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A tested transformation path from raw to a consumer-ready model.
Specialization Courses/Data & Analytics
AI-First Pro specialization
AI-First Pro: Data Engineering Specialization
Build the pipelines that make analytics, ML, and AI possible.
- Intermediate
- Instructor-led
- Projects + Experience
- Placement Assurance
Built around practical learning, projects, mentorship, and career readiness.
Real skills. Real solutions. A brighter tomorrow.
What you will learn
Gain in-demand, industry-relevant skill, create meaningful work, and drive smarter decisions with AI as your copilot.
- Design batch and incremental pipelines with clear contracts
- Model data for analytics and downstream ML
- Orchestrate, test, and observe data products
- Partner with analysts and ML engineers without becoming a bottleneck
- Work with SQL, Python, dbt
- Prepare toward roles such as Data Engineer
Your learning journey
A simple, focused path from learning to real-world impact.
- 1
Learn
Build a strong foundation with live classes, guided content, and hands-on labs.
- 2
Build
Work on real-world projects using industry tools and AI-powered workflows.
- 3
Demonstrate
Create a portfolio, gain practical experience, and get career-ready with mentorship and placement support.
Curriculum at a glance
A structured, hands-on curriculum designed for real-world outcomes.
- Products not scripts
- SLAs
- Ownership
Projects
Work you can speak about in an interview, not a single weekend demo.
Orchestrated pipeline
Schedules, retries, and a failure that pages the right person.
ML-ready features
A small feature set with freshness and documentation.
Outcomes
What you will be able to do, and the kinds of roles this track prepares you toward.
- Design batch and incremental pipelines with clear contracts
- Model data for analytics and downstream ML
- Orchestrate, test, and observe data products
- Partner with analysts and ML engineers without becoming a bottleneck
Data EngineerAnalytics EngineerData Platform EngineerETL Developer
FAQs
No. You need comfort with SQL and programming basics. ML literacy is useful because you will often serve ML teams, and the track includes that collaboration.