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Deep Learning Course (with Keras & TensorFlow) Certification Training

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Last Update January 12, 2022
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About This Course

This Deep Learning course with TensorFlow certification training is developed by industry leaders and aligned with the latest best practices. You’ll master deep learning concepts and models using Keras and TensorFlow frameworks through this TensorFlow course. Learn to implement deep learning algorithms with our TensorFlow training and prepare for a career as a Deep Learning Engineer. Achieve our deep learning certification and gain a competitive edge over your peers in your next interview.

 

Deep Learning Course Overview

In this Deep Learning course with Keras and TensorFlow certification training, you will become familiar with the language and fundamental concepts of artificial neural networks, PyTorch, autoencoders, and more. Upon completion, you will be able to build deep learning models, interpret results, and build your own deep learning project.

 

Benefits

The global deep learning system market size is expected to reach USD 93.34 Billion at a steady CAGR of 39.1% in 2028

 

Deep Learning Course Curriculum

 

Eligibility
Demand for skilled Deep Learning Engineers is booming across a wide range of industries, making this Deep Learning course with Keras and Tensorflow certification training well-suited for professionals at the intermediate to advanced level. We recommend this Deep Learning course particularly for Software Engineers, Data Scientists, Data Analysts, and Statisticians with an interest in deep learning.

 

Pre-requisites

Participants in this Deep Learning certification training should have familiarity with programming fundamentals, a fair understanding of the basics of statistics and mathematics, and a good understanding of machine learning concepts.

Course Content

Lesson 1 – Welcome!
Lesson 2 – Introduction to Tensorflow
Lesson 3 – Convolutional Networks
Lesson 4 – Recurrent Neural Network
Lesson 5 – Restricted Boltzmann Machines (RBM)
Lesson 6 – Autoencoders
Lesson 7 – Course Summary

 

TensorFlow Training FAQs

 

What is Deep Learning?
Deep Learning, also known as Deep Neural Learning, is a subset of machine learning, an application of AI, where machines imitate the workings of the human brain and employ artificial neural networks to process the information.

 

What is TensorFlow?
TensorFlow is an open source library created and released by google for numerical computation and building deep learning models.

 

Why is Deep Learning important?
Companies are gathering a massive amount of data every day and analyzing them to draw meaningful business insights. Most of that data is in an unstructured format, i.e. in the form of text, image, audio, and video rather than numerical. Deep learning is quite effective for analyzing such types of data and has become vitally important for business decision making. With our TensorFlow certification course, you can learn all the essential deep learning concepts from scratch.

 

Why should I learn Deep Learning?
In traditional machine learning, most of the applied features need to be identified by a domain expert in order to reduce the complexity of the data. Whereas the biggest advantage of the Deep Learning algorithm is it tries to learn high-level features from data in an incremental manner, which makes the process simpler and popular. Deep Learning techniques outperform other techniques when the data size is large and complex, and also, this technique is behind many high-end innovations.

 

How do I become a Deep Learning Engineer?
This Deep Learning course with Keras and TensorFlow certification training will give you a complete overview of  Deep Learning concepts, enough to prepare you to excel in your next role as a Deep Learning Engineer. It will help you become familiar with artificial neural networks, PyTorch, autoencoders, and more. At the end of our best deep learning course online, you will get an industry-recognized course completion certificate from Simplilearn, which will be a testament to your skills with deep learning specialization.

 

Why should you take this Deep Learning course?
Deep learning skills are in high demand and offer professionals a clear edge over others when applying for top related job roles like Machine Learning Engineer, Data Scientist, or NLP Specialist. Requiring a high level of technical understanding, one may not find it easy to learn deep learning through self-study. Taking up this Deep Learning course is a better option where you get the right guidance from industry experts.

 

What kind of careers can I pursue with a background in Deep Learning?
With the relevant skills that you gain from our Deep Learning course, you can apply for top job roles like Machine Learning Engineer, Data Scientist, Business Intelligence Developer, NLP Scientist, and more.

 

Learning Objectives

Keras and TensorFlow Framework
PyTorch and its elements
Image Classification
Artificial Neural Networks
Autoencoders
Deep Neural Networks
Conventional Neural Networks
Recurrent Neural Networks
ADAM Adagrad and Momentum

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Material Includes

  • Keras and TensorFlow Framework
  • PyTorch and its elements
  • Image Classification
  • Artificial Neural Networks
  • Autoencoders
  • Deep Neural Networks
  • Conventional Neural Networks
  • Recurrent Neural Networks
  • ADAM Adagrad and Momentum
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