Artificial INTELLIGENCE Certification.
The Artificial Intelligence Certification
The Artificial Intelligence Certification
Tools covered
Is the Certification Program for you?
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
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.
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.
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.
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
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.
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.
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.
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.
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.
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
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
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
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
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 skills. You will also get the chance to receive advice from an HR expert on designing your CV and building your portfolio.
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.
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.
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.
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.
Research & Hot Topics
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
You will dedicate these three weeks to finalizing your capstone project solution with the support of guided, one-on-one mentor-ship 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.
Career Fair
You will present your capstone projects and 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.
Data Science Specialization
Orientation & Prepwork
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
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
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
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
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.
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.
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.
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.
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
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.
Research & Hot Topics
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
You will dedicate these three weeks to finalizing your capstone project solution with the support of guided, one-on-one mentor-ship 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 Data Science.
Career Fair
You will present your capstone projects and 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.
Data Engineering Specialization
Orientation & Prepwork
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.
Introduction to Data Engineering
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 and what defines data to be “big”.
Programming Skills for Data Engineering
You will hone your skills in Python by understanding its basics and how data engineers use it to extract, transform, and load data. You will also learn how to deal with Linux environments, and run shell scripts in Linux. And for application’s fast deployment, you will learn how to use Docker to run different tools and applications .
Introduction to Databases
You will learn the different data models and the basics of SQL and NoSQL Databases. You will get familiar with common database management systems and build client sessions to access databases programmatically with Python.
Data Pipelines: Extract, Transform, & Load
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 Warehousing & Pipeline Automation
You will learn how to construct Data Warehouses, query data and create views in them. However, now that you have become familiar with the big picture of data engineering and data warehousing, and you know how to build data pipelines, you will learn how to automate, and orchestrate its execution.
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.
Big Data: Hadoop & Spark Ecosystem
You will understand how to deal with Hadoop storage and processing tools, like HDFS and Spark. We will also dive deeper into Spark and how to program it with Python programming language to start building big data
Big Data Streaming and Automation
ou will learn about other integrated tools within Hadoop ecosystem, starting with dealing with streaming data sources with Apache Kafka, and how to use Kafka to produce/ consume data. Also, you will learn how to migrate relational data into your data warehouse using Apache Sqoop. Another tools Apache Oozie/ Airflow will be used to automate and orchestrate data pipelines.
Data Warehouses in Hadoop Ecosystem
You will learn how to deal with big data warehouses and how to set up Apache Hive on a Hadoop cluster. You will dive deep into how to load data into Hive from local file systems and HDFS programmatically. At the end of this week, you will be able to understand the relationships between data and business intelligence engineers.
Big Data Collection & Storage in Cloud
Beside working with data on-premises, you will dive into collecting and storing data in the cloud. This week, you will explore different services offered by cloud providers such as AWS for big data processing.
Big Data Processing & Analysis in Cloud
After exploring how to collect and store data in the cloud, you will learn how to process it, analyze it, and use AWS tools to create visuals.
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.
Capstone Projects
You will dedicate these three weeks to finalizing your capstone project solution with the support of guided, one-on-one mentor-ship 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 Data Engineering.
Career Fair
You will present your capstone projects and 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
Mohammad Srouji
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
$2,967/ person
Different financing options available
- Recorded sessions including lectures and coding labs
- Live instructor-led online workshops
- Learn from others: invited online talks & discussions
- Weekly office hours & round-the-clock advising
- Group capstone project with guided mentorship
- Career development workshops & mentorship
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