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AI with Cloud Automation

Objective: On completing this course, there will be ample opportunities for you to work as a Deep learning cloud engineer or AI cloud specialist or cloud engineer. You will be able to do some real world concepts like neural network, ANN, CNN, Cloud AWS etc. After completion of this course will be able work on real life projects like image processing, text classification, recommendation engine etc.

Technical Prerequisite: Knowledge of High level Mathematics, statistics, python and Machine learning will be highly required. Knowledge of cloud will be added advantage.

System Prerequisite: Min 8GB RAM, Windows 8 or above, High Speed internet connection

Suitable For: 3rd Yr / 4th Yr B.Tech. / Diploma / MCA / BCA students

AI with Cloud Automation Course Curriculum

Course Duration: 4/6 Weeks & 3/6 Months

Online : Regular Batches / Weekend Batches

Live Project


Soft Skill Development

Advanced Programs

  • What is AI and ML
  • Fields of AI
  • Application of ML in AI
  • Types of ML
  • Limitations of ML
  • Solutions using deep learning
  • Application of deep learning
  • How deep learning works
  • What is neuron
  • Introduction to perceptron
  • Neural network activation functions
  • Weights and bias
  • Types of activation functions
  • Single layer and multilayer perceptron
  • Training a perceptron
  • Parameters of perceptron
  • What is learning rate, epoch
  • Optimization algorithm
  • Introduction to tensorflow
  • Tensorflow syntax
  • Constants, Variable and placeholder
  • Introduction to Keras
  • Introduction to ANN
  • How it works
  • Layers in ANN
  • Concepts of back propagation
  • Example of image recognition using ANN
  • Understanding CNN
  • Why CNN
  • Convolution layer, filtering
  • ReLU and Pooling layer
  • Fully connected network
  • CNN use case
  • What is pre trained model
  • Advantage of pre trained model to speed up your CNN
  • Imagenet dataset
  • VGG 16, VGG 19 model
  • Train your model using VGG and compare accuracy
  • What is cloud computing
  • Cloud service model, IaaS, PaaS, SaaS
  • Concept of public cloud, private cloud
  • Cloud service provider, AWS
  • Create free account on AWS
  • Different services in AWS
  • AWS core services
  • AWS S3, Lambda
  • AWS EC2
  • Concepts of free and paid services in AWS
  • Introduction to Amazon SageMaker
  • Build , train , Deploy model on SageMaker
  • Amazon rekognition, a deep learning service in AWS
  • Image analysis on AWS rekognition

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