Deep Learning with TensorFlow Training Certification Course

SKU: 8402
9 Lesson
|
40 Hours
Deep Learning with TensorFlow training by igmGuru will play a key role in ensuring you learn this open-source ML framework best practices efficiently for training a neural network for computer vision apps. Learn to explore strategies while handling real-world image data to facilitate preventing overfitting via our Deep Learning with TensorFlow online course. Prepare to ace the TensorFlow certification as you learn to build NLP systems with it.

Deep Learning Course Overview

Deep Learning with TensorFlow training by igmGuru will play a key role in ensuring you learn this open-source ML framework efficiently to train a neural network for computer vision apps. Learn to explore strategies while handling real-world image data to facilitate preventing overfitting via our Deep Learning with TensorFlow online course. Prepare to ace the TensorFlow certification exam as you learn to build NLP systems with it.

Our Deep Learning with TensorFlow course includes the basics of Deep Learning and how to use TensorFlow to build and train Deep Learning models. igmGuru's Deep Learning with TensorFlow training online program has been curated by the industry leader experts, which will help students to learn from basic to advanced Deep Learning with TensorFlow practices. This Deep Learning with TensorFlow course is aligned with Deep Learning with TensorFlow certification exam.

Deep Learning with TensorFlow is a course that covers the basics of Deep Learning and how to use TensorFlow, an open-source software library for machine learning, to build and train Deep Learning models. The Deep Learning with TensorFlow course typically covers topics such as artificial neural networks, convolutional neural networks, and recurrent neural networks, and how to use TensorFlow to implement these models. It also covers how to train and evaluate Deep Learning models on various datasets and how to deploy them in real-world applications. The course is crafted for students with a basic understanding of machine learning and programming concepts.

Deep Learning is considered a niche skill. It is an ever-expanding field and is widely regarded as an extension of the Machine Learning algorithm. Deep Learning is an aspect of artificial intelligence that depends on data representations rather than task-specific algorithms. There are a lot of applications that are a by-product of Deep Learning techniques starting from self-driving cars, movie suggestions appearing in various streaming platforms, word suggestions being provided when you compose a WhatsApp message, etc. Deep Learning skill is highly in demand in the market as you need to have a very good understanding of the algorithms along with a very good foundation of machine learning concepts. 

In fact, as per one of the recent job-related surveys, it was found that the demand for Deep Learning using TensorFlow far outstretches the supply. And for the same reason, there are a lot of organizations that have started upskilling their employees to fulfill these gaps.

Similar to machine learning, there is a tremendous growth rate for Deep Learning related jobs. Another reason which could oblige you to seriously think about this skill set is automation. As we must have heard about reports stating that there are a lot of jobs which could vanish due to automation in the next few years.

igmGuru offers one of the best courses in the market that covers all the skills required to become proficient in the Deep Learning domain. There will be a lot of business-world projects in which learners would be needed to enhance understanding. Hence, by leveraging igmGuru’s Deep Learning with TensorFlow certification training, learners will be exposed to numerous high-paying opportunities.

Learners who are interested in the course need to have a very good understanding of Machine Learning techniques. 

There are a lot of companies hiring Deep Learning engineers/specialists. Notable among them are IT companies like Microsoft, Intel, Nvidia, Flipkart, Amazon, and a lot more. Learners who would finally be acquiring the skill set of Deep Learning could end up in the below-mentioned profiles

  1. Deep Learning engineer
  2. Deep Learning specialist
  3. Artificial Intelligence engineer
  4. Data Scientist with DL skill
Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised or unsupervised. Artificial neural networks were inspired by information processing and distributed communication nodes in biological systems.

There is a lot of different Deep Learning architecture, which we will study in this training course ranging from deep neural networks, deep belief networks, recurrent neural networks, and convolutional neural networks. They have been applied to fields including computer vision, machine vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, and material inspection. Some of these architectures have been known to produce better results than humans and will be discussed in the training courses.

We will be using the open-source library known as TensorFlow while providing Deep Learning knowledge, which is developed and maintained by Google Brain. Tensorflow is an API that could be used in Python (as a library) to build and deploy various Deep Learning models. Tensorflow is suited mostly for Deep Learning algorithms but can also be used to build a machine learning algorithm. We will understand more about TensorFlow in this course and explore the various operations that we can perform on it. There are many other options available apart from TensorFlow, including how to build Deep Learning algorithms like Keras, Caffe framework, Mxnet, etc. Since TensorFlow is widely used in the industry, we also get a lot of community support for related issues. Deep Learning has been broadly classified into Supervised and Unsupervised learning.

What are the Objectives of Deep Learning with TensorFlow Course Online?

  • Learners would be made familiar with the various types of Deep Learning techniques under each supervised and unsupervised learning method in the Deep Learning with TensorFlow.
  • They would also have a very good idea about the usage of the techniques depending on the business problems.
  • Each session in Deep Learning with TensorFlow certification program ends with assignments and tasks that you need to solve based on the available dataset.
  • Further, you will work on many industry-specific projects that will solidify your skills in 

Deep learning has the potential to change the way businesses make decisions. These algorithms to be taught in deep learning TensorFlow training course takes massive amounts of unstructured data and build programs that can analyze natural language, sentiment, and other complicated data the way the human brain would, only better.

Deep learning models are transforming the way we approach business. Humans produce a massive amount of data, but up to now, we've been unable to use it fully. Now, deep learning algorithms are providing learning techniques and real-world solutions based on these large data sets. We will be exploring some of these techniques in deep learning the TensorFlow training course.

Deep Learning with TensorFlow course focuses on the development of computer programs that use data to understand patterns and relationships on their own. The primary aim is to allow the computers to learn automatically without human intervention or assistance and adjust actions accordingly. There is a stark difference in the way of finding a relationship between the different variables in Deep Learning and machine learning.

What are the Key Deliverables Deep Learning with TensorFlow Training Online

The course will mostly deal with the below things:

  • Difference between supervised and unsupervised techniques
  • Understanding the usage of supervised and unsupervised learning techniques
  • Choosing the best algorithm for a given problem
  • Understanding the various accuracy measures.

Key Features

Deep Learning Training Modules

1. Define Deep Learning
2. Neural Networks
3. Deep Learning Applications

1. What is a Perceptron
2. Logic Gates with Perceptrons
3. Activation Functions
4. Sigmoid
5. ReLU
6. Softmax
7. Hyperbolic Functions

1. Introduction
2. Perceptron Learning Rule
3. Gradient Descent Rule
4. Minimize Cost Function
5. Tuning Learning Rate
6. Stochastic vs Batch Gradient Descent

1. Intro to MLP
2. Forward propagation
3. Minimize Cost Function
4. Backpropagation
5. Convergence in a neural net
6. Overfitting and Capacity
7. Hyperparameters in an ANN

1. Intro to TensorFlow
2. Computational Graph
3. Key highlights
4. Creating a Graph
5. Regression example
6. Gradient Descent
7. Saving and Restoring Models
8. Tf.layers API
9. Keras-based networks
10. TensorBoard

1. Vanishing/Exploding Gradients
2. Xavier Initialization
3. Leaky ReLUs and ELUs
4. Batch Normalization
5. Transfer Learning
6. Unsupervised Pre-training
7. Optimizers
8. Regularization
9. Dropout

1. Intro to CNNs
2. Convolution Operation
3. Kernel filter
4. Feature Maps
5. Pooling
6. CNN Architecture
7. Implement CNN in TensorFlow

1. Intro to RNNs
2. Unfolded RNNs
3. Basic RNN Cell
4. Dynamic RNN
5. Training RNNs
6. Time-series predictions
7. LSTM
8. Word Embeddings
9. Seq2Seq Models
10. Implement RNN in TensorFlow

1. Autoencoders
2. Reinforcement Learning (RL)
3. Generative Adversarial Networks (GANs)

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US $ 599.00
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  • Duration : 40 hrs
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Deep Learning Certification Exam

How can I get TensorFlow Certification in 2024?

The Deep Learning with TensorFlow certification exam is a test that will assess your knowledge and understanding of the TensorFlow library & deep learning concepts. This exam is mostly chosen after completing a training on the subject matter. Those who have significant experience working with TensorFlow and DL also go for this course.

The exam covers topics such as artificial neural networks, convolutional neural networks, recurrent neural networks, and how to use TensorFlow to implement these models. It also covers how to train and evaluate deep learning models on various datasets, and how to deploy them in real-world applications. The format of the exam can vary, but it may include multiple choice questions, coding challenges, and practical exercises. Upon passing the exam, the individual will be awarded a certification, which can be used to demonstrate their expertise in the field to potential employers or clients.

  • Number of questions: 5
  • Exam cost: $100 USD
  • Duration: 5 hours
  • Passing percentage: 90%
Deep Learning Certification Exam

Deep Learning Online Training FAQ

This training will be conducted online through live meetings and will have a minimum total duration of 30 hours

All the sessions for deep learning TensorFlow training courses are always saved as videos and you can request the class video if you ever miss a class. However, you must provide genuine reasons for the same

Prior understanding of machine learning techniques will help participants a lot in getting a better understanding of this subject.

Yes, this course is certification-based training, and certification is provided online after one has successfully cleared the Deep Learning assignments and test with the minimum required cut-off.

The price of the online training course is listed on the website of IgmGuru. For the payment mode, we strictly do not accept cash entries. We accept payment through Credit Card / Debit Card / Online Banking App.

TensorFlow, developed by Google, is an open-source library that has essentially been developed for deep learning applications. Thus, igmGuru's Deep Learning with TensorFlow Training is sure to help you unlock the best career opportunities in the field.

Yes, obtaining a TensorFlow certificate can be worth it for individuals interested in pursuing a career in machine learning and deep learning. The certificate validates your proficiency in TensorFlow, a widely-used framework for building and deploying machine learning models. It demonstrates your knowledge and skills, making you stand out to potential employers. Additionally, the certification process often involves practical projects and assessments that provide valuable hands-on experience. However, it's important to note that while the certification can enhance your resume, practical experience and a strong understanding of machine learning concepts are equally important for success in the field.

Created by Google, TensorFlow is an important framework used widely to create Deep Learning models. While it is not used for only DL models, they are highly chosen to work together.

To train with TensorFlow models, undertake these steps -

- Install TensorFlow

- Load the dataset

- From the dataset, plot an image

- Outline the total classes in dataset

- Preprocessing and normalization

- Generate model graph

TensorFlow is known to have a steeper learning curve than many other machine learning tools. That said, there is nothing you cannot achieve with good training and excellent trainers. igmGuru’s Deep Learning with TensorFlow training will help you learn from the best.

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