(Coursera) IBM Data Engineering Professional Certificate
About Course
Become an IBM Data Engineering Professional with Free Online Courses
Unlock your potential in the exciting field of data engineering with this comprehensive IBM Data Engineering Professional Certificate program. Completely free and offered through top online learning platforms like Udemy, Udacity, Coursera, MasterClass, NearPeer, and more, this program equips you with in-demand skills for a successful career.
Master core data engineering concepts, including:
- SQL: Learn the foundation of database query language.
- RDBMS: Understand relational database management systems.
- ETL: Master data extraction, transformation, and loading techniques.
- Data Warehousing: Build and manage efficient data warehouses.
- NoSQL: Explore non-relational database systems for diverse data structures.
- Big Data: Learn to handle massive datasets and analyze them effectively.
- Spark: Gain expertise in this powerful framework for big data processing.
Gain hands-on experience with real-world data engineering projects and prepare for high-demand roles in this rapidly growing field. Start your free journey to becoming an IBM Data Engineering Professional today!
Course Content
Introduction to Data Engineering
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A Message from the Professor
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01_welcome-to-introduction-to-data-engineering
03:22 -
02_modern-data-ecosystem
04:50 -
03_key-players-in-the-data-ecosystem
05:36 -
04_what-is-data-engineering
04:23 -
05_viewpoints-defining-data-engineering
04:26 -
06_viewpoints-evolution-of-data-engineering
07:34 -
01_responsibilities-and-skillsets-of-a-data-engineer
05:26 -
02_viewpoints-skills-and-qualities-to-be-a-data-engineer
06:57 -
03_a-day-in-the-life-of-a-data-engineer
03:36 -
01_overview-of-the-data-engineering-ecosystem
04:52 -
02_types-of-data
04:01 -
03_understanding-different-types-of-file-formats
04:59 -
04_sources-of-data
07:56 -
05_languages-for-data-professionals
08:30 -
06_viewpoints-working-with-varied-data-sources-and-types
06:37 -
01_overview-of-data-repositories
04:33 -
02_rdbms
07:37 -
03_nosql
07:34 -
04_data-warehouses-data-marts-and-data-lakes
07:15 -
05_optional-data-lakehouses-explained
08:47 -
06_viewpoints-considerations-for-choice-of-data-repository
06:24 -
07_etl-elt-and-data-pipelines
06:36 -
08_data-integration-platforms
04:47 -
09_viewpoints-tools-databases-and-data-repositories-of-choice
06:37 -
01_foundations-of-big-data
05:21 -
02_big-data-processing-tools-hadoop-hdfs-hive-and-spark
06:30 -
03_viewpoints-impact-of-big-data-on-data-engineering
03:40 -
01_architecting-the-data-platform
07:11 -
02_factors-for-selecting-and-designing-data-stores
06:45 -
03_security
06:21 -
04_viewpoints-importance-of-data-security
04:02 -
01_how-to-gather-and-import-data
06:30 -
02_data-wrangling
07:14 -
03_tools-for-data-wrangling
05:37 -
01_querying-and-analyzing-data
05:40 -
02_performance-tuning-and-troubleshooting
07:05 -
01_governance-and-compliance
07:35 -
01_career-opportunities-in-data-engineering
05:52 -
02_viewpoints-get-into-data-engineering
07:51 -
03_data-engineering-learning-path
03:39 -
04_viewpoints-what-do-employers-look-for-in-a-data-engineer
06:24 -
05_viewpoints-the-many-paths-to-data-engineering
05:40 -
06_viewpoints-advice-to-aspiring-data-engineers
06:46 -
Course Material Download Link
00:00
Python for Data Science, AI & Development
Python Project for Data Engineering
Introduction to Relational Databases (RDBMS)
Databases and SQL for Data Science with Python
Hands-on Introduction to Linux Commands and Shell Scripting
Relational Database Administration (DBA)
ETL and Data Pipelines with Shell, Airflow and Kafka
Getting Started with Data Warehousing and BI Analytics
Introduction to NoSQL Databases
Introduction to Big Data with Spark and Hadoop
Machine Learning with Apache Spark
Data Engineering Capstone Project
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