4 GB or more

Layar

1366 x 768 (Rekomendasi Full HD 1920 x 1080)

Sistem Operasi

Windows, Linux, MacOS

Prosesor

Intel i3 (Recommended: Core i5 or higher)

Tools

Kelas ini membutuhkan beberapa tools berikut:

PyCharm IDE

Metode Ajar

Online - Self-paced Learning.
- Total study hours: 25 hours.
- Recommended study time: 10 hours per week (completed in 18 days).
- You decide for yourself how much time you will spend studying this course material as long as you are still actively enrolled in the course.
- This course does not have graduation stages and certificates, you can only study in this class as long as your subscription or token is active.
Teaching Facilities
- Discussion forum : Each course has a discussion forum that you can use to ask questions and discuss.

Lihat semua metode ajar

Metode Ajar

Online - Self-paced Learning.
- Total study hours: 25 hours.
- Recommended study time: 10 hours per week (completed in 18 days).
- You decide for yourself how much time you will spend studying this course material as long as you are still actively enrolled in the course.
- This course does not have graduation stages and certificates, you can only study in this class as long as your subscription or token is active.
Teaching Facilities
- Discussion forum : Each course has a discussion forum that you can use to ask questions and discuss.

Kontributor

Curriculum Developer yang membangun kelas ini: