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Prerequisites:

  • While the deep learning concepts will be taught in an intuitive way, some prior knowledge of linear algebra and calculus would be helpful.
  • participants should be comfortable with programming. Familiarity with python data stack is ideal.
  • Our Deep Learning Bootcamp is tailored for professionals working in technology development with an engineering background and a basic understanding of logic and mathematical reasoning.
  • Prior knowledge of machine learning will be helpful. Participants should have some practice with basic machine learning problems e.g. regression, classification.
  • Participants are required to possess a basic knowledge of Python since all
  • assignments/projects will be done using the Python programming language.

 

Training Program Description:

    • The objective of these six days Bootcamp is to ensure that the participants have enough theory and practical concepts of building a deep learning solution in the space of computer vision and natural language processing. Post the Bootcamp, all the participants would be familiar with the following key concepts and would be able to apply them to a problem.
    • You will learn and implement an end-to-end deep learning model for computer vision (image recognition) and natural language processing (text classification). This is predominantly a hands-on course and will be 90% programming/coding and 10% theory

 

  • Audience and Requirements
    • Anybody who can write some code in whatever programming language should be able to follow the Bootcamp. We make use of an iPython/Jupyter Notebook, so nothing but a laptop is required to participate.
      We will be using Python data stack for the workshop with Keras for the deep learning component. Please install Ananconda for Python 3 for the workshop. Additional requirements will be communicated to participants.
    • The course is suitable for a range of positions including:
      • A machine learning practitioner
      • A programmer interested in building data science products
      • Anyone (researcher, student, professional) learning deep learning
      • Corporates and start-ups looking to add DL to their product or service offerings
      • Hardware: Bring Your Own Laptop and charger, leave with the knowledge
    • Important note: Each Bootcamp participant is required to bring their own laptop running Windows 10. Although this workshop requires Windows 10, the skills learned, and code used will be transferrable to Mac OS and other platforms because all software used will be open source.
    • Assistants will also be on hand to help attendees with hardware/software issues.
    • Attendees receive an electronic copy of the course materials and related code at the conclusion of the Bootcamp.

 

Projects

    • This program is comprised of many career-oriented projects. Each project you build will be an opportunity to demonstrate what you've 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 data analysis and feature engineering, machine 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've acquired and to demonstrate your newfound abilities to future employers or colleagues. Throughout this program, you'll 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’ve acquired and to demonstrate your newfound abilities to future employers. Throughout this program, you’ll have the opportunity to prove your skills by building the Projects During the Program

 

Benefits:

  • Understand AI's unique challenges and opportunities
  • Gain practical and strategic comprehension of AI
  • Explore Deep Learning, RL, CV, And NLP techniques and applications
  • Building a deep learning solution
  • Learn how to develop AI systems with Python programming
  • Solve real AI problems through hands-on projects
  • Develop creativity and engagement skills through storytelling and empathy exercises
  • Receive a Certificate of Completion from Epsilon AI Institute, Delaware, USA

10% Theory, 90% Practice

Program Duration: 6 Days

Program Language: English / Arabic

Location: Online Virtual Classroom Live (Zoom Platform) / Offline classroom Live (EPSILON AI INSTITUTE | Nasr City)

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

DAY 1

  • Introduction to Neural Networks & Deep Learning
  • Implementing Gradient Descent
  • Training Neural Networks
  • Introduction to TensorFlow
  • Neural Network Hands-on Project

 

DAY 2

  • Introduction to Deep learning
  • Deep Learning with Keras
  • Intro to Artificial Neural Networks – ANN
  • Intro to Convolutional Neural Networks – CNN
  • Intro to Recurrent Neural Network – RNN
  • MNIST Handwritten Digit Classification Dataset Project

 

DAY 3

  • Intro to Classic Computer Vision with OpenCV
  • Classical Machine Learning
  • Deep Learning with CNN
  • CNN Architectures
  • Transfer Learning
  • Object Detection with YOLO
  • GANs & DCGAN
  • Hot dog or Not Hot dog Project

 

DAY 4

  • Introduction to NLP
  • Introduction to Spacy toolkit
  • Challenges with traditional NLP techniques
  • Concept of Sparse vs. Dense Embedding
  • Word embeddings
  • Long Short Term Memory (LSTM) Model
  • Build an NLP model using word embedding (for text
    classification)

 

DAY 5

  • Introduction to Reinforcement Learning
  • Applications of RL
  • Policy
  • Exploration and Exploitation
  • Design Reward Function
  • Discounted Reward Factor
  • Q-Learning Algorithm
  • Introduction to Deep RL (DQN)
  • Project: Cart Pole with Keras-RL

 

DAY 6

  • More Practice – Projects
  • Questions

 

 

Download Deep Learning BOOTCAMP Brochure PDF

 

 

Course Curriculum

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