Deep learning is driving advances in artificial intelligence that are changing our world. To join this field, start by learning Python fundamentals and neural networks, move on to core machine learning concepts, and then apply deep neural networks to challenges like image classification and generation, time-series prediction, and model deployment.

Prerequisites:

• Certified Data Scientist Professional – CDSP

Training Program Description:

• Deep learning is driving advances in artificial intelligence that are changing our world. Enroll now to build and apply your own deep neural networks to challenges like image classification and generation, time-series prediction, and model deployment.
• you'll master fundamentals that will enable you to go further in the field, launch or advance a career, and join the next generation of deep learning talent that will help define a beneficial, new, AI-powered future for our world. You will study cutting-edge topics such as Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, and Network Deployment, and build projects in Kera's and NumPy

• In this Program, you practice with real-life examples of Deep learning and see how it affects society in ways you may not have guessed!

• Throughout this program, you will practice your Deep Learning skills through a series of hands-on labs, assignments, and projects inspired by real-world problems and data sets from the industry. You will also complete the program by preparing a Deep learning capstone project that will showcase your applied skills to prospective employers.

What you will learn

• Identify the deep learning algorithms which are more appropriate for various types of learning tasks in various domains.
• Implement Neural Networks from scratch
• using frameworks like Kera's.
• Build convolutional networks, recurrent networks, and generative adversarial networks
• Implement deep learning algorithms and solve real-world problems

Projects

• This program is comprised of many career-oriented projects. Each project you build will be an opportunity to demonstrate what you have learned in the lessons. Your completed projects will become part of a career portfolio that will demonstrate to potential employers that you have skills in Deep learning algorithms, and training and evaluating models.
• One of our main goals at EAII is to help you create a job-ready portfolio of completed projects. Building a project is one of the best ways to test the skills you have acquired and to demonstrate your newfound abilities to future employers or colleagues. Throughout this program, you will have the opportunity to prove your skills by building the following projects
• Building a project is one of the best ways both to test the skills you have acquired and to demonstrate your newfound abilities to future employers. Throughout this program, you will have the opportunity to prove your skills by building the following projects:
• Project 1:  Age Prediction
• Project 2:  Cancer Detection
• Project 3:  Cat or Dog
• Project 4:  Sentiment Analysis
• Project 5:  Stock Market Prediction
• Capstone Project

Program Duration: 5 Weeks

Program Language: English / Arabic

Location: EPSILON AI INSTITUTE | Head Office

Participants will be granted a completion certificate from Epsilon AI Institute, USA if they attend a minimum of 80 percent of the direct contact hours of the Program and after fulfilling program requirements (passing both Final Exam and Project to obtain the Certificate)

CURRICULUM

1.Artificial Neural Networks

• Introduction to Neural Networks
• Deep Neural Networks
• Gradient Descent
• Activation Functions
• Weight Initialization
• Training Neural Networks (Backpropagation)
• Regularization and Dropout
• Stochastic & Batch & Mini-Batch Gradient Descent
• Momentum & Rmsprop And Adam
• Batch Normalization
• Regression with Deep Learning
• Binary and Multi Classification with DeepLearning
• Deep Learning with Tensorflow And Keras
• GPU And Google Colab
• Project #1 (Age Prediction)
• Project #2 (Cancer Detection)

2.Convolutional Neural Networks

• Convolution and Pooling Layers
• Data Augmentation
• Project #3 (Cat or Dog)

3.Recurrent Neural Networks

• Convolution and Pooling Layers
• What is RNN
• LSTM & GRU
• Embedding & Word2Vec
• Project #4 (Sentiment Analysis)
• Project #5 (Stock Market Prediction)

4.CAPSTONE PROJECT

Download Certified Deep Learning Specialist Brochure PDF