Erkan Şirin

Senior Data/ML Engineer, AWS Solution Architect

Erkan Şirin profil fotoğrafı

Application Status

AWS Cloud Data Engineering

Two different trends have emerged in recent years.

First; cloud usage has been increasing worldwide due to its many different advantages. In the cloud market, Amazon Web Services (AWS), the first and pioneer of cloud service providers, is still the market leader by far.

The second; is the continuous increase in the amount and importance of data. Here, too, the role of Data Engineer has great responsibilities and is therefore in high demand. Now, the industry is well aware that without a well-functioning data engineering infrastructure healthy ML/AI/BI/Analysis products are impossible.

Considering these two important trends, we have prepared incredible content for you to learn about the most popular profession in the data world on the world’s number one cloud. We are thrilled to have you embark on the AWS Cloud Data Engineering journey with us.

So what does a data engineer do? A data engineer designs and builds systems that collect, transform, and appropriately deliver data that business units or customers need.

Summary

As a data engineer candidate, you are at the right place if you want to build and serve something useful, see that the data coming out of the data pipelines you have designed and installed is consumed by internal or external customers, and enjoy it. Because AWS Cloud Data Engineering Bootcamp is designed for you to acquire the most demanded skills with up-to-date content prepared by an instructor with extensive industry experience in Turkey, Europe, and America.

This course will help you to get AWS Certified Data Analytics – Specialty Certification which is highly recognized by employers.

The Cloud Data Engineering course consists of 3 stages;

1. Preparation: Starts 4 weeks before the live training, 2 weeks

At this stage, training that will facilitate the understanding of online lessons is taken through videos with the support and guidance of mentors and trainers. For example, if docker-compose or SQL join will be used in the live lesson, it is also aimed not to waste time on what they mean.

2. Live Lessons: 8 July – 27 August 2023 (Cloud Data Ops-1), 8 weeks.

It is the main part of the training and continues over online platforms (Zoom) with the curriculum titled “Program content – curriculum” below, with 3 hours x 2 days of online lessons a week + 1.5 hours of homework control / additional lessons.

3. Graduation Project: 7 September 2023 2 weeks.

It is the stage where the trainees complete their graduation projects after the online lessons are over and presents them via Zoom. At this stage, individual/group work is done. Mentor and trainer support are available.

In this course, we will find answers to the following questions.

  • What’s in the world of data engineering? How do we become good data engineers?
  • What are file formats and compression algorithms? Where and how do we use which one?
  • How do we execute distributed queries over many different data sources?
  • How do we prepare our own PC to run on AWS?
  • How do we create an AWS EC2 virtual machine? How do we set the security settings?
  • How do we write data to AWS S3 with Python? How do we read?
  • What can we do as data engineers on AWS? What are the example use cases?
  • How do we query datasets on S3 with Athena?
  • How to set up Amazon EMR Cluster? How to run the Spark applications on EMR?
  • What services are available for streaming apps? How do we use it?
  • How do we do data visualization?
  • How do we clean and transform data with AWS Lambda?
  • How about creating EC2, creating an Autoscaling group, and running an application behind Load&Balancer?

Frequently Asked Questions

  • Bootcamp is given online / remotely by an experienced trainer and team.
  • During the bootcamp, you will learn professional data engineering at a level that you can easily use in business life.
  • You will experience a real-life process with content that is not available in any online or classroom training in Turkish and is specific to bootcamp participants only.
  • You will have the opportunity to learn together and benefit from the power of the community.
  • Python knowledge (available in the preparation stage)
  • Basic Docker knowledge (available in the preparation stage)
  • Basic SQL and database knowledge (available in the preparation stage)

Education time:

  • Preparation stage 2 weeks over videos
  • Online lessons 8 weeks
  • Graduation project 2 weeks

Preparatory training starts 4 weeks before the live training

Online lessons: 8 July – 27 August 2023 (CloudDataOps-1)

Project presentations: 7 September 2023

Live training will be on Saturday-Sunday 10:00-13:00 (Istanbul time GMT+3).

In addition, there will be presentations/solutions for homework given on Thursday at 20:00 (Istanbul time GMT+3) on weekdays. (between 1-2 hours)

  • Student: 15.200₺ VAT Included.

  • Full-time: 19.000₺ VAT Included.

Note 1: 20% discount is applied to former VBO Bootcamp graduates.

Note 2: These are the current list prices and there may be price updates until final registration.

Note 3: The preparation phase is included in the price.

Note 4: You must not be working full-time for the student discount. At the same time, only one discount is available.

  • IAM
  • EC2
  • S3
  • Lambda
  • RDS
  • Redshift
  • Kinesis
  • EMR
  • CloudWatch
  • Glue
  • Athena
  • DynamoDB
  • OpenSearch
  • Quicksight
  • ElastiCache
  • Linux Basic, Bash Script (preparation stage)
  • Git Basic (preparation stage)
  • Crontab (preparation stage)
  • Postgresql & SQL Basics (preparation stage)
  • Docker & Kubernetes (preparation stage)
  • Data Engineering Concept
  • Big Data Basics
  • Data Management Architectures for Analytics
  • The AWS Data Engineer’s Toolkit
  • Data Cataloging, Security, and Governance
  • Architecting Data Engineering Pipelines
  • Ingesting Batch and Streaming Data
  • Transforming Data to Optimize for Analytics
  • Identifying and Enabling Data Consumers
  • Loading Data into a Data Mart
  • Orchestrating the Data Pipeline
  • Ad Hoc Queries with Amazon Athena
  • Visualizing Data with Amazon QuickSight
  • PySpark
  • Data Pipeline
  • ETL
  • Streaming
  • Querying

It is for those who are in the roles of Data Engineer, ML Engineer and Data Scientist in order of priority and candidates for these roles. Team leaders who have these roles in their team can also follow.

In addition, if you want to find your direction in the sector and decide where you want to go in a healthier way, we think that these issues will become clear after this training.

So, can I follow this program?

If you know basic Python programming and SQL, you can follow this course if you are familiar with basic computer science concepts.

The preparation stage will be followed through the videos.

Live training will be held online on Zoom.

Any computer connected to the internet and running docker is sufficient.

Important notes:

The language of bootcamp is English!

Certificate: A certificate will be issued for participants who meet the following three criteria at the same time. 1. Attending at least 70% of the lessons, 2. Doing at least 70% of the homework, 3. Getting at least 70 points out of 100 from the graduation project.

Resources to be shared with students: Educational video recordings, presentations and sample codes used in the course will be shared.

Cloud: Cloud cost belongs to the participant. A very high cloud cost is not expected. 20 USD maximum.

For all your questions and detailed information:

Bengisu Bostancı – mldataops@veribilimiokulu.com

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