Data engineering is one of the hottest careers today. But most colleges don’t offer a good curriculum in data engineering. But thankfully, there are a good number of free and paid courses you can take to learn and improve your data engineering skills.
The best way to position yourself for a data engineering career is to have a portfolio of projects you can use to show your skills. Paid courses curate the content you need and save you time but if you are willing to do some legwork, free courses will be sufficient to learn data engineering skills.
Data Engineering Courses
Udacity Data Engineer Nanodegree Program
- Time to complete – approximately 5 months, flexible learning program
- Cost – $399 per month or $1695 for 5-month access
- Prerequisites – Intermediate Python and SQL skills
- Access to career services. Includes Github portfolio review and Linkedin profile optimization
Course content
- Data modeling – Postgres and Cassandra
- Cloud data warehouse – AWS
- Spark and Data lakes
- Data pipelines with Airflow
- Capstone project
You can check out the details on Udacity’s Data Engineer Nanodegree Program here.
Data Camp – Data Engineer with Python
- Time to complete – 75 hours
- 19 courses
Course content
- Understanding data engineering
- Python Programming
- Introduction to data engineering
- Streamline data ingestion with Pandas
- Writing efficient python code
- Writing functions in python
- Introduction to shell
- Data processing in shell
- Introduction to bash scripting
- Unit testing for Data Science in Python
- Object-oriented programming in python
- Introduction to Airflow in Python
- Introduction to PySpark
- Introduction to AWS Boto in Python
- Data analysis in SQL (PostgreSQL)
- Introduction to relational databases in SQL
- Database design
- Introduction to Scala
- Big data fundamentals with PySpark
- Cleaning data with PySpark
- Introduction to MongoDB in Python
You can learn more about Data Camp’s Data engineer with Python course here.
Coursera – Data Engineering, Big Data, and Machine Learning on GCP Specialization
This course is offered by Google Cloud and is highly rated with 4.6 stars with almost 12,000 ratings. This specialization has 5 courses covering everything from Google Cloud fundamentals, building pipelines, and building Stream analytics.
- Time to complete (4 months at 4 hours per week)
- Flexible schedule
Course content
- Google Cloud Big Data and Machine Learning Fundamentals
- Modernizing Data Lakes and Data Warehouses with Google Cloud
- Building Batch Data Pipelines on Google Cloud
- Building Resilient Streaming Analytics Systems on Google Cloud
Coursera – Data Engineering Learning Path
This learning path from Coursera includes courses on SQL, Tableau, data analysis skills, and big data. There is a course for every level – beginner, intermediate, and advanced data professional.
- Time to complete – varies, as this is a learning path and not a course
- Flexible schedule
Course content
- Learn SQL Basics for Data Science Specialization
- Data Visualization with Tableau Specialization
- Data Analysis and Presentation Skills: the PwC Approach Specialization
- Big Data Specialization
- Preparing for Google Cloud Certification: Cloud Data Engineer Professional Certificate
Coursera- Data Warehousing for Business Intelligence Specialization
- Time to complete – 8 months (6 hours/week)
- Flexible schedule
- Level – Advanced
Course Content
- Business Intelligence Concepts, Tools, and Applications
EdX- Data Engineering Basics for Everyone
- Time to complete – 4 weeks (9-10 hours/week)
- Flexible schedule
- Level – Advanced
Course content
- Module 1: What is Data Engineering
- Module 2: Data Engineering Ecosystem
- Module 3: Data Engineering Lifecycle
- Module 4: Career Opportunities and Learning Paths