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Deep Learning with Python Practice Exam

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Deep Learning with Python


About Deep Learning with Python

Python is the ideal choice for machine learning and AI-based applications because of its flexibility, platform neutrality, availability of excellent libraries and frameworks for AI and machine learning (ML), simplicity, and consistency. These increase the language's general appeal.

Deep Learning with python has gained immense popularity across the globe resulting in huge demand for certified professionals.


Why is Deep Learning with Python important?

Python provides the stability, versatility, and wide range of tools needed for a machine learning or artificial intelligence project. From the phases of creation through deployment and up until the maintenance stage, Python allows developers to be productive and confident in the product that they are manufacturing.

It's simple to comprehend Python, and once you do, you may utilize those abilities to launch a fantastic career in the quickly growing data science sector. Even better, as more and more machine learning applications are developed daily, there will be a high need for Python programmers, which will benefit your career.

Deep Learning with Python certified professionals, executives and managers are in high demand in companies across the globe.


Who should take the Deep Learning with Python Exam?

  • Data scientists
  • Programmers
  • Professional mathematicians willing to learn how to analyze data programmatically
  • Python Developers
  • AI/ML Developers


Knowledge and Skills required for the Deep Learning with Python

Critical thinking and communication skills helps candidate to gain quick success for career in deep learning with python.


Deep Learning with Python Practice Exam Objectives

Deep Learning with Python exam focuses on assessing your skills and knowledge in machine learning, deep learning and Python language,


Deep Learning with Python Practice Exam Pre-requisite

There are no prerequisites for the Deep Learning with Python exam. Candidates who are well versed in machine learning, deep learning and Python language can easily clear the exam.


Deep Learning with Python Certification Course Outline

  1. Overview of Deep Learning
  2. Why is Deep Learning required?
  3. Concept of ANN
  4. Anatomy and function of neurons
  5. The architecture of a neural network
  6. Single-layer perceptron (SLP) model
  7. Radial Basis Network (RBN)
  8. Multi-layer perceptron (MLP) Neural Network
  9. Recurrent neural network (RNN)
  10. Long Short-Term Memory (LSTM) networks
  11. Boltzmann Machine Neural Network
  12. What is the Activation Function?
  13. Rectified Linear Unit (ReLU) function
  14. What is Stochastic Gradient Decent?
  15. Advantages and disadvantages of Neural Networks
  16. Applications of Neural Networks
  17. Exploring the dataset
  18. Building the Artificial Neural Network
  19. Compiling the artificial neural network
  20. Components of convolutional neural networks
  21. Building the CNN model


Exam Format and Information

Certification name – Certificate in Deep Learning with Python
Exam duration – 60 minutes
Exam type - Multiple Choice Questions
Eligibility / pre-requisite - None
Exam language - English
Exam format - Online
Passing score - 25
Exam Fees  - INR 1199



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$7.99
Format
Practice Exam
No. of Questions
30
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Online, Lifelong Access
Test Modes
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Deep Learning with Python Practice Exam

Deep Learning with Python Practice Exam

  • Test Code:1611-P
  • Availability:In Stock
  • $7.99

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Deep Learning with Python


About Deep Learning with Python

Python is the ideal choice for machine learning and AI-based applications because of its flexibility, platform neutrality, availability of excellent libraries and frameworks for AI and machine learning (ML), simplicity, and consistency. These increase the language's general appeal.

Deep Learning with python has gained immense popularity across the globe resulting in huge demand for certified professionals.


Why is Deep Learning with Python important?

Python provides the stability, versatility, and wide range of tools needed for a machine learning or artificial intelligence project. From the phases of creation through deployment and up until the maintenance stage, Python allows developers to be productive and confident in the product that they are manufacturing.

It's simple to comprehend Python, and once you do, you may utilize those abilities to launch a fantastic career in the quickly growing data science sector. Even better, as more and more machine learning applications are developed daily, there will be a high need for Python programmers, which will benefit your career.

Deep Learning with Python certified professionals, executives and managers are in high demand in companies across the globe.


Who should take the Deep Learning with Python Exam?

  • Data scientists
  • Programmers
  • Professional mathematicians willing to learn how to analyze data programmatically
  • Python Developers
  • AI/ML Developers


Knowledge and Skills required for the Deep Learning with Python

Critical thinking and communication skills helps candidate to gain quick success for career in deep learning with python.


Deep Learning with Python Practice Exam Objectives

Deep Learning with Python exam focuses on assessing your skills and knowledge in machine learning, deep learning and Python language,


Deep Learning with Python Practice Exam Pre-requisite

There are no prerequisites for the Deep Learning with Python exam. Candidates who are well versed in machine learning, deep learning and Python language can easily clear the exam.


Deep Learning with Python Certification Course Outline

  1. Overview of Deep Learning
  2. Why is Deep Learning required?
  3. Concept of ANN
  4. Anatomy and function of neurons
  5. The architecture of a neural network
  6. Single-layer perceptron (SLP) model
  7. Radial Basis Network (RBN)
  8. Multi-layer perceptron (MLP) Neural Network
  9. Recurrent neural network (RNN)
  10. Long Short-Term Memory (LSTM) networks
  11. Boltzmann Machine Neural Network
  12. What is the Activation Function?
  13. Rectified Linear Unit (ReLU) function
  14. What is Stochastic Gradient Decent?
  15. Advantages and disadvantages of Neural Networks
  16. Applications of Neural Networks
  17. Exploring the dataset
  18. Building the Artificial Neural Network
  19. Compiling the artificial neural network
  20. Components of convolutional neural networks
  21. Building the CNN model


Exam Format and Information

Certification name – Certificate in Deep Learning with Python
Exam duration – 60 minutes
Exam type - Multiple Choice Questions
Eligibility / pre-requisite - None
Exam language - English
Exam format - Online
Passing score - 25
Exam Fees  - INR 1199