Deep Learning & AI with Python


Become an expert in neural networks, and learn to implement them using the deep learning framework PyTorch. Build convolution networks for image recognition, recurrent networks for sequence generation, and generative adversarial networks for image generation, and learn how to deploy models accessible from a website.

Course Duration: 45 Hours

1. Course Overview

Deep learning is a key enabler of AI powered technologies being developed across the globe. In this deep learning course, you will learn an intuitive approach to building complex models that help machines solve real-world problems with human-like intelligence. The intuitive approaches will be translated into working code with practical problems and hands-on experience. You will learn how to build and derive insights from these models using Python Jupiter notebooks.

  • The components of a deep neural network and how they work together
  • The basic types of deep neural networks (MLP, CNN, RNN, LSTM) and the type of data each is designed for
  • A working knowledge of vocabulary, concepts, and algorithms used in deep learning
2. Course Prerequisites

This program has been created specifically for students who are interested in machine learning, AI, and/or deep learning, and who have a basic working knowledge of related fields.

  1. Python programming
  2. Data Analysis
  3. Good Knowledge of Mathematics fundamental.
  4. Aware with any cloud ( Optional )
3. Course Outline
  •  Introduction to deep learning and a quick recap of machine learning concepts.
  • Building a simple multi-class classification model using logistic regression
  •  Detecting digits in hand-written digit image, starting by a simple end-to-end model, to a deep neural network
  • Improving the hand-written digit recognition with convolutional network
  •  Building a model to forecast time data using a recurrent network
  • Build your own recurrent networks and long short-term memory networks with PyTorch
  • Learn to understand and implement a Deep Convolutional GAN (generative adversarial network) to generate realistic images, with Ian Goodfellow,
  • Train and deploy your own PyTorch sentiment analysis model. Deployment gives you the ability to use a trained model to analyse new, user input. Build a model, deploy it, and create a gateway for accessing it from a website.
4. Why Choose Highsky !

Highsky IT is the most trusted training partner for providing IT courses for eligible candidates. Our course offers high-end infrastructure and tech labs along with expert-designed course materials. Also, training and content have built-in project-based use cases for better understanding. Get 100% placement support right after completing your classes & live project training sessions. Contact us for more information on the course details!

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