Course 1 of 11
Streaming with KafkaTopics, Producers/consumers, Stream processing, and more.
Advanced · Course · 3 weeks at 5 hrs/week
14 hours · 16 lessons · 16 exercises · 4 quizzes · 1 project
Career track
Data Engineer
11 courses, 80 hours, ending in Project: National Health Data Pipeline.
Yiga AI
Intermediate → Advanced en
Intermediate → Advanced · Career Track · 4–5 months at 10 hrs/week
- Duration
- 4–5 months
- Effort
- 10 hrs/week
- Courses
- 11
- Hands-on exercises
- 209
- Projects
- 11
- Certificate
- Included
Your pace≈ 4–5 months · 176 hours total
What you'll learn
11 courses in this track
- 01Streaming with KafkaAdvanced · 14 hours · 16 lessonsTopics · Producers/consumers · Stream processing · +1 more
- 02Cloud Data PlatformsIntermediate · 16.7 hours · 20 lessonsAWS/GCP/Azure services · Storage · IAM · +1 more
- 03Python for Data EngineeringIntermediate · 14 hours · 16 lessonsETL scripts · Logging · Testing · +1 more
- 04Advanced SQL for EngineersIntermediate · 16.8 hours · 21 lessonsPerformance · Partitioning · Transactions · +1 more
- 05Data Quality & GovernanceIntermediate · 14 hours · 16 lessonsValidation · Lineage · Privacy · +1 more
- 06Data Engineering FoundationsBeginner · 14 hours · 16 lessonsRoles · Architectures · Batch vs streaming · +1 more
- 07Big Data with SparkIntermediate · 16.7 hours · 20 lessonsRDDs & DataFrames · Transformations · Optimisation · +1 more
- 08dbt & Analytics EngineeringIntermediate · 16.7 hours · 20 lessonsModels · Tests · Docs · +1 more
- 09Workflow Orchestration with AirflowIntermediate · 16.7 hours · 20 lessonsDAGs · Operators · Scheduling · +1 more
- 10Data WarehousingIntermediate · 16.7 hours · 20 lessonsDimensional modelling · BigQuery/Snowflake · Loading · +1 more
- 11Project: National Health Data PipelineAdvanced · 19.3 hours · 24 lessonsIngest · Transform · Warehouse · +1 more
About this track
What you’ll learn.
1
Data Engineering Foundations
2
Advanced SQL for Engineers
3
Python for Data Engineering
4
Data Warehousing
Skills you’ll gain
Data
How this compares
Comparable to DataCamp Data Engineer · Coursera IBM Data Engineering. This track is 176 hours of study — about 4–5 months at 10 hrs/week.
Career outcomes
Turn learning into forward motion.
Build job-ready evidence for roles that use these skills every day.
Data Engineer
Analytics Engineer
Curriculum
A clear path, course by course.
Complete the courses in order so each new skill builds on the last.
- 1View course
- 2View course
Course 2 of 11
Cloud Data PlatformsAWS/GCP/Azure services, Storage, IAM, and more.
Intermediate · Course · 4 weeks at 5 hrs/week
17 hours · 20 lessons · 20 exercises · 4 quizzes · 1 project
- 3View course
Course 3 of 11
Python for Data EngineeringETL scripts, Logging, Testing, and more.
Intermediate · Course · 3 weeks at 5 hrs/week
14 hours · 16 lessons · 16 exercises · 4 quizzes · 1 project
- 4View course
Course 4 of 11
Advanced SQL for EngineersPerformance, Partitioning, Transactions, and more.
Intermediate · Course · 4 weeks at 5 hrs/week
17 hours · 21 lessons · 21 exercises · 4 quizzes · 1 project
- 5View course
Course 5 of 11
Data Quality & GovernanceValidation, Lineage, Privacy, and more.
Intermediate · Course · 3 weeks at 5 hrs/week
14 hours · 16 lessons · 16 exercises · 4 quizzes · 1 project
- 6View course
Course 6 of 11
Data Engineering FoundationsRoles, Architectures, Batch vs streaming, and more.
Beginner · Course · 3 weeks at 5 hrs/week
14 hours · 16 lessons · 16 exercises · 4 quizzes · 1 project
- 7View course
Course 7 of 11
Big Data with SparkRDDs & DataFrames, Transformations, Optimisation, and more.
Intermediate · Course · 4 weeks at 5 hrs/week
17 hours · 20 lessons · 20 exercises · 4 quizzes · 1 project
- 8View course
Course 8 of 11
dbt & Analytics EngineeringModels, Tests, Docs, and more.
Intermediate · Course · 4 weeks at 5 hrs/week
17 hours · 20 lessons · 20 exercises · 4 quizzes · 1 project
- 9View course
Course 9 of 11
Workflow Orchestration with AirflowDAGs, Operators, Scheduling, and more.
Intermediate · Course · 4 weeks at 5 hrs/week
17 hours · 20 lessons · 20 exercises · 4 quizzes · 1 project
- 10View course
Course 10 of 11
Data WarehousingDimensional modelling, BigQuery/Snowflake, Loading, and more.
Intermediate · Course · 4 weeks at 5 hrs/week
17 hours · 20 lessons · 20 exercises · 4 quizzes · 1 project
- 11View course
Course 11 of 11
Project: National Health Data PipelineIngest, Transform, Warehouse, and more.
Advanced · Course · 4 weeks at 5 hrs/week
19 hours · 24 lessons · 24 exercises · 4 quizzes · 1 project
Applied learning project
Finish with work you can show.
Bring the track together in Project: National Health Data Pipeline. Apply what you have learned to a practical challenge and explain the decisions behind your solution.
- Data Engineering Foundations
- Advanced SQL for Engineers
- Python for Data Engineering
Learn from experts
Grace A.
AI for professions
Shows working professionals how to use AI responsibly inside everyday workflows.
“The examples felt relevant to public service and worked on the connection I actually have.”
Frequently asked questions
Before you begin.
Do I need prior experience?
This track is designed for intermediate → advanced learners. Start with the first course and follow the numbered path so each skill builds naturally.
How long will the track take?
The track contains 11 courses and about 176 hours of learning. Most learners finish in around 4–5 months at 10 hrs/week.
Can I learn on my phone?
Yes. Yiga lessons are designed to work across phones and computers, so you can keep learning on the device available to you.
Will I earn a credential?
You can earn a shareable Yiga credential after completing the required learning and assessment activities in the track.
Is financial support available?
Scholarship and financial-aid options are available for eligible learners. Contact the Yiga support team before enrolling for guidance.
Ready when you are
Start this track today.
Begin with course 1 of 11, Streaming with Kafka, and work through the path at your own pace.
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