Artificial Intelligence Professional Program

Program Description

Taste of Training

Artificial Intelligence and Big Data are some of the most highly sought after skills in the High-Tech Industry. The demand for data scientists is increasing so quickly, that McKinsey predicts that in the near future, there will be a 50 percent gap in the supply of data scientists versus demand.

Our Artificial Intelligence Professional Program will enable you to gain the skills, experience and certification you need to be successful as an AI or Big Data Professional.  You will learn the best practices and methodologies of how to conduct leading edge Artificial Intelligence and Big Data Projects, and be mentored by some of the best experts in the field. This program is approved by the Knowledge and Human Development Authority (KHDA) of Dubai.

Dates Location Instructor's Office Hours Registration Fees
17 October - 07 November 2020 Dubai Knowledge Park Wednesdays: 6:00PM - 8:00PM 2,500 AED (680 USD)

What You Will Get

KHDA-Accredited Certification

Live Classes

Lecture Videos

Practical Projects

AI Professional Program Description
Course I - Python Programming Click Here for More Details
Course II - Python for Data Science and Machine Learning Click Here for More Details
Certification - Innosoft Certified AI Professional (AI-200) Exam Click Here for More Details

Course Instructor - Ahmed El Koutbia

Ahmed_Passport_Photo

Founder and CEO of Innosoft Gulf, a leading AI and Big Data Education Center in Dubai. Most of the work that I do at Innosoft Gulf involves teaching, consulting and research in Deep Learning, Machine learning and Big Data. In the last couple of years, I have trained hundreds of professionals in these areas.  To develop a local community of AI and Big Data professionals, I started in March 2017, one ofthe largest meet-up groups in Dubai: Innosoft Gulf – Big Data and Artificial Intelligence. At the moment, this active meet-up group has over 3,800 members.

After completing my Bachelor’s degree in Information and Decision Science at the University of Illinois at Chicago in 1996, I had the opportunity to work for some of the most prestigious organizations in the US including Sun Microsystems and Chicago Board of Options Exchange (CBOE).  At Sun, I worked closely with the Chief Architect of the Java Center in the architecture, design and development of a Java EE based workflow engine. This work was included in the best selling  book Java EE Patterns.  Currently, I am pursuing graduate studies in AI at Stanford University, where I worked recently on a self-driving project that uses Fully Convolutional Neural Networks for Automated Traffic Lane Detection (Click here to download the project report).

 

Course and Certification Schedule

Event Date Description Timing

Live Session 1

In-Person or Zoom Meeting
18 October 2020
  • Meet and Greet

  • Course Introduction

  • Python Fundamentals

  • Assignment 1
7:00PM - 8:30PM

Lecture Video 1

18 October 2020
  • Python Environment Setup

  • Data Types, Strings, Lists, Tuples
Self-Paced

Lecture Video 2

19 October 2020
  • Sets, Dictionaries

  • Selection Statements, Loops

  • File Input and Output

  • Functions, Python Modules

  • Object-Oriented Programming – Classes

Self-Paced

Assignment 1 Due

20 October 2020 at 6:00PM

Live Session 2

In-Person or Zoom Meeting
20 October 2020
  • Q & A: Lecture Videos 1 and 2

  • Assignment 1 Solution

  • Assignment 2
7:00PM - 8:30PM

Lecture Video 3

21 October 2020
  • Objected Oriented Programming (Code Reuse, Inheritance, Composition)

  • Data Analysis with Pandas

  • Data Analysis with Numpy
Self-Paced

Lecture Video 4

22 October 2020
  • Data Analysis with Numpy – Continued

  • Practical Data Analysis Project

Self-Paced

Assignment 2 Due

24 October 2020 at 6:00PM

Live Session 3

In-Person or Zoom Meeting
24 October 2020
  • Q & A: Lecture Videos 3 and 4

  • Assignment 2 Solution

  • Assignment 3
7:00PM - 8:30PM

Lecture Video 5

25 October 2020
  • Introduction to Machine Learning

  • Supervised, Unsupervised and Reinforcement Learning

  • Supervised Learning (Classification, Regression)

  • Linear Regression

  • Building a Predictive Model for a Real Estate Firm
Self-Paced

Lecture Video 6

26 October 2020
  • Data Preparation (Handling Missing Values and Categorical Features)

  • Building a Classification Model with Logistic Regression

  • Evaluating Classification Models (Accuracy, Precision, Recall, F1-Score)

  • Bias-Variance Tradeoff
Self-Paced

Assignment 3 Due

27 October 2020 at 6:00PM

Live Session 4

In-Person or Zoom Meeting
27 October 2020
  • Q & A: Lecture Videos 5 and 6

  • Assignment 3 Solution

  • Assignment 4
7:00PM - 8:30PM

Lecture Video 7

28 October 2020
  • Classification – K-Nearest Neighbors (KNN)

  • Tuning a KNN Model

  • Unsupervised Learning – K-Means Clustering

  • Data Visualization with Seaborn and Matplotlib
Self-Paced

Lecture Video 8

29 October 2020
  • Introduction to Deep Learning

  • Neural Network Representation

  • Forward Propagation

  • Activation Functions

  • Cost Functions

  • Back-Propagation with Gradient Descent

  • Solving an Image-Classification Problem with Deep Learning

Self-Paced

Assignment 4 Due

31 October 2020 at 6:00PM

Live Session 5

In-Person or Zoom Meeting
31 October 2020
  • Q & A: Lecture Videos 7 and 8

  • Assignment 4 Solution

  • AI-200 Certification Exam Prep
7:00PM - 8:30PM

AI-200 Certification Exam

7 November 2020

In-Class Exam


  • Dubai Knowledge Park, Block 6, Office F02


3:00PM - 5:00PM

Testimonials