• AstroLabs Dubai Deep Learning Bootcamp


In order to participate in this bootcamp, basic programming knowledge is required (in any programming language).

Deep Learning, Machine Learning, AI and Data Science are very hyped up topics that have been highly misunderstood.

In this 2 week intensive bootcamp, our goal is to dispell the myths of Deep Learning, and show you how to build real world applications. We won’t be covering any abstract concepts, it will be all coding and all practical.

This certificate granting bootcamp will focus on five main areas:

  1. In-Person Training on Core Topics
  2. Mentorship, and Office Hours sessions
  3. Remote Online Learning & Blended Learning With Follow Up
  4. Practical and Project Based With Real World Assignments
  5. Open Coding & Pair Programming Sessions At Coworking Space

This data deep learning bootcamp will take place at the AstroLabs Dubai Coworking Space

This program focuses on modern deep learning, data science and machine learning technologies used in the industry that include: Basics of Python, Data Science Coding Basics, Numpy Operations and Data Visualization, Deep Learning / Machine Learning / Artificial Intelligence Basics, Machine Learning Libraries, Using Keras Models, Convolutional Neural Network, Convnet training / plotting and architecture, Classification and Object Segmentation,Recurrent Neural Networks, Sequential Data, Architectures of RNN and more!

Learn more about the full program below.


AstroLabs Dubai Deep Learning Bootcamp Logistics

The AstroLabs Deep Learning Bootcamp will take place on weekday evenings (from 6:30-9pm), and Friday and Saturday (10am -4pm)  from February 22,2019 to March 2, 2019. You can view the entire schedule and what will be covered below.

  • Curriculum

    Module 1 Python for Data Science (2 Days)

    Python basics – Day 1

    This module will be a crash course in Python for those that are unfamiliar with the language. If you have experience in Python, it will serve as a short refresher.

    • Intro to interpreted languages
    • Hello world in python
    • Variables and data types
    • Functions
    • Control flow
    • List comprehension
    • Classes
    • Files

     Numpy and ND arrays – Day 2

    • Python Libraries
    • Array creation and representation
    • Indexing and slicing
    • Universal Functions
    • Reductions
    • Linear operations

    Data visualization in Python

    Module 2 Deep Learning (2 Days)

     Deep learning 101 – Day 3

    • Deep Learning, Machine Learning and Artificial Intelligence Programming Basics
    • Fundamentals of deep learning
    • Building neural network from scratch (how to program them)

     Creating Models in Keras – Day 4

    • Intro to Machine Learning libraries
    • Keras layers and models
    • Optimizers and loss functions
    • Training a Keras model

    Module 3 Deep Learning for Computer Vision  (5 Days)

    Introduction to Convolutional Neural Networks (ConvNets ) – Day 5

    • Real World uses of Convnet
    • What is convolution?
    • Convolution in image processing
      • Kernels
      • Stride
      • Padding
      • Pooling 

    Training a Convnet in Keras – Day 6

    • Building a convnet using keras
    • Training the convnet on MNIST dataset
    • Plotting the loss graph in matplotlib

    Convnet Architectures – Day 7

    • Concept
    • AlexNet
    • VGG
    • GoogleNet
    • Darknet
    • Resnet

    Common Application Algorithms with Convnet – Day 7 Continued

    • Classification
    • Object Detection
    • Object Segmentation
    • Example – Classification and detection using YOLO (darknet)

    Deep Learning for text and Sequences

    Understanding sequential data and the concept of Recurrent Neural Networks in the context of Sequential data – Day 8

    • What is Sequential data
    • What is RNN and why is it used?
      • Forward Propagation
      • Backprop through time

    Understand different architectures of RNN – Day 8 Continued

    • One – one
    • Many – Many
    • Many – one
    • One – Many
    • Bidirectional
    • Encoder – Decoder
    • LSTM
    • GRU
    • Attention model

    Learn to implement a RNN in keras  for different applications – Day 9

    • RNN for NLP 
    • Machine Translation
    • Sentiment Classification
    • Named Entity Recognition

Full Dubai Deep Learning Bootcamp Calendar

Friday February 22, 2019 10am-4pm -> Python Basics (Crash course in Python)
Saturday February 23, 2019 10am-4pm -> Numpy and ND arrays and Data Visualization in Python
Sunday February 24, 2019 6:30-9pm-> Deep learning, Machine Learning and Artificial Intelligence 101
Monday February 25, 2019 6:30-9pm-> Machine Learning Libraries and Keras
Tuesday February 26, 2019 6:30-9pm-> Deep Learning for Computer Vision, Introducton to Convolutional Neural Networks
Wednesday February 27, 2019 6:30-9pm-> Learn to Implement and train a ConvNet in Keras
Thursday February 28, 2019 6:30-9pm-> Implementing common application algorithms for Deep Learning
Friday March 1, 2019 10am-4pm -> Understand Recurrent Neural Networks in the context of Sequential data, Different architectures of RNN
Saturday March 2, 2019 10am-4pm -> Implement a RNN in keras for different applications, RNN for NLP (Machine Translation, Sentiment Classification, Named Entity Recognition) + Program wrap up


  • Current Students
  • Fresh Graduates
  • Unemployed
  • Paying out of pocket
  • Working At A Startup
  • Freelancers
  • Team Development
  • Corporate Employees
  • Group Discounts

*See Our Installment Plans

If you have any questions please contact: [email protected]

  • Instructors

    Fariz Rahman
    Deep Learning Engineer – Skymind Inc
    Skymind Inc develops enterprise quality machine learning frameworks, most notably deeplearning4j – the only production quality deep learning library available for the JVM. www.skymind.io

    Fariz is also a contributor to Keras the popular deep learning library. Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. Keras is the library of choice for thousands of researchers, academics, deep learning enthusiasts and companies ranging from startups to Microsoft and Google. To learn more about Keras,  www.keras.io,     www.github.com/keras-team

    He is also the founder of the Kerala AI Initiative a non-profit effort to turn Kerala into an AI hub – similar to Montreal.ai. www.keralaai.in as well as the Director & Data Scientist  – Minicog, Artifical Intelligence Consulting and Services  www.minicog.ai. Formerly Faraz worked as a Machine Learning Engineer at Datalog Inc,  An Artificial Intelligence company based in LA   www.Datalog.ai

    Mohammed Ibrahim
    Director & Engineer Robotics – Minicog, Artifical Intelligence Consulting, and Services  www.minicog.ai

    Former Robotics Engineer – Sastra Robotics,  a robotics company that makes industrial robotic manipulators. Sastra was noticed for winning TiE50 Award by TiE Silicon Valley in 2017.  www.sastrarobotics.com

  • Teaching Method

    The goal of this program is not to teach you what to do, but have you do it yourself! Each day in the program will have heavy hands-on work using the actual tools that developers use on a daily basis.

  • How Will This Bootcamp Benefit My Career?

    This bootcamp will benefit your career in 3 ways:

    1. You will learn the building blocks of Deep Learning, Data Science and Machine Learning, a very in-demand field.
    2. We will connect you with our network of recruiters, and companies to help land you a job!
    3. In addition to having you build up a portfolio of projects, as a KHDA accredited training institute, AstroLabs will grant a certificate on the completion of this bootcamp, which shows employers that you’re legit!
  • Are There Any Prerequisites or Minimum Requirements to Join?

    We will cover Python from scratch, so no previous knowledge is required. However, attendees must have a basic understanding of programming concepts (functions, loops, variables etc.), ideally with basic experience in at least one programming language (Python, JavaScript, Java, PHP, C etc.), since we won’t be spending too much time on the basics programming.

  • More Information

    Have any questions or need more information? Send us an email at [email protected]


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