Download and Learn Become a Data Engineer Udacity Nanodegree Course 2023 for free with google drive download link.
Data Engineering is the foundation for the new world of Big Data. Enroll now to build production-ready data infrastructure, an essential skill for advancing your data career.
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What You’ll Learn in Become a Data Engineer Nanodegree
Data Engineering
5 months to complete
Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets. At the end of the program, you’ll combine your new skills by completing a capstone project.
Become a Data Engineer Intro Video:
Prerequisite knowledge
To be successful in this program, you should have intermediate Python and SQL skills.
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.
Data Modeling
Learn to create relational and NoSQL data models to fit the diverse needs of data consumers. Use ETL to build databases in PostgreSQL and Apache Cassandra.
Project – Data Modeling with Postgres
In this project, you’ll model user activity data for a music streaming app called Sparkify. You’ll create a relational database and ETL pipeline designed to optimize queries for understanding what songs users are listening to. In PostgreSQL you will also define Fact and Dimension tables and insert data into your new tables.
Project – Data Modeling with Apache Cassandra
In this project, you’ll model user activity data for a music streaming app called Sparkify. You’ll create a noSQL database and ETL pipeline designed to optimize queries for understanding what songs users are listening to. You’ll model your data in Apache Cassandra to allow for specific queries provided by the analytics team at Sparkify.
Cloud Data Warehouses
Sharpen your data warehousing skills and deepen your understanding of data infrastructure. Create cloud-based data warehouses on Amazon Web Services (AWS).
Project – Build a Cloud Data Warehouse
In this project, you are tasked with building an ETL pipeline that extracts their data from S3, stages them in Redshift, and transforms data into a set of dimensional tables for their analytics team to continue finding insights in what
songs their users are listening to.
Spark and Data Lakes
Understand the big data ecosystem and how to use Spark to work with massive datasets. Store big data in a data lake and query it with Spark.
Project – Build a Data Lake
In this project, you’ll build an ETL pipeline for a data lake. The data resides in S3, in a directory of JSON logs on user activity on the app, as well as a directory with JSON metadata on the songs in the app. You will load data from S3, process the data into analytics tables using Spark, and load them back into S3. You’ll deploy this Spark process on a cluster using AWS.
Data Pipelines with Airflow
Schedule, automate, and monitor data pipelines using Apache Airflow. Run data quality checks, track data lineage, and work with data pipelines in production.
Project – Data Pipelines with Airflow
In this project, you’ll continue your work on the music streaming company’s data infrastructure by creating and automating a set of data pipelines. You’ll configure and schedule data pipelines with Airflow and monitor and debug production pipelines.
Capstone Project
Combine what you’ve learned throughout the program to build your own data engineering portfolio project.
Project – Data Engineering Capstone
The purpose of the data engineering capstone project is to give you a chance to combine what you’ve learned throughout the program. You’ll define the scope of the project and the data you’ll be working with. You’ll gather data from several different data sources; transform, combine, and summarize it; and create a clean database for others to analyze.
The average base pay for a Data Engineer in the U.S. is $115k!
Become a Data Engineer Nanodegree Free Download Link:
