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Master Data Engineering for AI Certification

Master production-grade data pipelines using Databricks Delta Lake and Medallion Architecture. Train with experts to earn your Databricks Certified Data Engineer Professional certification through hands-on labs.

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Bain & Company
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Shell
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Data Engineering for AI

Explore Data Engineering for AI certification and training courses — delivered live by certified instructors.

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Relevant Technology
Level
Duration
All Courses
Browse all certification courses across Microsoft, Cisco, AWS, CompTIA, VMware and more
Showing 10 courses
Associate
DP-604T00: Implement a Data Science and Machine Learning Solution for AI with Microsoft Fabric
DP-604T00 1 day · 8hrs
6,876+ 4.6 USD 650
View Course
Associate
DP-3014: Build Machine Learning Solutions Using Azure Databricks
DP-3014 1 day · 8hrs
8,103+ 4.8 USD 650
View Course
Associate
Machine Learning for Azure Databricks
3 days · 24hrs
4,635+ 4.5 On Request
View Course
Associate
DP-3027: Implement a Data Engineering Solution with Azure Databricks
DP-3027 1 day · 8hrs
2,730+ 4.5 USD 650
View Course
Associate
Azure AI Engineering: Semantic Kernel & Agents
5 days · 40hrs
6,571+ 4.6 USD 1,750
View Course
Associate
AWS Data Engineering: PySpark, Glue & Lambda
10 days · 80hrs
2,226+ 4.6 On Request
View Course
Associate
IBM DataStage-aaS Anywhere Developers Training
4 days · 32hrs
3,466+ 4.6 On Request
View Course
Associate
NiFi 2.0: Data Flow Migration and AI Integration (DOPS-243)
1 day · 8hrs
2,924+ 4.9 On Request
View Course
Associate
Serverless Data Processing with Dataflow
3 days · 24hrs
7,871+ 4.6 On Request
View Course
Associate
Python for Data Engineering and Machine Learning (Python Institute)
5 days · 40hrs
5,728+ 4.8 USD 1,700
View Course
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Data Engineering for AI Certification Training with Koenig Solutions

Course Overview

What is Data Engineering for AI?

Data Engineering for AI is the discipline of designing, building, and maintaining data systems specifically to support the training, deployment, and operation of artificial intelligence and machine learning models. Published by Databricks as a core component of its Data Intelligence Platform, it solves the challenge of transforming raw, unstructured, and real-time data into reliable, model-ready inputs. It extends traditional data engineering by integrating AI-specific capabilities such as feature engineering, vector database management, and retrieval augmented generation pipeline design. Key components include Delta Lake for unified data storage and governance, Databricks Feature Store for managing and serving ML features with point-in-time consistency, Databricks AI Search for vector-based retrieval in RAG applications, Lakeflow Pipelines for automated data workflows, and Lakebase for operationalizing RAG with embedded vector support in a governed Postgres environment. These tools enable scalable ingestion, transformation, feature computation, and real-time serving essential for production AI. This technology is for data engineers, ML engineers, and AI developers who build production-grade AI systems and require governed, scalable data pipelines that ensure feature consistency, eliminate training-serving skew, and support real-time inference and retrieval augmented generation workflows.

Python Programming

Write and debug Python scripts for data processing and automation

SQL Queries

Execute complex SQL queries on structured and semi-structured datasets

Apache Spark

Use PySpark to process large-scale datasets in distributed environments

Delta Lake

Implement ACID transactions and schema enforcement in Delta tables

Medallion Architecture

Design Bronze, Silver and Gold layer data pipelines for AI workloads

RAG Pipelines

Build retrieval-augmented generation workflows using vector embeddings

Who Should Take This Course?

Data Engineer

Build and maintain scalable data pipelines for AI model training and inference

AI Solution Engineer

Design and deploy AI-enabled data workflows using agentic AI and LLMs

Data Scientist

Access and prepare high-quality data for machine learning and NLP models

Machine Learning Engineer

Integrate data pipelines with model development and deployment environments

Data Architect

Design data lakehouse architectures and medallion data models for AI workloads

Analytics Manager

Oversee data infrastructure that supports AI-driven analytics and business intelligence

Career Outcomes

What Data Engineering for AI Certification Opens Up For You

Based on industry data from certified Data Engineering for AI professionals worldwide

104%

Median salary increase after AI upskilling

Salary Impact
+24%

Average salary increase reported after obtaining a Data Engineering for AI certification

Typical Salary Range (Global)
Entry
$75,000–$95,000
Mid
$95,000–$120,000
Senior
$120,000–$145,000

*Source: Glassdoor / LinkedIn 2025

Job Roles
  • Data Engineer
  • AI Data Engineer
  • Machine Learning Engineer
  • Cloud Data Engineer
  • Data Architect
  • Lead Data Engineer
  • AI Engineer
  • Data Scientist
  • Big Data Engineer
  • Staff AI Data Engineer
Companies Hiring
Mastercard Barclays EY Angel One SIXT Tata Consultancy Services Accenture IBM HyperVerge Qure.ai Ignitarium Razorthink ExaWizards TATA ELXSI bizAmica Wisteli

and 5,000+ organisations worldwide seeking Data Engineering for AI certified professionals

The building blocks every Data Engineering for AI solution is made of

01
Lakehouse
A unified data architecture that stores structured and unstructured data in Delta Lake format. Practitioners build scalable medallion architectures and enable cross-engine analytics with Spark and SQL.
02
Notebook
An interactive computing environment for writing and executing code in Python, Scala, SQL, or R. Practitioners build data ingestion, transformation, and analysis workflows with live visualizations.
03
Pipeline
A sequence of data integration steps that move and transform data from source to destination. Practitioners build ETL workflows using copy activities and orchestrate data flows.
04
Apache Spark Job Definition
A code artifact that defines batch or streaming jobs for execution on Spark clusters. Practitioners build production-grade data processing applications using compiled binaries.
PostgreSQL Data Store
KaireonAI utilizes PostgreSQL as the primary data store for Data Engineering for AI, managing schemas and interactions. It executes real DDL to automate table creation and maintain entity structures and decision history with high precision.
80+ Connectors
Accelerate your Data Engineering for AI workflows using 80+ native connectors. Seamlessly ingest data from databases, cloud storage, and SaaS apps. These secure, testable connections ensure reliable data pipelines for your enterprise AI initiatives.
✦ Sample Certificate

Your Data Engineering for AI Certification Awaits

See what your official Data Engineering for AI certification looks like. Download a sample — then let our advisors map the fastest path to earning the real one.

Sample Data Engineering for AI certification issued by Koenig Solutions — official Microsoft Authorized Learning Partner
🔒 Fill your details to unlock
Free · No credit card · Instant download
Learning Formats

Learning That Fits Your Life

Four formats. One quality standard. Every option comes with the same expert instructors, official courseware, and money-back guarantee.

Classroom Training Most Popular

Classroom Training

Traditional, instructor-led learning in popular global destinations.

Classroom Training

  • Hands-on lab sessions
  • Face-to-face with expert instructors
  • Global training centers
Live Online Classes Best Value

Live Online Classes

Flexible virtual learning with expert instructors from the comfort of your own space.

Live Online Classes

  • Live instructor-led sessions
  • Interactive Q&A & labs
  • Train from anywhere
Fly-Me-A-Trainer (FMAT) Fastest

Fly-Me-A-Trainer (FMAT)

Flexible on-site learning for larger groups. Fly an expert to your location anywhere in the world.

Fly-Me-A-Trainer (FMAT)

  • Expert trainer at your site
  • Custom schedule & pace
  • Any location worldwide
Flexi (Self-Paced) Most Flexible

Flexi (Self-Paced)

Self-paced learning with edited lectures, courseware, hands-on labs, and optional doubt clearing sessions.

Flexi (Self-Paced)

  • Edited video lectures
  • Hands-on labs & courseware
  • Optional doubt clearing sessions
1-on-1 Training Most Focused

1-on-1 Training

Dedicated instructor assigned exclusively to you for maximum personalisation and knowledge retention.

1-on-1 Training

  • Personalised schedule
  • Instructor adapts to your pace
  • Max knowledge retention
Customised Programmes Bespoke

Customised Programmes

Bespoke curricula tailored to your tech stack, business processes, and learning goals.

Customised Programmes

  • Custom course content
  • Fits your tech stack
  • Aligned to business goals
Webinar as a Service New

Webinar as a Service

Professionally hosted live webinars delivered to your global workforce at scale.

Webinar as a Service

  • Global workforce delivery
  • Live hosted sessions
  • Scalable & trackable
Qubits Assessment

Qubits

AI-powered assessments to benchmark skills, identify gaps, and measure training ROI.

Qubits

  • Skill benchmarking
  • Gap identification
  • Training ROI measurement
The Honest Comparison
How Koenig Stacks Up Against Every Alternative

Every factor that determines whether you actually pass your Data Engineering for AI exam — rated across every training format available.

Koenig
Official ALP Partner
12
/12 criteria ✓
ALP Provider
Other authorised partner
5
/12 criteria
Legacy Provider
Traditional classroom
2
/12 criteria
Self-Paced Platform
On-demand video
2
/12 criteria
Free Platform
Self-study / free tier
4
/12 criteria
Criteria Koenig Free Platform Self-Paced Platform ALP Provider Legacy Provider Note
Trainer Quality & Credentials
MCT-Certified Trainers Partial
Live Instructor-Led Delivery
1-on-1 Private Training
Microsoft Authorisation
Official Microsoft ALP Status
Official Microsoft Courseware Partial
ESI / EA Credits Accepted
Flexibility & Access
Any-Day / Flexi Start
On-Site / Fly-Me-A-Trainer Partial
Global Delivery Reach Partial
Results & Trust
Exam Pass Rate 95% N/A N/A N/A N/A Verified Data Engineering for AI success rates
Entry Price (Fundamentals) ~$745 · best value Free $15-30/mo ~$1,500+ ~$1,500+
Verified Learner Reviews 18,400+ · 4.9★ N/A N/A Limited Limited Verified Data Engineering for AI learner feedback

Data sourced from public pricing pages and review platforms. Accurate as of March 2026. Partial = available in select regions only.

Recognition

Awards & Recognition

Recognized by global vendors and quality bodies for training excellence

10+
Awards & Certifications
6+
Global Partners
15 Yrs
Great Place to Work
Microsoft Partner of Year
Winner of Microsoft Training Services Partner of the Year Award

Winner of Microsoft Training Services Partner of the Year Award

2025
Winner of Microsoft's ANZ Superstar Campaign

Winner of Microsoft's ANZ Superstar Campaign

2024
Winner of Microsoft's Asia Superstar Campaign

Winner of Microsoft's Asia Superstar Campaign

2022
Finalist – AWS Partner of the Year

Finalist – AWS Partner of the Year

2024
Winner of EC-Council ATC of the Year Award

Winner of EC-Council ATC of the Year Award

2024
Winner of the PECB Titanium Partner Award

Winner of the PECB Titanium Partner Award

2024
Certified as a Great Place to Work
Great Place to Work

Certified as a Great Place to Work

2011–2025
Winner of RedHat Gold Partner of the Year – Non-Retail (GLS India)

Winner of RedHat Gold Partner of the Year – Non-Retail (GLS India)

2025
Winner of RedHat Gold Partner of the Year – Non-Retail (GLS India)

Winner of RedHat Gold Partner of the Year – Non-Retail (GLS India)

2024
Winner of the Red Hat Partner of the Year Award

Winner of the Red Hat Partner of the Year Award

2023
Reviews

What our 500K+ alumni say

Verified reviews from learners certified on Azure, AI, Security, and more.

18,400+
Verified Reviews
4.9 / 5
Average Rating
95%
Would Recommend
1M+
Professionals Trained
  • ★★★★★

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    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified

    ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig’s on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client

    ✓ Verified
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    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified

    ✓ Verified
  • ★★★★★

    “Passed AZ-104 on first attempt. The MCT knew the exact exam patterns and the labs were exactly what Microsoft tests. Worth every penny.”

    Rahul M.

    Rahul M.

    Azure Administrator

    AZ-104 Certified

    ✓ Verified
  • ★★★★★

    “I trained 15 of my team members for SC-200. Koenig’s on-site delivery was seamless and all 15 passed within 3 months.”

    Sarah K.

    Sarah K.

    CISO, Financial Services

    Enterprise Client

    ✓ Verified
  • ★★★★★

    “The 1-on-1 format was a game changer. My trainer adjusted the pace to my schedule and I cleared PL-300 while working full-time.”

    Ahmed R.

    Ahmed R.

    Business Intelligence Lead

    PL-300 Certified

    ✓ Verified
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    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert

    ✓ Verified
  • ★★★★★

    “As an L&D head I’ve used 5 training vendors. Koenig’s MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

    James T.

    Head of L&D, UK Enterprise

    100+ Learners Trained

    ✓ Verified
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    “SC-900 and SC-300 back to back — both cleared first try. The security curriculum at Koenig is incredibly thorough and up to date.”

    Aisha N.

    Aisha N.

    Security Analyst

    SC-300 Certified

    ✓ Verified
  • ★★★★★

    “From AZ-900 to AZ-305 in 6 months. Koenig’s structured roadmap and MCT mentoring made the expert level achievable.”

    Priya S.

    Priya S.

    Cloud Solutions Architect

    AZ-305 Expert

    ✓ Verified
  • ★★★★★

    “As an L&D head I’ve used 5 training vendors. Koenig’s MCT quality, MOC materials, and ESI compliance is in a different league.”

    James T.

    James T.

    Head of L&D, UK Enterprise

    100+ Learners Trained

    ✓ Verified
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    Aisha N.

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    Security Analyst

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    David L.

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    AI Engineer

    AI-102 Certified

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    Mei W.

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    Data Platform Engineer

    DP-600 Certified

    ✓ Verified
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    “Our whole DevOps team got AZ-400 certified through Koenig’s corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training

    ✓ Verified
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    “AI-102 was daunting but the trainer broke it down perfectly. Real Azure OpenAI labs made the difference. Highly recommend.”

    David L.

    David L.

    AI Engineer

    AI-102 Certified

    ✓ Verified
  • ★★★★★

    “DP-600 Fabric certification done in 3 weeks of part-time study. The customised schedule around my timezone was a lifesaver.”

    Mei W.

    Mei W.

    Data Platform Engineer

    DP-600 Certified

    ✓ Verified
  • ★★★★★

    “Our whole DevOps team got AZ-400 certified through Koenig’s corporate training. Smooth logistics and top-tier MCTs throughout.”

    Carlos R.

    Carlos R.

    Engineering Manager

    AZ-400 Team Training

    ✓ Verified

Got Questions? We've Got Answers.

Everything you need to know about Data Engineering for AI certification training with Koenig Solutions.

Data Engineering for AI is the discipline of designing, building, and maintaining data systems—such as pipelines, architecture, and quality processes—specifically to support AI and machine learning models. It extends traditional data engineering by incorporating feature engineering, vector databases, retrieval augmented generation (RAG), and AI-specific governance. Core components include ingestion, open-format storage, feature stores, and RAG infrastructure.
Data Engineering for AI training is designed for data engineers, analytics engineers, data architects, and ML engineers with intermediate-level experience. It serves professionals building AI-ready data infrastructure, especially those transitioning from traditional ETL to AI pipeline development. Roles focused on feature engineering, RAG, or MLOps benefit most from this training.
Learners should have intermediate proficiency in Python, SQL, and cloud platforms (AWS, Azure, or GCP), along with foundational knowledge of data pipelines and ETL workflows. Familiarity with Apache Spark and Databricks is recommended. Six months of hands-on data engineering experience is highly advised before enrolling.
The training prepares learners for the Databricks Certified Data Engineer Associate (DEA) certification, exam code DEA-211. It validates skills in data ingestion, transformation, Lakeflow Jobs, CI/CD, and governance on the Databricks Data + AI Platform. The exam covers ETL/ELT, pipeline orchestration, and data quality in a cloud environment.
The Databricks Certified Data Engineer Associate exam has 45 scored multiple-choice questions with a 90-minute time limit. The passing score is approximately 70%, and the certification is valid for 2 years. Recertification requires retaking the current version of the exam, which costs $200 USD.
The training runs for 32 to 40 hours, depending on the course, and is delivered in live online 1-on-1, public instructor-led, classroom, and Flexi self-paced formats. All live sessions are Guaranteed-to-Run (GTR), with flexible start dates. Labs are included in applicable courses for hands-on practice.
Still have questions?
Talk to a Data Engineering for AI certification advisor — free, no obligation.
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Training Professionals
Across 50+ Countries

From our headquarters in India to training centers across UAE, Iraq, Saudi Arabia, UK, USA, Singapore, Australia, and more — Koenig delivers Microsoft certification training in 50+ countries.

50+
Countries
500K+
Trained
33+
Years
95%
Pass Rate
Koenig training locations worldwide