Online course / Flexible schedule

Artificial INTELLIGENCE Certification.

From basic Python knowledge to complete understanding and implementation of Machine Learning algorithms.

The Artificial Intelligence Certification

This is a 16-week intensive training program designed to equip participants from the Middle East and North Africa (MENA) region with the necessary knowledge, tools, and know-how for market-ready skills. The program was carefully designed by our team with industry and academic expertise to ensure participants learn the foundational knowledge they need while engaging in real-world projects and challenges that help them attain the skills needed for today’s industry job roles.

The Artificial Intelligence Certification

Tools covered

Is the Certification Program for you?

A fresh graduate who wants to build a career in Machine learning.

An entrepreneur looking to launch a new tech venture that builds on AI solutions.

An enthusiast looking to transition into the Machine Learning field early on in your career, and you are wondering where to begin.

A working professional who wants to dive deeper into the world of Artificial Intelligence with the right tools and projects.

Our Partner Network

Interested in hiring our graduates?

3 Different Specializations
you will

Pick your track

A Machine Learning Engineer will put more focus on the modeling-related tasks: training, testing, comparing and fine-tuning models to deploy them into production at scale. Also, the Machine Learning Engineer will be responsible for monitoring these models once in production, and retraining them when necessary to make sure they are performing as expected.

Pick your track

A Data Scientist for instance will put more focus on the data-related tasks: extracting, cleaning, transforming, and visualizing data to derive valuable insights from it. Also, a Data Scientist can use this data to build predictive models for testing purposes.

Pick your track

A Data Engineer’s primary job is to prepare data for analytical or operational uses. They are typically responsible for building data pipelines to bring together information from different source systems. Data engineers often work as part of an analytics team alongside data scientists.

Machine Learning Track

Pick your track

Neural Networks & Deep Learning

You will learn about neural networks’ mathematical foundations and why neural networks have brought about great advancements to the field of Machine Learning. You will get introduced to deep learning libraries in Python and discover techniques for improving deep learning models’ performance.

Deep Learning in Advanced Data Types

You will learn about new deep learning architectures suitable for different data types. You will understand what makes these data types unique and why there is a need to make use of advanced deep learning designs. You will explore foundations of the Computer Vision, Natural Language Processing, and Time-series signals fields.

Machine Learning in Production

Now that your foundation is solid, you will explore machine learning in practice: what are the challenges commonly faced when these models are deployed in real-world and how to overcome them, what are some best practices to abide by, and what are tools that can help you scale to real-world implementations.

Data Science Track

Pick your track

Data Preprocessing

You will explore different types of data and what kind of operations can be performed on each in order to better extract useful information. You will also learn how to structure sequential data to conduct your analysis.

Neural Networks & Deep Learning

You will learn about Deep Learning and discover its great advancements. You will get introduced to deep learning libraries in Python and discover different Neural Network architectures that help you build deep learning solutions when dealing with different kinds of data.

Data Science Toolkit

You will learn how you can scrape data from the web using python libraries. You will get introduced to relational and non-relational databases for storing data, and finally, you will learn about some data transformations.

Data Science in Production

Now that your foundation is solid, you will explore data science in practice. You will revisit the data science lifecycle to know more about each of its steps in production. You will learn about the challenges that might occur and the best practices to overcome them, along with tools that help you scale to real-world implementations.

Data Storytelling

You will learn how to effectively communicate insights from your dataset using various types of visualizations. You will discover tools and techniques to create an engaging and informative story.

Detailed Curriculum

Machine Learning Specialization

Orientation & Prepwork (1 week)

During orientation week, you will get onboarded to the program. This week will focus on providing you with review material on preparatory material you need to be comfortable with before you begin your journey in the AI Certification.

Data Science Foundations (1 week)

You will discover the Data Science lifecycle and explore its different aspects in detail. You will also learn the basics of databases, the different data types you will encounter in your study, and different treatment methods for data.

Machine Learning Foundations (2 weeks)

You will focus on understanding what a machine learning algorithm is composed of, get introduced to the most popular algorithms and explore their mathematical formulations, and be able to select the best model to build and train on different real-world problems.

Statistical Model Validation & Testing (1 week)

You will discover common mistakes and mishaps in the evaluation of machine learning methods. You will learn different evaluation criteria as well as statistical methods that guarantee your model comparisons are accurate and statistically supported.

Career Development Week

You will discover the soft skills needed for a successful career such as communication, leadership and networking skills. You will also get the chance to receive advice from an HR expert on designing your CV and building your portfolio.

Neural Networks & Deep Learning (1 week)

Deep Learning in Advanced Data Types (2 weeks)

Machine Learning in Production (1 week)

Career Development Week

Research & Hot Topics (1 week)

You will develop the skills needed to conduct successful research in machine learning, from identifying top references to stay up to date with the latest advancements to contributing back to the research community with your own advancements. You will also get introduced to various foundational and hot research topics in the field.

Capstone Projects (3 weeks)

You will dedicate these three weeks to finalizing your capstone project solution with the support of guided, one-on-one mentorship from practitioners in the field. At the end, you will present your project solution to a panel who will assess your work as well as to recruiting firms working in the field of Machine Learning.

Data Science Specialization

Orientation & Prepwork

Data Science Foundations ( 1 week)

Machine Learning Foundations (2 weeks)

Statistical Model Validation & Testing (1 week)

You will discover common mistakes and mishaps in evaluation of machine learning methods. You will learn different evaluation criteria as well as statistical methods that guarantee your model comparisons are accurate and statistically supported.

Career Development Week

You will discover the soft skills needed for a successful career such as communication, leadership and networking. You will also get the chance to receive advice from an HR expert on designing your CV and building your portfolio.

Advanced Data Types (1 week)

Neural Networks & Deep Learning (1 week)

Data Science Toolkit (1 week)

Data Science in Production (1 week)

Data Storytelling (1 week)

You will learn how to effectively communicate insights from your dataset using various types of visualizations. You will discover tools and techniques to create an engaging and informative story.

Career Development Week

Research & Hot Topics

Capstone Projects (4 weeks)

Data Engineering Specialization

Orientation & Prepwork (1 week)

Data Engineering Lifecycle (1 week)

You will discover the Data Lifecycle and get familiar with Data Engineering related terminologies. You will also see the big picture of the process and get introduced to Big Data architectures and platforms.

Career Development Week

Data Ingestion Methods (1 week)

You will learn the common data stacks and get introduced to some tools for each part of the pipeline. You will also explore each step of the process starting from extracting data from different sources, passing through data transformation, and ending with the different options for loading data. At the end of this week, you will combine all of the previous steps to build a full pipeline.

Data Storage and Retrieval ( 1 week)

You will learn the different data models and the basic databases (SQL and NoSQL). You will also get familiar with data warehouses, data lakes and data marts. Finally, you will learn how to retrieve data from the multiple storage options according to your use case.

Data Processing and Analytics (1 week)

You will learn about batch and real time data processing. You will also dive into data analytics where you will investigate OLTP and OLAP systems, and finally you will learn about data visualization techniques to communicate your findings.

Exploring Big Data (1 week)

You will learn about big data processing frameworks and focus on Apache Spark. Then, you will learn how to use Kafka to produce/ consume data. In addition, you will go through streaming data sources with Apache Flink and Hive.

Data Engineering on Cloud (1 week)

In this week, you will dive into collecting, storing, processing, analyzing, and visualizing data using various services from different cloud providers. You will also explore serverless computing and pipeline automation on the cloud.

Career Development Week

Capstone Projects (3 weeks)

Career Fair Access

You will engage directly with recruiting firms in the Middle East and North African region looking to hire talent in the fields of Data Science, Machine Learning, and Data Engineering. As part of the Career Fair, you will also get access to exclusive career training workshops that will help you better prepare your work portfolio (resume, LinkedIn, etc.) and your interviewing skills for Data Science and Machine Learning roles.

Alumni

Get Inspired and find your own path!

Whether you are a student, entrepreneur, freelancer, or career shifter, with the right certification, you can reach your goals in Artificial Intelligence.

Mohammad Srouji

Here’s how Mohamad was able to use the knowledge he acquired to develop his start-up

Watch this video

Jana Kabrit

Just like Jana start your journey in AI from zero!

Watch this video

Ali Wehbe

From Control Engineering to a Master degree in AI!

Watch this video

Get Certified

Enrollment Process

APPLY

Complete your program application by taking a technical assessment

INTERVIEW

Go through a general interview to make sure that the program is the right fit for you

ACCEPTANCE

Receive an official acceptance for enrollment

How does the Certification Program Prepare you for the job market?

Master fundamental concepts and the language of Data Science and Machine Learning
Learn how to best represent yourself to recruiters in the Machine Learning space
Work in a team to solve a real-world, research-oriented challenge
Gain the skills to become a sufficient self-learner and investigator in the field of Machine Learning
Learn the best practices for Machine Learning in development and in research settings
Be guided by AI instructors and engineers to learn from real-life practitioners
Gain the soft skills to become a full-stack fit in a diverse Data Science team in the job market

Fees