Artificial Intelligence Professional Program

Program Description

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 accredited by the Knowledge and Human Development Authority (KHDA) of Dubai.

Dates Delivery Method Duration Registration Fees
13 February - 6 March 2021
  • Live Online Sessions

  • Lecture Videos

  • Practical Projects
  • 16 hours of Lecture Videos

  • 4 Live Online Sessions

  • 2 Hours Certification Exam

750 USD

What You Will Get

KHDA-Accredited Certification

Live Online Sessions

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


Founder and CEO of Innosoft Gulf, a leading AI and Big Data Education Center in Dubai. Most of the work that Ahmed does at Innosoft Gulf involves teaching, consulting and research in Deep Learning, Machine learning and Big Data. In the last couple of years,  he has trained hundreds of professionals in these areas.  To develop a local community of AI and Big Data professionals  in March 2017 he started one of the largest meet-up groups in Dubai: Innosoft Gulf – Big Data and Artificial Intelligence. At the moment, this active meet-up group has nearly 4,000 members.

After completing his Bachelor’s degree in Information and Decision Science at the University of Illinois at Chicago in 1996, he 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, Ahmed 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, he is pursuing graduate studies in AI at Stanford University, where he 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 Duration

Live Session

In-Person & Online
Week 1
  • Meet and Greet

  • Program Orientation and Logistics
3:00PM - 4:30PM

Lecture 1

Week 1
  • Python Environment Setup

  • Data Types, Strings, Lists, Tuples
1h30 min

Lecture 2

Week 1
  • Sets, Dictionaries

  • Selection Statements, Loops

  • File Input and Output

  • Functions, Python Modules

  • Object-Oriented Programming – Classes

1h30 min

Lecture 3

Week 1
  • Objected Oriented Programming (Code Reuse, Inheritance, Composition)

  • Data Analysis with Pandas

  • Data Analysis with Numpy
2 hours

Lecture 4

Week 1
  • Data Analysis with Numpy – Continued

  • Practical Data Analysis Project

2 hours

Live Session

In-Person & Online
Week 1
  • Python Programming Review

  • Python Programming Project

  • Q & A

3:00PM - 4:30PM

Lecture 5

  • Introduction to Machine Learning

  • Supervised, Unsupervised and Reinforcement Learning

  • Supervised Learning (Classification, Regression)

  • Linear Regression

  • Building a Predictive Model for a Real Estate Firm
2 hours

Lecture 6

Week 2
  • 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
2 hours

Live Session

In-Person & Online
Week 2
  • Machine Learning Review

  • Hands-On Machine Learning Project

  • Q & A

3:00PM - 4:30PM

Lecture 7

Week 2
  • Classification – K-Nearest Neighbors (KNN)

  • Tuning a KNN Model

  • Unsupervised Learning – K-Means Clustering

  • Data Visualization with Seaborn and Matplotlib
2 hours

Lecture 8

Week 2
  • 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

2 hours

Live Session

In-Person & Online
Week 2
  • AI-200 Certification Exam Review
3:00PM - 4:30PM

AI-200 Certification Exam

Week 2

  • Online Exam with Oral Interview follow up

3:00PM - 5:00PM