MICRO DEGREE
Databricks Data Engineering Certification
Become a Certified Databricks Data Engineer in just 6 weeks
100% LIVE Interactive Classes
Become a Certified Databricks Data Engineer in just 6 weeks
100% LIVE Interactive Classes
Reserve your spot today!
Basic Info
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Application closes on:14 Apr 2026
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What is in it for you?
Shape the future with Databricks Certification
100% Live Classes
Instructor-led Live Sessions
Attend 4 weeks of instructor led live classes from the top 1% industry experts
Projects & Case Studies
Projects & Case Studies
Gain hands-on experience with projects and real-world case studies for impactful learning.
Verified Certificate
Verified Certificate
Earn a industry recognized certificate and kick start your career
Session Recordings
Session Recordings
Revisit older chapters anytime with recorded sessions
Flexible Schedule
Flexible Schedule
Choose live classes from different cohorts that fit your availability.
Hands-on Classes
Hands-on Classes
Hands-on classes to enhance your learning experience
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Reserve your spot today!
Basic Info
Select Offers
Application closes on:14 Apr 2026
Get instant access of pre-course material!
Talk to Us
We’re here to help! Reach us at:
Learn from Top 1%
Sr. Managers, VPs, CXOs, Directors & Founders from companies shaping the future.
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Available in 4 monthly installments at $134/month
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Curriculum
A Curriculum designed for your success
Duration: 6 weeks
Max Batch Size: 15 persons
Live Sessions Schedule 
Sat - Sun (Weekends Only) 
Timing 7:00 AM - 9:00 AM / 8:30 AM - 10:30 AM / 11:00 AM - 1:00 PM / 5:00 PM - 7:00 PM / 7:30 PM - 9:30 PM EST
- What is Data Engineering?
- Understanding Big Data Problems
- Overview of Data Architecture (Batch vs Streaming)
- Role of Azure Databricks in Modern Data Platforms
- Visualize a Modern Data Engineering Workflow
- Identify Components: Storage, Compute, Orchestration, Reporting
- Discussion: Traditional vs Cloud-Based Data Systems
- Azure Overview: Regions, Subscriptions, and Resource Groups
- Azure Portal Tour
- Key Azure Services for Data Engineering (Azure Storage, SQL Database, Synapse Analytics, Data Factory)
- Create a Free Azure Account
- Create Resource Group and Storage Account
- Upload Files to Blob Storage
- Explore Data Lake Gen2 Hierarchy
- What is Databricks?
- Databricks on Azure Architecture
- Workspace Components (Clusters, Notebooks, Jobs, Data)
- Databricks Runtime Versions
- Create Databricks Workspace in Azure Portal
- Explore the UI and Basic Configuration
- Run Your First Notebook ('Hello Databricks')
- Cluster Types (Standard, Single Node, Serverless Compute)
- Serverless SQL Warehouses
- Unity Catalog Volumes for File Access
- DBFS Overview (Legacy Context)
- Databricks Utilities (dbutils): Files, Widgets, Secrets
- Create a Serverless Cluster
- Create and Access Unity Catalog Volumes
- Upload and Read Files via Volumes
- Compare Serverless vs Classic Cluster Startup and Performance
- Introduction to Apache Spark Ecosystem
- Spark Components (Driver, Executors, Cluster Manager)
- SparkSession and Lazy Evaluation
- RDDs vs DataFrames
- Create SparkSession
- Explore RDD and DataFrame Creation
- Perform Basic Transformations (select, filter, count)
- Examine Execution Plans with explain()
- Schema and Data Types in PySpark
- Data Transformations (Select, Filter, GroupBy, Join)
- Data Cleaning (Handling Nulls, Dates, Duplicates)
- Load Data from Azure Blob to PySpark DataFrame
- Apply Real Transformations (Filtering, Aggregation, Joins)
- Save Results as Parquet and CSV
- User Defined Functions (UDFs)
- Window Functions and Ranking
- Liquid Clustering (Replacing Partitioning & Bucketing)
- Predictive Optimization Overview
- Create UDFs for Custom Logic
- Implement Window Functions (Top N, Running Totals)
- Apply Liquid Clustering to a Delta Table
- Compare Query Performance: Liquid Clustering vs Old-Style Partitioning
- Enable Predictive Optimization and Observe Automated Maintenance
- Using SQL in Databricks
- Temporary and Global Views
- SQL Joins, Aggregations, and Built-In Functions
- Integrating SQL and PySpark Workflows
- Register Views and Run SQL Queries
- Create Analytical Queries using GROUP BY, HAVING, ORDER BY
- Combine SQL Queries with PySpark DataFrames
- What is Delta Lake and Why It’s Important
- Delta Lake Architecture and ACID Transactions
- Schema Enforcement and Evolution
- Delta Time Travel
- Convert Parquet Table to Delta Table
- Perform UPSERTs, DELETEs, MERGEs
- Use Time Travel to View Older Versions
- ETL vs ELT Explained
- Lakeflow Declarative Pipelines (formerly Delta Live Tables)
- Medallion Architecture (Bronze / Silver / Gold)
- Data Quality Expectations and Rules
- Batch and Streaming Ingestion with Lakeflow
- Databricks Jobs for Orchestration
- Error Handling and Logging
- Build a Medallion Pipeline using Lakeflow Declarative Pipelines
- Define Data Quality Expectations
- Ingest Raw Data into Bronze, Transform through Silver and Gold
- Orchestrate the Pipeline with a Databricks Job
- Databricks SQL Dashboards (New Dashboard Experience)
- Genie: AI-Powered Natural Language Data Exploration
- AI/BI Dashboards
- Notebook Charts and Graphs
- Integrating Databricks with Power BI
- Publishing Delta Tables for BI Reporting
- Build a Databricks SQL Dashboard
- Use Genie to Query Data with Natural Language
- Connect Delta Tables to Power BI
- Monitoring Jobs with Spark UI
- Serverless Compute Cost Monitoring
- Caching and Adaptive Query Execution
- Liquid Clustering Tuning
- Predictive Optimization: Automated Maintenance
- Photon Engine Overview
- Cost Optimization: Serverless vs Classic Compute
- Track Job Performance using Spark UI
- Compare Photon vs Non-Photon Performance
- Analyze Cost Differences between Serverless and Classic Clusters
- Review Predictive Optimization Activity Logs
- Unity Catalog: Architecture and Setup (Metastore, Catalog, Schema, Table)
- Unity Catalog Access Control (Grants, Privileges, Row/Column-Level Security)
- Data Lineage and Auditing
- Data Discovery and Tagging
- Secure Storage Connections (External Locations, Storage Credentials)
- Version Control and Git Integration
- Key Vault for Secrets Management
- Set Up a Unity Catalog Metastore
- Create Catalogs and Schemas
- Configure Table-Level and Column-Level Permissions
- Explore Automated Lineage Tracking
- Integrate Databricks with GitHub
- Scenario: Retail Company End-to-End Data Engineering Solution
- Ingest Raw CSV Data from Azure Blob Storage
- Transform Data using PySpark and SQL
- Store Processed Data in Delta Format
- Query the Results with Spark SQL
- Visualize Output in Power BI
- Deliverables: ETL Notebooks, Delta Lake Tables, Documentation & Power BI Dashboard
Mentors
20+ Years, Sr. Engineering Manager, Amazon
15+ Years, Data Strategy Director, Ex-Citibank, Ex-JP Morgan.
Course Includes
LIVE Interactive Sessions
Quizzes, Assignments & Projects
Study Materials & Session Recordings
Certificate
Course Includes
LIVE Interactive Sessions
Quizzes, Assignments & Projects
Study Materials & Session Recordings
Certificate
Course Pre-requisites
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Basic Python- No prior experience needed
Outcomes
- Understand the role of data engineering in modern data platforms and the key components of a cloud-based data architecture.
- Leverage Azure cloud services like Blob Storage, SQL Database, and Synapse Analytics to build a robust data infrastructure.
- Harness the power of Apache Spark and PySpark to perform advanced data transformations and analytics.
- Implement a Medallion data architecture using Databricks' Lakeflow declarative pipelines for efficient data ingestion and ETL.
- Visualize data insights using Databricks SQL Dashboards and integrate with Power BI for comprehensive reporting.
- Ensure data security, governance, and optimization through Unity Catalog, Photon Engine, and Predictive Optimization.
Real-World Case Studies
Learn through real-world case studies
Retail
Retail Chain's Hybrid Cloud Migration
Retail chain modernizing IT while keeping on-premises systems. Create Azure hybrid architecture for gradual migration, ensuring security and management consistency. Enable cloud-native development while maintaining legacy integration.
Finance
Global Financial Services Company: Modernizing Legacy Systems
MultiNational Bank updating core system. Implement Azure DevOps for microservices transition. Accelerate feature delivery, enhance security, and reduce technical debt.
Finance
Financial Services Data Security and Compliance
Multinational bank moving to cloud. Develop secure, compliant AWS infrastructure for sensitive data. Ensure regulatory compliance while enabling cloud migration.
for successfully completing the 'Databricks Data Engineering Certification' course conducted from 02 Mar 2026 to 13 Apr 2026
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for successfully completing the 'Databricks Data Engineering Certification' course conducted from 02 Mar 2026 to 13 Apr 2026
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Looking for help? Here are our most frequently asked questions
What is a EdYoda Micro Degree?
EdYoda Micro Degree is an online, Live classroom based short-term course, where you get Live Sessions conducted by industry experts. It is designed to help you acquire practical & job-relevant skills quickly.
How do I register for the micro degree?
To register, visit the micro degree details page and fill up the registration form and make the payment to reserve your seat before the application closing date.
What happens after I register and pay?
After successful registration and payment, you will receive a confirmation email with instructions on how to access the online micro degree classes
Are there any pre-requisites?
All you need is a PC or Laptop to attend the online live classes and your commitment of 4 weeks. Apart from that there are no prerequisite for the Micro Degree.
What if I miss a live session?
We've got you covered! The session recording will be added automatically on the classroom platform after the session is ended.
Will I get a certificate after completion?
Yes. After successful completion of curriculum you will be provided a digital certificate which you can download and share with others.
What is a EdYoda Micro Degree?
EdYoda Micro Degree is an online, Live classroom based short-term course, where you get Live Sessions conducted by industry experts. It is designed to help you acquire practical & job-relevant skills quickly.
How do I register for the micro degree?
To register, visit the micro degree details page and fill up the registration form and make the payment to reserve your seat before the application closing date.
What happens after I register and pay?
After successful registration and payment, you will receive a confirmation email with instructions on how to access the online micro degree classes
Are there any pre-requisites?
All you need is a PC or Laptop to attend the online live classes and your commitment of 4 weeks. Apart from that there are no prerequisite for the Micro Degree.
What if I miss a live session?
We've got you covered! The session recording will be added automatically on the classroom platform after the session is ended.
Will I get a certificate after completion?
Yes. After successful completion of curriculum you will be provided a digital certificate which you can download and share with others.
General FAQs
Everything you need to know
