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IBM Deep Learning with PyTorch, Keras and TensorFlow
Coursera
Professional Certificate
Unknown

IBM Deep Learning with PyTorch, Keras and TensorFlow

IBM

Develop advanced deep learning skills to build, train, and deploy neural network models using PyTorch, Keras, and TensorFlow in 3 months.

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About this Course

The global deep learning market is set to grow 23% annually to 2030 (Grand View Research) . This IBM Deep Learning with PyTorch, Keras and TensorFlow Professional Certificate builds the job-ready skills and practical experience AI techies need to catch the eye of employers. Deep learning is a branch of machine learning powering the generative AI revolution. It uses multilayered neural networks, called deep neural networks, to simulate the complex decision-making power of the human brain. During the program, you’ll learn to build, train, and deploy deep learning models . You’ll master fundamental concepts of machine learning and deep learning, including supervisedlearning , using Python. You’ll learn to develop transformer models for sequential data and time series predictions and apply unsupervised learning and reinforcement learning . Plus, you’ll apply popular libraries such as Keras, PyTorch, and TensorFlow to industry problems using object recognition,image and natural language processing. You’ll also gain valuable hands-on experience in labs and projects using PyTorch with deep learning models, creating custom layers and models using Keras, integrating Keras with TensorFlow 2, and developing advanced convolutional neural networks (CNNs ). If you’re looking to take the next step in your AI or data science career, this IBM Professional Certificate will give you job-ready skills and practical experience employers are looking for, so ENROLL TODAY!

What You'll Learn

  • Acquire job-ready deep learning skills using PyTorch, Keras, TensorFlow
  • Create projects, models, and neural networks with Keras and PyTorch
  • Train and optimize regression models using gradient descent
  • Build advanced CNNs and transformer models

Prerequisites

  • Basic familiarity with terminology and concepts
  • Readiness to practice through applied exercises

Instructors

W

Wojciech 'Victor' Fulmyk

R

Ricky Shi

Data Scientist

A

Aman Aggarwal

T

Tenzin Migmar

Topics

Machine Learning
Data Science
Algorithms
Computer Science
Artificial Neural Networks
Autoencoders
Computer Vision
Convolutional Neural Networks
Data Preprocessing
Deep Learning

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

تعلم الآلة
علوم البيانات
الخوارزميات
علوم الحاسوب
الشبكات العصبية الاصطناعية
المُشفرات التلقائية
رؤية الحاسوب
الشبكات العصبية الالتفافية
Data Preprocessing
Deep Learning

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