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Data Engineering Specialization

Build a strong foundation in Data Engineering for exciting career opportunities.
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Benefits of becoming
part of our community

Embark on a transformative educational journey alongside like-minded individuals through our innovative online, part-time programs designed to elevate your learning experience.

Flexible Learning

Our programs offer a combination of self-paced coursework and live sessions with industry professionals to clarify concepts and enhance your understanding.

Convenient Schedule

Enjoy the flexibility of our part-time, online program to fit your busy life and commitments.

Instructor-Led Cohort

Join a cohort led by expert instructors who provide guidance, support, and valuable insights throughout your learning experience.

Hands-On Projects

Engage in practical capstone projects, either self-designed or in collaboration with industry partners, to showcase your skills.

Collaborative Cohort

Stay motivated and inspired by the support of your cohort peers and our dedicated team throughout your learning journey.

Career Support

Access exclusive career services, including career fair, interviews, projects, and sourcing opportunities, to accelerate your career growth.

PROGRAM SCHEDULE

1 Week

Introduction to Data Engineering

Skills Gained

  • Data structures
  • Methods for Data storage
  • Data Pipelines definition
  • DE general architecture
  • Big Data definition
  • Distributed systems

Learning Outcomes

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”.

1 Week

Programming skills for Data Engineers

Skills Gained

  • Dealing with files/dataframes in Python
  • Get familiar with OOP with Python
  • Linux as an operating system
  • Shell scripting with Linux
  • Deploying containers using Docker
  • Docker main commands

Learning Outcomes

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 .

1 Week

Introduction to Databases

Skills Gained

  • Data relationships and data architectures
  • Normalization and denormalization for SQL databases
  • Writing Python scripts to access databases
  • NoSQL database categories

Learning Outcomes

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.

1 Week

Data Pipelines: Extract, Transform, & Load

Skills Gained

  • Extract data from different sources
  • Data parsing, filtering, and validation
  • Loading data in filing systems, databases, cloud, and data lakes.
  • Building ETL pipelines scripts

Learning Outcomes

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.

1 Week

Data Warehousing & Pipeline Automation

Skills Gained

  • Data Warehouses Architecting
  • Star and Snowflake schemas for data modeling
  • OLTP vs. OLAP data operations
  • Automating ETL scripts with Linux shell scripting
  • Data pipelines automation and orchestration with Apache Airflow.

Learning Outcomes

This week, 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.

1 Week

Big data: Hadoop & Spark ecosystem

Skills Gained

  • Distributed systems for storage and processing of data
  • Hadoop Cluster Architecture and User Web Interface
  • HDFS for big data storage
  • Spark for processing big data

Learning Outcomes

Now we will start diving into Hadoop platform and the main components of it. 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 pipelines.

1 Week

Data Warehouses in Hadoop ecosystem

Skills Gained

  • Understanding Apache Hive as data warehouse
  • Grasp the concept of querying engines
  • Basics of Machine Learning with Spark MLlib

Learning Outcomes

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, in addition to the concept of querying engines. At the end, you will learn about the basics of Machine Learning, and how data engineers can leverage that with SparkML.

1 Week

Big Data Streaming & Automation

Skills Gained

  • Apache Kafka for messaging systems
  • Apache Flink for streaming data
  • Apache Sqoop for databases migration
  • Preparing data in warehouses for BI engineers

Learning Outcomes

This week, you will learn about new integrated tools within the Hadoop ecosystem, starting with dealing with messaging systems with Apache Kafka, and how to use Kafka to produce/ consume data. Then you will go through streaming data sources with Apache Flink. In addition, you will get exposed to the migration of relational data into your data warehouse, and other tools to include such as Apache Oozie/ Airflow used to automate and orchestrate data pipelines. At the end of this week, you will be able to understand the relationships between data and business intelligence engineers.

1 Week

Data Engineering on AWS

Skills Gained

  • Accessing AWS through the Console vs. CLI
  • AWS Kinesis for data collection and streaming
  • AWS S3 for cloud Data Lake
  • Accessing S3 from CLI and programmatically

Learning Outcomes

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.

1 Week

Data Engineering on Azure

Skills Gained

  • Azure Data Factory as a data ingestion tool
  • Relational and non-relational data services in Azure
  • Data Processing and Analysis on Azure using Databricks, Synapse Analytics, HDInsight, and much more.
  • Power BI for dashboards.

Learning Outcomes

After exploring how to collect and store data in the cloud, you will learn how to process it, analyze it, and use Azure tools to create visuals.

OUR ALUMNI

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Wissam Moussa

Changing career and becoming a Machine Learning Engineer in 16 weeks
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Fatima Ksayrawi

From 0 knowledge in Machine Learning to a Machine Learning Engineer
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Hassan Kanaan

From Software Engineering to Machine Learning Engineer

ENROLLMENT PROCESS

01

APPLY

Complete you program application by taking a technical assessment

02

INTERVIEW

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

03

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 Engineering
  • Learn how to best represent yourself to recruiters in the Data Engineering 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 Data Engineering
  • Learn the best practices for Data Engineering 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 Engineering team in the job market

PRICE

PER PERSON

$2,967

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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