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Data Engineering
Data Engineering Fundamentals

In the age of big data and data-driven AI, many companies start to realize the importance of establishing data engineering best practices. As a result, the demand for data engineering has been growing rapidly. Currently there is a huge supply and demand mismatch in the talent market. One reason for the imbalance is that modern data engineering requires new tools/skills and traditional learning environments such as universities, colleges, and bootcamps don’t keep up with the trends. Another reason is that data engineering is hard to teach! Curriculums need to be extremely hands-on, and it requires very seasoned instructors who work in the fields to teach in the most practical way.

Interested in becoming a data engineer? Want to acquire the essential DE skills and build portfolio projects? Fill out the form to download syllabus or talk to our program advisor directly.

At a Glance
Intermediate
What you will learn

In this 12-week part-time course you will learn how to code like a data engineer and build up the foundation skills for a data engineering. The core skills covered in this course include: python and scala programming, bash/shell scripting, docker and kubernetes, cloud computing (AWS, GCP), as well as apache spark.

You will put these tools to use by implementing a capstone big data project and learn how to build big data pipelines with the guidance from our expert instructors who specialize in these areas

Summary
Spark, Kubernetes, Airflow, AWS, GCP
Learn to think like a data engineer
Learn and practice through projects
Weekly Leetcode practice and solution sharing

Part-time

Online Live

12 weeks

Register

About the Program

Data engineers are usually harder to train and source because the program needs to be very practical/hands-on and there is not much theory to teach. The open-source communities are also pushing out new tools and platforms on a regular basis which makes teaching data engineering challenging because materials need to be updated rapidly to keep up with the latest trends. At WeCloudData, we have heard from many hiring managers and recruiting agencies say that while the demand for data engineers is great, data engineer talents are even harder to find compared to data scientists.

The Data Engineering Fundamentals course is a 12-week part-time course that trains IT professionals, data scientists, and developers who want to up-skill themselves to get into the data engineering field. This is an intensive and hands-on course that requires a lot of programming, scripting, and project implementation. You will learn Linux, Docker, Scala & Functional Programming, Apache Spark and build an end-to-end data pipeline in the AWS cloud.

for those who want to
  • Data Engineers from traditional ETL background who want to acquire modern DE skills
  • Developers and Software Engineers who are interested in building data applications
  • IT Professionals who want to explore new paths
  • Data Scientists who want to switch to the engineering world

Speak to our advisor

Our Program Advisor can answer all your questions and help you pick a program that best suits your need. Please fill in your information below and we will contact you.

You can also contact us at info@weclouddata.com or (647) 588-4206

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What you will learn

  • Learn Containerization Essentials
    Data Engineers need to be very familiar with Linux and Docker containers. This module teaches students commonly used Linux commands and how to pull, run, and build your own containers. The instructor will also cover Kubernetes basics in an AWS environment.
    • Get your way around in a Linux development like a pro
    • Dockerize your application and start delivering microservices
    • Dive into the details of Docker, create image, Dockerhub, Docker network and more
    • Learn how to orchestrate containers on Kubernetes
  • Lay the Functional Programming Foundation for Apache Spark
    Scala programming language can be found in use at some of the best tech companies like LinkedIn, Twitter, and FourSquare. Scala’s performance has ignited interest amongst several financial institutions to use it for derivative pricing in EDF Trading. The biggest names in the digital economy that are investing in Scala programming for big data processing are - Kafka created by LinkedIn and Scalding created by Twitter. With powerful monoids, combinators, pattern matching features, provision to create DSL’s and more -Scala as a tool for big data processing on Apache Spark is definitely a certainty.
    • Process big data with Apache Spark
      • Setup your own Hadoop environment in Docker-Compose
      • Build Spark applications in AWS EMR and Databricks
      • Processing large datasets with Spark DataFrame
      • Spark performance tuning like a pro
    • Learn how to develop data pipelines
      Real-world data engineering is never textbook-like. Data operators have complex dependencies. A data engineer will need to build robust data pipelines that handle dependency DAGs, data quality checks, scheduling, backfilling, error checking, etc. This module helps students connect the dots by implementing a cloud-based data processing pipeline using Apache Airflow.
      • Understand data lineage and pipelines in enterprises
      • Workflow management using Apache Airflow
      • Automate data pipelines for data processing
    • Build pipelines, break them, and optimize them
      Students will need to complete an end-to-end data pipeline in the cloud using AWS, Docker, Airflow, and Apache Spark. The instructor will give expert suggestion and guidance on how to engineer pipelines in the most efficient way and help you build real experience faster.

      Resources

      Watch our recorded webinar and learn more about Data Science career and industry insights.
      Data Engineering Program Info Session
      Data Engineer Career Panel Discussion
      Meet Your TA: Zheng Xu
      Meet Your TA: David Tian

      Instructors & Guest Speakers

      Edwin Guo
      Big Data Specialist @ CPPIB
      Edwin is an expert Data Engineer and Cloud Architect who is specialized in Distributed Computing, Distributed Storage, Microservice, Cloud(AWS), Machine learning and Blockchain technologies. Skilled in Spark, Apache Kafka, Akka, Cassandra and various popular tools in the open-source landscape, he has had the opportunity to lead many challenging big data projects in the past. Coming from a Software Engineer background with a strong passion for the CS space, Edwin Guo is well versed in productive languages such as Scala, Java, Clojure, Python, and Golang. His past experience covers many domains including telecommunications, stock market price dissemination/portfolio management system, customer loyalty programs, and cybersecurity.
      Preetika Bhateja
      Data Engineer & Cloud Architect @Google | Data Engineering Instructor @WeCloudData
      Preetika works as a data engineer and cloud architect for Google in the Toronto office. Before Google, she worked in AdTech and banking industries in the data space. In her spare time, she Iikes to geek on anything about data, policy, and politics. She’s passionate about teaching and looks forward to working with students in this program.
      WeCloudData Data Engineer Bootcamp Assistant Instructor Zheng Xu
      Zheng Xu
      Data Engineer, The Globe and Mail
      Zheng is currently a data engineer at one of the largest Canadian newspaper company where he builds and supports the data application from other teams in the company. He specializes in building data pipelines using Apache Airflow, data integration and ETL/ELT in Snowflake/Redshift, and developing big data applications using Apache Spark on Databricks. He teaches with WeCloudData in the Data Engineering program as an assistant instructor. Topics he covers include Airflow, Cassandra, Spark, and Spark Streaming.
      Bhargavi Singh
      Senior Data Analyst, Marketing Science @ Critical Mass
      Online Learning Platform

      Learn anywhere, anytime

      Track your learning journey
      Watch lecture recordings, work on coding challenges, ask for TA help, and get resume and job support. The learning portal allows you to track your entire learning journey with ease.
      Sharpen your coding skills
      Leverage our online coding tool to test your knowledge, identify your weaknesses, and improve your Python and SQL coding skills. The LeetCode style live coding challenges will help you get prepared for technical job interviews.

      DATA ENGINEERING CAPSTONE PROJECT

      Build portfolio projects that impress hiring managers
      Learn how to build end-to-end data engineering pipelines and showcase that to hiring managers. Your resume will shine with the projects you work on in this course.
      What you will work on
      • Build an end-to-end data pipeline on AWS/GCP
      • Automate the workflow using Apache airflow
      • Transform data in real-time using Serverless
      • Process big data using Apache Spark on EMR
      • Containerize data pipelines and run data infrastructure on Kubernetes
      STUDENT PROJECT DEMO
      WeCloudData Data Engineer Student Project Demo 8

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      Related Blog Posts

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      Toronto Institute of Data Science and Technology, WeCloudData, Launches New Data Engineering Diploma Program
      It has FINALLY arrived! Our long awaited Data Engineering diploma program has launched at last. As the leading institute…
      by WeCloudData
      January 26, 2021
      Student Blog
      An Introduction To Spark and Its Behavior.
      The blog is posted by WeCloudData’s Big Data course student Abhilash Mohapatra. Checklist Followed: Mapreduce, Hadoop and Spark. Spark…
      by Student WeCloudData
      October 7, 2020

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