Deep Learning Course (with Keras & TensorFlow) in Atlanta

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Deep Learning Course Overview

The deep learning course with tensorflow training in Atlanta includes the language and basic concepts of artificial neural networks, PyTorch, autoencoders, etc. Upon completion of the deep learning course with tensorflow training in Atlanta, you can create a deep learning model, interpret the results, and create a learning project.

Skills Covered

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

Benefits

With a deep learning course with tensorflow training in Atlanta, the global deep learning system market is poised to touch a mammoth USD 93.34 billion in 2028 with a compound annual growth rate of 39.1%. With a deep learning course with tensorflow training in Atlanta, one can gain skills required for the field.

  • Designation
  • Annual Salary
  • Hiring Companies
  • Annual Salary
    $83KMin
    $113KAverage
    $154KMax
    Source: Glassdoor
    Hiring Companies
    Accenture hiring for Data Scientist professionals in Atlanta
    Oracle hiring for Data Scientist professionals in Atlanta
    Microsoft hiring for Data Scientist professionals in Atlanta
    Walmart hiring for Data Scientist professionals in Atlanta
    Amazon hiring for Data Scientist professionals in Atlanta
    Source: Indeed
  • Annual Salary
    $51KMin
    $72KAverage
    $110KMax
    Source: Glassdoor
    Hiring Companies
    Qualcomm hiring for AI Engineer professionals in Atlanta
    Nvidia hiring for AI Engineer professionals in Atlanta
    LarsenAndTurbo hiring for AI Engineer professionals in Atlanta
    Honeywell hiring for AI Engineer professionals in Atlanta
    Source: Indeed

Training Options

Corporate Training

Upskill or reskill your teams

  • Flexible pricing & billing options
  • Private cohorts available
  • Training progress dashboards
  • Skills assessment & benchmarking
  • Platform integration capabilities
  • Dedicated customer success manager

Deep Learning Course Curriculum

Eligibility

The demand for skilled deep learning engineers in all walks of life is booming, so this deep learning course with tensorflow training in Atlanta with Keras and Tensorflow certification training is very suitable for intermediate and advanced professionals. We especially recommend this deep learning course with tensorflow training in Atlanta to software engineers, data scientists, data analysts and statisticians who are interested in deep learning.
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Pre-requisites

Participants of the deep learning course with tensorflow training in Atlanta should be familiar with the basics of programming, have a solid understanding of the basics of statistics and mathematics, and have a firm grasp on the vital learning areas of machine learning. Candidates with this deep learning course with tensorflow training in Atlanta are highly preferred by the companies for the jobs.
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Course Content

  • Section 1 - Deep Learning with Keras and Tensorflow (IBM)

    Preview
    • Lesson 01: Deep Learning with Keras and Tensorflow (IBM)

      • 1.01 Deep Learning with Keras and Tensorflow (IBM)
  • Section 2 - Deep Learning with Keras and Tensor Flow (Live Classes)

    Preview
    • Lesson 1 - Course introduction

      03:11Preview
      • Introduction
      • Accessing Practice Lab
        03:11
    • Lesson 2 - AI and Deep learning introduction

      • What is AI and Deep learning
      • Brief History of AI
      • Recap: SL, UL and RL
      • Deep learning : successes last decade
      • Demo & discussion: Self driving car object detection
      • Applications of Deep learning
      • Challenges of Deep learning
      • Demo & discussion: Sentiment analysis using LSTM
      • Fullcycle of a deep learning project
      • Key Takeaways
      • Knowledge Check
    • Lesson 3 - Artificial Neural Network

      • Biological Neuron Vs Perceptron
      • Shallow neural network
      • Training a Perceptron
      • Demo code: Perceptron ( linear classification) (Assisted)
      • Backpropagation
      • Role of Activation functions & backpropagation
      • Demo code: Backpropagation (Assisted)
      • Demo code: Activation Function (Unassisted)
      • Optimization
      • Regularization
      • Dropout layer
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project (MNIST Image Classification)
    • Lesson 4 - Deep Neural Network & Tools

      • Deep Neural Network : why and applications
      • Designing a Deep neural network
      • How to choose your loss function?
      • Tools for Deep learning models
      • Keras and its Elements
      • Demo Code: Build a deep learning model using Keras (Assisted)
      • Tensorflow and Its ecosystem
      • Demo Code: Build a deep learning model using Tensorflow (Assisted)
      • TFlearn
      • Pytorch and its elements
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Build a deep learning model using Pytorch with Cifar10 dataset
    • Lesson 5 - Deep Neural Net optimization, tuning, interpretability

      • Optimization algorithms
      • SGD, Momentum, NAG, Adagrad, Adadelta , RMSprop, Adam
      • Batch normalization
      • Demo Code: Batch Normalization (Assisted)
      • Exploding and vanishing gradients
      • Hyperparameter tuning
      • Interpretability
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Hyperparameter Tunning With Keras Tuner
    • Lesson 6 - Convolutional Neural Network

      • Success and history
      • CNN Network design and architecture
      • Demo code: CNN Image Classification (Assisted)
      • Deep convolutional models
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Image Classification
    • Lesson 7 - Recurrent Neural Networks

      • Sequence data
      • Sense of time
      • RNN introduction
      • LSTM ( retail sales dataset kaggle)
      • Demo code: Stock Price Prediction with LSTM (Assisted)
      • Demo code: Multiclass Classification using LSTM (Unassisted)
      • Demo code: Sentiment Analysis using LSTM (Assisted)
      • GRUs
      • LSTM Vs GRUs
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Stock Price Forecasting
    • Lesson 8 - Autoencoders

      • Introduction to Autoencoders
      • Applications of Autoencoders
      • Autoencoder for anomaly detection
      • Demo code: Autoencoder model for MNIST data (Assisted)
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Anomaly detection with Keras
  • Section 3 - Practice Projects

    Preview
    • Practice Projects

      • PUBG Players Finishing Placement Prediction
  • Free Course
  • Math Refresher

    Preview
    • Lesson 01: Course Introduction

      06:23Preview
      • 1.01 About Simplilearn
        00:28
      • 1.02 Introduction to Mathematics
        01:18
      • 1.03 Types of Mathematics
        02:39
      • 1.04 Applications of Math in Data Industry
        01:17
      • 1.05 Learning Path
        00:25
      • 1.06 Course Components
        00:16
    • Lesson 02: Probability and Statistics

      32:38Preview
      • 2.01 Learning Objectives
        00:29
      • 2.02 Basics of Statistics and Probability
        03:08
      • 2.03 Introduction to Descriptive Statistics
        02:12
      • 2.04 Measures of Central Tendencies​
        04:50
      • 2.05 Measures of Asymmetry
        02:24
      • 2.06 Measures of Variability​
        04:55
      • 2.07 Measures of Relationship​
        05:22
      • 2.08 Introduction to Probability
        08:36
      • 2.09 Key Takeaways
        00:42
      • 2.10 Knowledge check
    • Lesson 03: Coordinate Geometry

      06:31Preview
      • 3.01 Learning Objectives
        00:35
      • 3.02 Introduction to Coordinate Geometry​
        03:16
      • 3.03 Coordinate Geometry Formulas​
        01:51
      • 3.04 Key Takeaways
        00:49
      • 3.05 Knowledge Check
    • Lesson 04: Linear Algebra

      29:53Preview
      • 4.01 Learning Objectives
        00:29
      • 4.02 Introduction to Linear Algebra
        03:21
      • 4.03 Forms of Linear Equation
        05:21
      • 4.04 Solving a Linear Equation
        05:21
      • 4.05 Introduction to Matrices
        02:05
      • 4.06 Matrix Operations
        07:07
      • 4.07 Introduction to Vectors
        01:00
      • 4.08 Types and Properties of Vectors
        01:52
      • 4.09 Vector Operations
        02:39
      • 4.10 Key Takeaways
        00:38
      • 4.11 Knowledge Check
    • Lesson 05: Eigenvalues Eigenvectors and Eigendecomposition

      08:56
      • 5.01 Learning Objectives
        00:29
      • 5.02 Eigenvalues
        01:19
      • 5.03 Eigenvectors
        04:09
      • 5.04 Eigendecomposition
        02:21
      • 5.05 Key Takeaways
        00:38
      • 5.06 Knowledge Check
    • Lesson 06: Introduction to Calculus

      09:47Preview
      • 6.01 Learning Objectives
        00:30
      • 6.02 Basics of Calculus
        01:20
      • 6.03 Differential Calculus
        03:01
      • 6.04 Differential Formulas
        01:01
      • 6.05 Integral Calculus
        02:33
      • 6.06 Integration Formulas
        00:47
      • 6.07 Key Takeaways
        00:35
      • 6.08 Knowledge Check

Project

  • Project 1

    PUBG Players Finishing Placement Prediction

    Create a model that predicts players’ finishing placement based on their final stats, on a scale of 1 (first place) to 0 (last place).

  • Project 2

    Lending Club Loan Data Analysis

    Create a model that predicts whether a loan will go into default using the historical data.

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TensorFlow Exam & Certification

Deep Learning Certificate in Atlanta
  • Who provides the certification and how long is it valid for?

    Once you complete of the deep learning course with tensorflow training in Atlanta successfully, you will be awarded an industry-recognized course completion certificate from Simplilearn has lifelong validity. The deep learning course with tensorflow training in Atlanta will help you to fetch a well-paid job.

  • What do I need to do to unlock my Simplilearn certificate?

    To obtain a deep learning course with tensorflow training in Atlanta, you will need to:
    Attend one complete batch of this deep learning course with tensorflow training in Atlanta.
    Finish and acquire an evaluation for atleast one of the projects mentioned below;. 
    After the completion of the course, you will be given a certification of a deep learning course with tensorflow training in Atlanta.

  • What is the fee for the TensorFlow Developer certification exam?

    The deep learning course with tensorflow training in Atlanta exam costs $100, which includes one exam attempt. The deep learning course with tensorflow training in Atlanta will help you to expand your knowledge in this particular subject. 

  • What is the duration of the TensorFlow Developer certification exam?

    After you start the deep learning course with tensorflow training in Atlanta, you have 5 hours to complete and submit it. However, if you do not submit a response within 5 hours, the portal will automatically send your response for the deep learning course with tensorflow training in Atlanta after that time.

  • How many attempts do I have to pass the TensorFlow Developer certification exam?

    For the deep learning course with tensorflow training in Atlanta, you will have three attempts to pass the deep learning course with tensorflow course in Atlanta exam.  For the deep learning course with tensorflow course in Atlanta, there are no more attempts you can try.

  • What are the system requirements for taking the TensorFlow Developer certification exam?

    To be able to appear for the deep learning course with tensorflow training in Atlanta examination, here are the minimum requirements that you need to have:

    • RAM - 4 GB
    • Disk Space - 2.5 GB and another 1 GB for caches
    • Monitor resolution - 1024 x 768
    • Operating system - officially released 64-bit versions of
    • macOS 10.13 or subsequent upgrades, Microsoft Windows 8 or future versions, or any Linux distribution supporting tools including Gnome, KDE, or Unity DE.
    • These are the minimum requirements for the deep learning course with tensorflow training in Atlanta examination

  • What are the benefits of taking the TensorFlow Developer certification exam?

    Here are the benefits of taking the deep learning course with tensorflow training in Atlanta:

    • Learn new things about Machine Learning - This deep learning course with tensorflow training in Atlanta exam will help you increase your proficiency in Machine Learning.
    • Receive recognition - Once you are certified, it is imperative that you will be recognized by the TensorFlow community.
    • Showcase skills - The deep learning course with tensorflow training in Atlanta is internationally recognized and attests to the knowledge that you possess and as an extension also is proof of the skills you’ve practiced and perfected with this course.
    • The deep learning course with tensorflow training in Atlanta also helps one to build their passion for this subject.

  • How do I crack the Tensorflow Developer certification exam?

    The best way to pass the deep learning course with tensorflow training in Atlanta exam is to take this deep learning course with tensorflow training in Atlanta. After completing the deep learning course with tensorflow training in Atlanta, you will be able to register and take the TensorFlow developer certification exam. There will be five categories during the exam, and students will complete five models, one for each category. These categories include basic ML models, models from learning data sets, CNNs with real image data sets, NLP text classification with real text data sets, and sequence models with real numerical data sets. This exam can be taken on a system that supports the requirements of PyCharm IDE.

Deep Learning Training Reviews

  • A.Anthony Davis

    A.Anthony Davis

    Kingston

    The Simplilearn Data Scientist Master’s Program is an awesome course! You learn how to solve real-world problems, and the wide variety of projects give you hands-on experience to make you industry-ready. The lecturers are experts and share their knowledge energetically. Thank you for an excellent learning experience.

  • Abhishek Tripathi

    Abhishek Tripathi

    Bangalore

    Good online content for data science. I completed Data Science with R and Python. The instructors have good knowledge on the subject. Self-learning videos help a lot, too. Thanks, Simplilearn.

  • Angiras Modak

    Angiras Modak

    Associate System Engineer at IBM India Pvt. Ltd., Kolkata

    Simplilearn is one of the best online training providers available. The trainer was really great in explaining the concepts to the minute detail and also gave multiple real-world examples. The course content was very informative. I understood the concept of CNN. Overall I really enjoyed the training a lot.

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Why Join this Program

  • Develop skills for real career growthCutting-edge curriculum designed in guidance with industry and academia to develop job-ready skills
  • Learn from experts active in their field, not out-of-touch trainersLeading practitioners who bring current best practices and case studies to sessions that fit into your work schedule.
  • Learn by working on real-world problemsCapstone projects involving real world data sets with virtual labs for hands-on learning
  • Structured guidance ensuring learning never stops24x7 Learning support from mentors and a community of like-minded peers to resolve any conceptual doubts

Deep Learning Training FAQs

  • What is the salary of a machine learning engineer with TensorFlow skills in Atlanta?

    A machine learning engineer with TensorFlow skills in Atlanta earns an average salary of $101,034 per annum, a minimum of $68k, and a maximum of $147k is being offered based on an individual’s experience. A deep learning course with a TensorFlow training course in Atlanta will help you earn more.

  • What are the major companies hiring for Machine Learning engineers with TensorFlow skills in Atlanta?

    The companies that hire machine learning engineers with TensorFlow skills in the United States Of America are Numenta, Amazon, Warner India, Microsoft, and Inspirit AI. An individual who has completed a deep learning course with a TensorFlow training course in Atlanta has more chances to get hired by any one of these companies.

  • What are the major industries in Atlanta?

    According to the BLS, employment in Atlanta remained strong and grew at the rate of 3.1 percent every year. Majorly due to its rapidly developing industries. Various industries that have shown tremendous growth in the economy of Atlanta are healthcare, education, technology, wireless networking, aviation, logistics, and manufacturing.

  • How to become a machine learning engineer with TensorFlow skills in Atlanta?

    A machine learning engineer should possess a solid foundation in mathematics, data analysis, and software learning. Through proper training, you can become an expert in machine learning and can gain additional knowledge in using the TensorFlow platform.

    Here is how you can become a machine learning engineer with TensorFlow skills in Atlanta,

    • Master in utilizing the TensorFlow framework in various forms.
    • Take up courses related to machine learning and improve your skills in it.
    • Materialize using ML algorithms. Act on real-life problems to get practical solutions.
    • Enhance your skills in data evaluation, data modeling, computer science, coding, and programming languages.

  • How to find a deep learning course with TensorFlow training courses in Atlanta?

    Deep learning is a function involved in artificial intelligence. Along with TensorFlow training, you could master this profession. You can find a course related to deep learning and TensorFlow training by using different sources. However, you should choose the appropriate one that meets your needs and requirements.

    Tips in finding a deep learning course with TensorFlow training courses in Atlanta,

    • Explore the internet to find ones offered by renowned institutions.
    • Speak with the seniors in the field to clear your doubts regarding the courses.
    • Analyze the course details, timings, and fee and pick the right course.

  • 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 Deep Learning Training with TensorFlow & Keras certification, 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. Deep Learning Training 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.

    Unlock New Frontiers: Discover More Tensorflow Courses for Career Growth.

  • 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.

  • 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 is online classroom training?

    All of the TensorFlow training classes are conducted via live online streaming. These classes for the TensorFlow course are interactive sessions that enable you to ask questions and participate in discussions during class time.

  • Who are the instructors and how are they selected?

    All of our highly qualified trainers are Deep Learning and Machine Learning industry experts with years of relevant industry experience. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating remain on our faculty.

  • How will the labs be conducted?

    Simplilearn provides Integrated labs for all the hands-on execution of projects. The learners will be guided on all aspects, from deploying tools to executing hands-on exercises.

  • What is Global Teaching Assistance?

    Our teaching assistants are a dedicated team of subject matter experts here to help you get certified in TensorFlow in your first attempt. They engage students proactively to ensure the Deep Learning Course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance. Teaching Assistance is available during business hours.  

  • Is this live training or will I watch pre-recorded videos?

    The TensorFlow certification training is conducted through live streaming. They are interactive sessions that enable you to ask questions and participate in discussions during class time. We do, however, provide recordings of each TensorFlow course session you attend for your future reference. Classes are attended by a global audience to enrich your learning experience.

  • What if I miss a class?

    Simplilearn provides recordings of each class of Deep Learning course so you can review them as needed before the next session. With Flexi-pass, Simplilearn gives you access to all classes for 90 days so that you have the flexibility to choose sessions as per your convenience.

  • What is covered under the 24/7 Support promise?

    We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your Deep Learning course online with us.

  • How do I enroll for the Deep Learning course?

    You can enroll for this Deep Learning Training on our website and make an online payment using any of the following options: 

    • Visa Credit or Debit Card
    • MasterCard
    • American Express
    • Diner’s Club
    • PayPal

    Once payment is received you will automatically receive a payment receipt and access information via email.

  • If I need to cancel my enrollment, can I get a refund?

    Yes, you can cancel your enrollment if necessary. We will refund the Deep Learning course price after deducting an administration fee. To learn more, please read our Refund Policy.

  • How can I learn more about this Deep Learning course?

    Contact us using the form on the right of any page on the Simplilearn website, or select the Live Chat link. Our customer service representatives can provide you with more details.

Deep Learning Course (with Keras & TensorFlow) in Atlanta

Atlanta is in between DeKalb County and Fulton County in Georgia. The cost of living in the city as a whole is 2% lower than the national average. Atlanta, the largest city in Georgia, is also the 37th largest city in the United States. It has a population of approximately 5.9 Billion.

Atlanta attained a GDP of 371.83 billion US Dollars in 2019. Its GDP per capita stood at $56,840 in 2017. Surrounded by trees, the city’s climate in summer is hot and moist, and it is cold and wet in winter. Atlanta ranks as the eighth busiest place in the country for its heavy automotive usage. The weather here is partly cloudy throughout the year.

Atlanta is renowned for its film industry. The Walking Dead, The Hunger Games, and the Marvel Cinematic Universe are some of Atlanta’s film sites that one should visit. It is also famous for its museums and parks. Famous historic places to visit in Atlanta are,

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