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Introduction to Relational Databases (RDBMS)

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 4 of  13. Are you ready to dive into the world of data engineering? In this course, you will learn the essential concepts behind relational databases and Relational Database Management Systems (RDBMS). You’ll study relational data models and discover how they are created and what benefits they bring, and how you can apply them to your own data. You’ll be introduced to several industry standard relational databases, including IBM DB2, MySQL, and PostgreSQL.

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Databases and SQL for Data Science with Python

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 5 of  13. The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment. You will create a database instance in the cloud. Through a series of hands-on labs you will practice building and running SQL queries. You will also learn how to access databases from Jupyter notebooks using SQL and Python.

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Introduction to NoSQL Databases

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 6 of  13. This course will provide you with technical hands-on knowledge of NoSQL databases and Database-as-a-Service (DaaS) offerings. You will start by learning the history and the basics of NoSQL databases and discover their key characteristics and benefits. You will learn about the four categories of NoSQL databases and how they differ from each other. You will explore the architecture and features of several different implementations of NoSQL databases. You will then get hands-on experience using those NoSQL databases to perform standard database management tasks.

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Introduction to Big Data with Spark and Hadoop

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 7 of  13. In this course, you will learn about the characteristics of Big Data and its application in Big Data Analytics. You will gain an understanding about the features, benefits, limitations, and applications of some of the Big Data processing tools. You’ll explore how Hadoop and Hive help leverage the benefits of Big Data while overcoming some of the challenges it poses. Apache Spark is an open-source processing engine that provides users new ways to store and make use of big data and Resilient Distributed Datasets that enable parallel processing.

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Data Engineering and Machine Learning using Spark

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 8 of  13. In this short course you'll gain practical skills when you learn how to work with Apache Spark for Data Engineering and Machine Learning (ML) applications. You will work hands-on with Spark MLlib, Spark Structured Streaming, and more to perform extract, transform and load (ETL) tasks as well as Regression, Classification, and Clustering. The course culminates in a project where you will apply your Spark skills to an ETL for ML workflow use-case. Recommended: Completion of The Introduction to Big Data with Spark and Hadoop course prior to starting this one.

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Hands-on Introduction to Linux Commands and Shell Scripting

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 9 of  13. This mini-course provides a practical introduction to commonly used Linux / UNIX shell commands and teaches you basics of Bash shell scripting to automate a variety of tasks. The course includes both video-based lectures as well as hands-on labs to practice and apply what you learn. In this course you will work with general purpose commands, directory management commands, file management commands, access control command, text processing commands,  and networking commands.

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Python Project for Data Engineering

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 3 of  13. This mini-course is intended to apply foundational Python skills by implementing different techniques to collect and work with data. Assume the role of a Data Engineer and extract data from multiple file formats, transform it into specific datatypes, and then load it into a single source for analysis. Continue with the course and test your knowledge by implementing webscraping and extracting data with APIs all with the help of multiple hands-on labs. PRE-REQUISITE: **Python for Data Science, AI and Development** course from IBM is a pre-requisite for this project course. 

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ETL and Data Pipelines with Shell, Airflow and Kafka

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 11 of  13. During this course, you will learn how ELT and ETL processing differ, identify methods and tools used for extracting the data, merging extracted data, and for importing data into repositories. You will also define transformations to make the data credible, contextual, and accessible to users. You will be able to outline methods for loading data into the destination system, verifying data quality, monitoring load failures, and the use of recovery mechanisms in case of failure. 

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Getting Started with Data Warehousing and BI Analytics

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 12 of  13. After taking this course, you will be able to describe different kinds of repositories including data marts, data lakes, and data reservoirs, and explain their functions and uses. You will also be able to describe how data warehouses serve a single source of data truth for  organization’s current and historical data. Finally, you will complete a shareable final project that enables you to demonstrate the skills you acquired in each module.

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Data Engineering Capstone Project

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 13 of  13. In this course you will apply a variety of data engineering skills and techniques you have learned as part of the previous courses in the IBM Data Engineering Professional Certificate. You will assume the role of a Junior Data Engineer who has recently joined the organization and be presented with a real-world use case that requires a data engineering solution.

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Relational Database Administration (DBA)

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 10 of  13. In this course, you will discover some of the activities, techniques, and best practices for managing a database. You will learn about configuring and upgrading database server software, database security; how to implement user authentication, assign roles, and assign object-level permissions. You will also gain an understanding of how to perform backup and restore procedures in case of system failures. You will learn to optimize databases for performance, monitor databases, collect diagnostic data, and access error information to help you resolve issues that may occur. 

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Introduction to Data Engineering

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 1 of  13. This course introduces you to the core concepts, processes, and tools you need to know in order to get a foundational knowledge of data engineering. You will gain an understanding of the modern data ecosystem and the role Data Engineers, Data Scientists, and Data Analysts play in this ecosystem. In this course, you will learn about the data engineering lifecycle. You will also learn about security, governance, and compliance. The course also includes hands-on labs.

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Python for Data Science, AI & Development

LENGTH OF ACCESS: Two Months
LOCATION: Online

Course 2 of  13. Kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python. This course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn Python fundamentals, including data structures and data analysis, complete hands-on exercises throughout the course modules, and create a final project to demonstrate your new skills. 

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LENGTH OF ACCESS: Three Months
LOCATION: Online

In this IBM Data Engineering bundle, take all 13 courses towards your certificate AND earn several IBM Data Engineering badges while saving 10% off the individual course tuition rates. Search for course # 85218 to see all the courses/course descriptions.

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