Download Udacity – Become a Data Engineer v1.0.0 2019-12

Description

Become a Data Engineer is a training course on data engineering and big data (Big Data) published by Udacity educational institute. The digital world is based on data and without data there is practically no digital world. Big data and data engineering are two relatively new and potential job fields that are used in the field of data sharing systems development and communication and information infrastructure construction. This training course covers almost all topics related to data science, and among the most important topics are the design of information models, the construction of analytical databases (data warehouses), data lake (Data Lake), automating the data transfer bus (Data Pipeline). , sorting, extraction and analysis of large datasets and… mentioned. Data engineering is one of the most lucrative careers this year, and professionals in this field earn over $115,000 a year!

Information modeling and types of relational and non-relational information models is one of the most important topics in the field of information engineering. The user must be able to use appropriate and practical information models according to the needs of the project and customer requests. The use of ETLs in the process of building information warehouses is very common and helps you to collect data from several sources at the same time and after filtering and filtering additional data, store the final information in databases and information warehouses such as PostgreSQL and Apache Cassandra. Today, cloud and online data warehouses are common, and during the educational process, you will learn the process of building and implementing data warehouses on Amazon cloud hosts (AWS). Learning the skills presented in this training course can prepare the student to assume various careers such as analysis engineer, big data engineer, information platform engineer, machine learning engineer and artificial intelligence.

What you will learn in the Become a Data Engineer course:

• Familiarity with the job field of data engineer and other fields related to it
• Construction of information infrastructure and data warehouses
• Designing relational and non-relational information models
• Construction and implementation of data warehouses and data lakes
• Data Pipeline Automation
• Sorting, extraction and analysis of large datasets
• Receiving data from several separate information sources and filtering and storing them
• Implementation of data warehouse on Amazon cloud servers (AWS)
• Understanding the big data ecosystem and related frameworks
• Planning, automating and monitoring the data pipeline (Data Pipeline) with Apache Airflow
• Implementation of data quality review and evaluation tests
• Checking and tracking information sources

Course details

Publisher: Udacity
teacher: Amanda Moran ,Ben Goldberg ,Sameh El-Ansary ,Olli Iivonen ,David Drummond ,Judit Lantos And Juno Lee
English language
Education level: Intermediate
Number of courses: 50
Duration of training: assuming 5 to 10 hours of work per week, about 5 months

Course headings

Part 01: Welcome to the Nanodegree Program

Module 01: Welcome

Module 02: Career Services Orientation

Part 02: Data Modeling

Module 01: Data Modeling Lessons and Projects

Part 03: Cloud Data Warehouses

Module 01: Cloud Data Warehouses Lessons

Module 02: Project: Data Warehouse

Part 04: Data Lakes with Spark

Module 01: Data Lakes Lessons

Module 02: Project: Data Lake

Module 03: Career Services: GitHub

Part 05: Data Pipelines with Airflow

Module 01: Data Pipelines Lessons

Module 02: Project: Data Pipelines

Module 03: Career Services: LinkedIn

Part 06: Capstone Project

Module 01: DEND Capstone

Part 07 (Elective): Intro to Python

Module 01: Lessons

Part 08 (Elective): SQL for Data Analysis

Module 01: Lessons

Part 09 (Elective): Command Line Essentials

Module 01: Command Line Essentials

Part 10 (Elective): Git and Github

Module 01: Git and GitHub

Prerequisites of Become a Data Engineer course

Intermediate Python programming knowledge, of the sort gained through the Programming for Data Science Nanodegree program, other introductory programming courses or programs, or additional real-world software development experience. Including:

• Strings, numbers, and variables; statements, operators, and expressions
• Lists, tuples, and dictionaries; Conditions, loops
• Procedures, objects, modules, and libraries
• Troubleshooting and debugging; Research & documentation
• problem solving; Algorithms and data structures

This content is also available in the Introduction to Python Programming course.

Intermediate SQL knowledge and linear algebra mastery, addressed in the Programming for Data Science Nanodegree program, including:

• Joins, Aggregations, and Subqueries
• Table definition and manipulation (Create, Update, Insert, Alter)

This content is also available in the SQL for Data Analysis course.

What software and versions will I need in this program?

There are no software and version requirements to complete this Nanodegree program. All coursework and projects can be done via Student Workspaces in the Udacity online classroom.

Course images

Introduction video of Become a Data Engineer course

Installation guide

In order to view the courses of the course in an organized and regular way, run the index.html file and run the videos through this file.

English subtitle

Quality: 720p

download link

Download part 1 – 1 GB

Download part 2 – 1 GB

Download part 3 – 1 GB

Download part 4 – 560 MB

Password file(s): www.downloadly.ir

Size

3.56 GB