IBM Data Engineering Professional Certificate

IBM Data Engineering Professional Certificate

Prepare for a career as a Data Engineer. Gain the in-demand skills and hands-on experience to get job-ready in less than 5 months.

IBM Skills Network Team
Muhammad Yahya
Abhishek Gagneja

Instructors: IBM Skills Network Team

2,595 already enrolled

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(4,403 reviews)

Beginner level

Recommended experience

Flexible schedule
6 months, 10 hours a week
Learn at your own pace
Earn degree credit

What you'll learn

  • Master the most up-to-date practical skills and knowledge data engineers use in their daily roles

  • Learn to create, design, & manage relational databases & apply database administration (DBA) concepts to RDBMSs such as MySQL, PostgreSQL, & IBM Db2 

  • Develop working knowledge of NoSQL & Big Data using MongoDB, Cassandra, Cloudant, Hadoop, Apache Spark, Spark SQL, Spark ML, and Spark Streaming 

  • Implement ETL & Data Pipelines with Bash, Airflow & Kafka; architect, populate, deploy Data Warehouses; create BI reports & interactive dashboards

Details to know

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Taught in English
Recently updated!

June 2024

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Advance your career with in-demand skills

  • Receive professional-level training from IBM
  • Demonstrate your technical proficiency
  • Earn an employer-recognized certificate from IBM
median U.S. salary for Data Engineering
U.S. job openings in Data Engineering

Get exclusive access to career resources upon completion

  • Soft skills training

    Get free access to IBM’s People and Soft Skills Specialization

  • Resume review

    Improve your resume and LinkedIn with personalized feedback

  • Interview prep

    Practice your skills with interactive tools and mock interviews

  • Career support

    Plan your career move with Coursera’s job search guide

¹Lightcast™ Job Postings Report, United States, 7/1/22-6/30/23. ²Based on program graduate survey responses, United States 2021.


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Professional Certificate - 16 course series

Introduction to Data Engineering

Course 112 hours4.7 (2,495 ratings)

What you'll learn

  • List basic skills required for an entry-level data engineering role.

  • Discuss various stages and concepts in the data engineering lifecycle.

  • Describe data engineering technologies such as Relational Databases, NoSQL Data Stores, and Big Data Engines.

  • Summarize concepts in data security, governance, and compliance.

Skills you'll gain

Category: Shell Script
Category: Bash (Unix Shell)
Category: Extract Transform and Load (ETL)
Category: Linux
Category: Linux Commands

Python for Data Science, AI & Development

Course 225 hours4.6 (36,176 ratings)

What you'll learn

  • Learn Python - the most popular programming language and for Data Science and Software Development.

  • Apply Python programming logic Variables, Data Structures, Branching, Loops, Functions, Objects & Classes.

  • Demonstrate proficiency in using Python libraries such as Pandas & Numpy, and developing code using Jupyter Notebooks.

  • Access and web scrape data using APIs and Python libraries like Beautiful Soup.

Skills you'll gain

Category: Cloud Database
Category: Mongodb
Category: Cassandra
Category: NoSQL
Category: Cloudant

Python Project for Data Engineering

Course 33 hours4.6 (613 ratings)

What you'll learn

  • Demonstrate your skills in Python for working with and manipulating data

  • Implement webscraping and use APIs to extract data with Python

  • Play the role of a Data Engineer working on a real project to extract, transform, and load data

  • Use Jupyter notebooks and IDEs to complete your project

Introduction to Relational Databases (RDBMS)

Course 415 hours4.6 (541 ratings)

What you'll learn

  • Describe data, databases, relational databases, and cloud databases.

  • Describe information and data models, relational databases, and relational model concepts (including schemas and tables). 

  • Explain an Entity Relationship Diagram and design a relational database for a specific use case.

  • Develop a working knowledge of popular DBMSes including MySQL, PostgreSQL, and IBM DB2

Skills you'll gain

Category: Data Science
Category: Data Analysis
Category: Python Programming
Category: Numpy
Category: Pandas

Databases and SQL for Data Science with Python

Course 520 hours4.6 (19,726 ratings)

What you'll learn

  • Analyze data within a database using SQL and Python.

  • Create a relational database and work with multiple tables using DDL commands.

  • Construct basic to intermediate level SQL queries using DML commands.

  • Compose more powerful queries with advanced SQL techniques like views, transactions, stored procedures, and joins.

Skills you'll gain

Category: Machine Learning
Category: Machine Learning Pipelines
Category: Data Engineer
Category: SparkML
Category: Apache Spark

Hands-on Introduction to Linux Commands and Shell Scripting

Course 614 hours4.7 (1,188 ratings)

What you'll learn

  • Describe the Linux architecture and common Linux distributions and update and install software on a Linux system.

  • Perform common informational, file, content, navigational, compression, and networking commands in Bash shell.

  • Develop shell scripts using Linux commands, environment variables, pipes, and filters.

  • Schedule cron jobs in Linux with crontab and explain the cron syntax. 

Skills you'll gain

Category: Python Programming
Category: Relational Databases
Category: SQL
Category: NoSQL
Category: Data Pipelines

Relational Database Administration (DBA)

Course 721 hours4.4 (186 ratings)

What you'll learn

  • Create, query, and configure databases and access and build system objects such as tables.

  • Perform basic database management including backing up and restoring databases as well as managing user roles and permissions. 

  • Monitor and optimize important aspects of database performance. 

  • Troubleshoot database issues such as connectivity, login, and configuration and automate functions such as reports, notifications, and alerts. 

Skills you'll gain

Category: Python Programming
Category: Information Engineering
Category: Extract Transform and Load (ETL)
Category: Data Engineer
Category: Web Scraping

ETL and Data Pipelines with Shell, Airflow and Kafka

Course 817 hours4.5 (319 ratings)

What you'll learn

  • Describe and contrast Extract, Transform, Load (ETL) processes and Extract, Load, Transform (ELT) processes.

  • Explain batch vs concurrent modes of execution.

  • Implement ETL workflow through bash and Python functions.

  • Describe data pipeline components, processes, tools, and technologies.

Skills you'll gain

Category: Extract Transform and Load (ETL)
Category: Data Engineer
Category: Apache Kafka
Category: Apache Airflow
Category: Data Pipelines

Data Warehouse Fundamentals

Course 915 hours4.4 (161 ratings)

What you'll learn

  • Job-ready data warehousing skills in just 6 weeks, supported by practical experience and an IBM credential.

  • Design and populate a data warehouse, and model and query data using CUBE, ROLLUP, and materialized views.

  • Identify popular data analytics and business intelligence tools and vendors and create data visualizations using IBM Cognos Analytics.

  • How to design and load data into a data warehouse, write aggregation queries, create materialized query tables, and create an analytics dashboard.

Skills you'll gain

Category: Big Data
Category: SparkSQL
Category: SparkML
Category: Apache Hadoop
Category: Apache Spark

What you'll learn

  • Explore the purpose of analytics and Business Intelligence (BI) tools

  • Discover the capabilities of IBM Cognos Analytics and Google Looker Studio

  • Showcase your proficiency in analyzing DB2 data with IBM Cognos Analytics

  • Create and share interactive dashboards using IBM Cognos Analytics and Google Looker Studio

Skills you'll gain

Category: Python Programming
Category: Cloud Databases
Category: Relational Database Management System (RDBMS)
Category: SQL
Category: Jupyter notebooks

Introduction to NoSQL Databases

Course 1118 hours4.6 (267 ratings)

What you'll learn

  • Differentiate among the four main categories of NoSQL repositories.

  • Describe the characteristics, features, benefits, limitations, and applications of the more popular Big Data processing tools.

  • Perform common tasks using MongoDB tasks including create, read, update, and delete (CRUD) operations.

  • Execute keyspace, table, and CRUD operations in Cassandra.

Skills you'll gain

Category: Database Security
Category: Database (DBMS)
Category: Database Servers
Category: database administration
Category: Relational Database

Introduction to Big Data with Spark and Hadoop

Course 1218 hours4.4 (349 ratings)

What you'll learn

  • Explain the impact of big data, including use cases, tools, and processing methods.

  • Describe Apache Hadoop architecture, ecosystem, practices, and user-related applications, including Hive, HDFS, HBase, Spark, and MapReduce.

  • Apply Spark programming basics, including parallel programming basics for DataFrames, data sets, and Spark SQL.

  • Use Spark’s RDDs and data sets, optimize Spark SQL using Catalyst and Tungsten, and use Spark’s development and runtime environment options.

Skills you'll gain

Category: Data Science
Category: Database (DBMS)
Category: Information Engineering
Category: SQL
Category: NoSQL

Machine Learning with Apache Spark

Course 1315 hours4.6 (65 ratings)

What you'll learn

  • Describe ML, explain its role in data engineering, summarize generative AI, discuss Spark's uses, and analyze ML pipelines and model persistence.

  • Evaluate ML models, distinguish between regression, classification, and clustering models, and compare data engineering pipelines with ML pipelines.

  • Construct the data analysis processes using Spark SQL, and perform regression, classification, and clustering using SparkML.

  • Demonstrate connecting to Spark clusters, build ML pipelines, perform feature extraction and transformation, and model persistence.

Skills you'll gain

Category: Business Intelligence
Category: Data Visualization
Category: IBM Cognos Analytics
Category: Google Looker Studio
Category: Dashboards

Data Engineering Capstone Project

Course 1416 hours4.7 (101 ratings)

What you'll learn

  • Demonstrate proficiency in skills required for an entry-level data engineering role.

  • Design and implement various concepts and components in the data engineering lifecycle such as data repositories.

  • Showcase working knowledge with relational databases, NoSQL data stores, big data engines, data warehouses, and data pipelines.

  • Apply skills in Linux shell scripting, SQL, and Python programming languages to Data Engineering problems.

Skills you'll gain

Category: Convolutional Neural Network
Category: Information Engineering
Category: Querying Databases
Category: Data Generation
Category: Generative AI

What you'll learn

  • Leverage various generative AI tools and techniques in data engineering processes across industries

  • Implement various data engineering processes such as data generation, augmentation, and anonymization using generative AI tools

  • Practice generative AI skills in hands-on labs and projects for data warehouse schema design and infrastructure setup

  • Evaluate real-world case studies showcasing the successful application of Generative AI for ETL and data repositories

Skills you'll gain

Category: Database (DB) Design
Category: Postgresql
Category: Relational Database Management System (RDBMS)
Category: Database Architecture
Category: MySQL

Data Engineering Career Guide and Interview Preparation

Course 1611 hours4.5 (15 ratings)

What you'll learn

  • Describe the role of a data engineer and some career path options as well as the prospective opportunities in the field.

  • Explain how to build a foundation for a job search, including researching job listings, writing a resume, and making a portfolio of work.

  • Summarize what a candidate can expect during a typical job interview cycle, different types of interviews, and how to prepare for interviews.

  • Explain how to give an effective interview, including techniques for answering questions and how to make a professional personal presentation.

Skills you'll gain

Category: Cubes
Category: Data Warehousing
Category: Snowflake Schemas
Category: Data Lakes
Category: Rollups
Category: Data Marts
Category: Star Schemas


IBM Skills Network Team
58 Courses818,593 learners
Muhammad Yahya
4 Courses55,036 learners
Abhishek Gagneja
5 Courses117,745 learners

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