Learn Data Engineering Guided Projects Online: Free Course with AI Tutor & Certificate
This free course with an optional paid certificate teaches you how to build end to end data engineering projects. Across 24 hours and 45 lessons, you'll master ETL pipelines, AWS cloud data engineering, and Apache Airflow. You'll complete 4 hands-on projects perfect for your resume.
What you'll learn in this Data Engineering Guided Projects course
Five concrete outcomes you'll walk away with, each mapped to modules in the curriculum below.
Design, build, and manage robust ETL pipelines using Python and cloud-based tools like AWS.
Implement and orchestrate complex workflows with Apache Airflow and AWS Step Functions.
Develop real-time data streaming solutions using Apache Kafka for efficient data processing.
Transform and model data effectively using dbt, ensuring high-quality data outputs.
Deploy and manage containerized applications with Docker and Kubernetes, and automate infrastructure with Terraform.
Data Engineering Guided Projects course syllabus
01 Python and SQL Foundations for Data Engineering
- Python environment setup for data engineering
- Python pandas for data manipulation
- Python requests library for API data
- SQL joins and aggregations for data engineers
- Python database connections with SQLAlchemy
- Git version control for data projects
02 ETL Pipeline Development
- ETL pipeline design principles
- Building ETL pipeline with Python
- Data validation and quality checks
- Error handling in ETL pipelines
- ETL pipeline logging and monitoring
- Parallel processing in ETL pipelines
- ETL pipeline testing strategies
03 Cloud Data Engineering with AWS
- AWS S3 for data storage tutorial
- AWS Lambda for serverless data processing
- AWS Glue ETL jobs tutorial
- AWS RDS database setup for data engineering
- AWS Redshift data warehouse tutorial
- AWS Step Functions for workflow orchestration
- AWS CloudFormation for infrastructure as code
04 Apache Airflow Workflow Orchestration
- Apache Airflow installation and setup
- Airflow DAG creation tutorial
- Airflow operators and tasks
- Airflow scheduling and triggers
- Airflow connections and hooks
- Airflow custom operators development
- Airflow production deployment best practices
05 Real-time Data Streaming with Kafka
- Apache Kafka basics tutorial
- Kafka producer and consumer Python
- Kafka Connect for data integration
- Kafka Streams processing tutorial
- Kafka monitoring and performance tuning
- Kafka cluster setup and management
06 Data Transformation with dbt
- dbt installation and project setup
- dbt models and transformations
- dbt macros and jinja templating
- dbt testing and documentation
- dbt deployment and CI/CD
- dbt advanced modeling techniques
07 Containerization and Infrastructure
- Docker for data engineering tutorial
- Docker Compose for multi-container applications
- Kubernetes basics for data engineers
- Terraform infrastructure as code tutorial
- CI/CD pipelines for data engineering
- Data engineering monitoring and alerting
Real-world projects you'll work on
Practice the exact kind of work Data Engineering Guided Projects professionals do on the job.
Building a Scalable ETL Pipeline for Real-Time Data Processing at TechGiant Inc.
Implementing a Serverless Data Workflow with AWS Lambda and Step Functions for FinTech Innovations
Designing a Robust Data Warehouse Solution with AWS Redshift for Global Retail Analytics
Orchestrating Complex Data Workflows with Apache Airflow for HealthTech Solutions
Skills you'll gain
Add these to your LinkedIn profile and resume the day you finish.
Who should take this Data Engineering Guided Projects course?
And exactly what you need before starting (spoiler: almost nothing).
This course is for
- Computer science students looking for data engineering projects for final year submissions.
- Software engineers wanting to transition into data engineering roles.
- Data analysts aiming to learn cloud data engineering with AWS and ETL pipeline development.
- Job seekers needing end to end data engineering projects for their resume.
Prerequisites
- Basic understanding of Python programming and SQL queries is required.
- Familiarity with general database concepts and data structures.
- A computer with internet access to set up the Python environment.
How learning works on LearnTube
The structure of a bootcamp, the price of free.
AI curates your path
Our AI picks the top 1% of video content for each topic and arranges it into a structured, goal-based curriculum. No more tutorial roulette.
Learn, then get quizzed
After every lesson, your AI tutor asks you a question and gives personalised feedback on your answer, so gaps get fixed immediately.
Finish with proof
Complete the course, build the capstone project, and claim a certificate recognised by 900+ hiring partners.
A complete Data Engineering Guided Projects course: free, structured and job-focused
This free course offers an optional paid certificate while teaching you how to build end to end data engineering projects. LearnTube pairs curated YouTube video lessons with an AI tutor that gives you a quick quiz after every single lesson. This setup makes sure you actually understand the concepts before moving forward. You'll start with Python environment setup for data engineering and progress through 7 focused modules. These include Python and SQL Foundations for Data Engineering, ETL Pipeline Development, and Cloud Data Engineering with AWS.
As you advance through the 24 hours of content, you'll tackle advanced topics like Apache Airflow Workflow Orchestration, Real-time Data Streaming with Kafka, Data Transformation with dbt, and Containerization and Infrastructure. The true value comes from building data engineering portfolio projects. You'll complete four major hands-on builds, such as Building a Scalable ETL Pipeline for Real-Time Data Processing at TechGiant Inc. and Implementing a Serverless Data Workflow with AWS Lambda and Step Functions for FinTech Innovations.
By the end of the 45 video lessons, you'll have practical experience Designing a Data Warehouse Solution with AWS Redshift for Global Retail Analytics and Orchestrating Complex Data Workflows with Apache Airflow for HealthTech Solutions. These are ideal data engineering projects for resume building. You'll learn how to deploy containerized applications with Docker and Kubernetes, automate infrastructure with Terraform, and model data effectively using dbt.
Jobs you can target after learning Data Engineering Guided Projects
Data Engineering Guided Projects is a gateway skill for some of the fastest-growing roles in tech.
Designs and maintains data pipelines to prepare large datasets for analytical use.
Builds systems that extract, transform, and load data into central data warehouses.
Manages data infrastructure and serverless workflows on platforms like AWS.
Typical entry-level salary ranges in India as of September 2026. Actual compensation varies by city, company and experience.
Earn a Data Engineering Guided Projects certificate employers recognise
Finish the course and claim a certificate you can share anywhere.
- Learn 100% free: every lesson, quiz and the AI tutor cost nothing
- Claim your certificate when you complete the course (an optional paid add-on)
- Recognised by 900+ hiring partners across India
- One click to share on LinkedIn and add to your resume
Why learners choose LearnTube
Real reviews from Google. You learn free, you get assessed free, and you pay only if you want the certificate.
Though I have 11 years of experience as an HRBP, the course helped me refresh my knowledge and gave me insights into new trends in the market. The modules were clear and easy to understand, and the quizzes were well designed. I have added the certificate to my LinkedIn profile.
I had a lot of doubts while learning, but the AI chatbot answered them in detail with simple summaries. The videos on the platform saved me a lot of time as I didn't have to search YouTube and watch random content.
Just earned my certificate in HR Management from LearnTube.ai! The platform is user-friendly and the assessment was a great way to validate my knowledge. Feeling proud of this accomplishment!
I enrolled in a LearnTube personalized course to get into a Data Analytics role. It helped me learn SQL in depth and gave me hands-on experience with Power BI. I attached the LearnTube certificate to my CV, it added credibility to my profile, and I'm currently in the interview process.
The interface is user-friendly and intuitive, making it easy to navigate the course. I encountered no errors during my time using the platform, which was a refreshing change from other online learning platforms.
Just cleared the Business Analyst assessment and got certified! Loved how the course simplifies big concepts like data-driven decision making into short, practical lessons. The automated quizzes kept me on track the whole time. Perfect boost for my resume!
The certificate gave me a real edge during my B.Tech. By the time I graduated, I had skills that set me apart from my peers, and the certification opened up more job opportunities. It gave me the confidence to stand out during interviews.
I manage many software projects as a General Manager and was looking for a good certification program to stay competitive. After researching many programs, I chose LearnTube and it was much better than I expected. The material is well-organized and practical, and what I liked most is the lifetime access.
Frequently asked questions
Everything learners ask before starting this Data Engineering Guided Projects course.
How long does this data engineering projects course take?
The course takes about 24 hours to complete. You will work through 45 video lessons and 7 modules at your own pace, making it easy to fit into a busy schedule.
What will I be able to build after this course?
You will build four complete portfolio pieces. These include a scalable ETL pipeline for real-time data processing, a serverless AWS data workflow, an AWS Redshift data warehouse, and an Apache Airflow orchestration project.
Are data engineering skills still in demand?
Yes, companies heavily rely on data engineers to manage their data infrastructure. Skills in AWS, Apache Kafka, and ETL pipeline development are highly sought after by employers looking to process large volumes of information.
Is this data engineering course really free?
Yes, all 45 video lessons, AI tutor quizzes, and the four hands-on projects are completely free to learn. You only pay if you choose to add the optional verified certificate at the end.
Do I need prior coding experience for this course?
Yes, you need a basic understanding of Python and SQL. The first lesson covers Python environment setup for data engineering, but knowing basic programming concepts will help you grasp the advanced cloud topics faster.
Can I use these projects on my resume?
Absolutely. The four hands-on builds serve as excellent end to end data engineering projects for your resume. They demonstrate practical experience with industry tools like Apache Airflow, dbt, Docker, and Kubernetes.
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