Databricks Spark Certification Training in Gurgaon
Master Databricks Spark Cloud and get prepared for Databricks official certifications with our role based courses tailored to your specific needs
- Enroll for Architecture, Data Engineering, Developer, Analyst, ML/ AI, Operations, and Governance Certifications
- Experience blended learning through interactive offline and online sessions.
- Job Assured Course
- Course Duration - 2 months
- Get Trained from Industry Experts
Train using realtime course materials using online portals & trainer experience to get a personalized teaching experience.
Active interaction in sessions guided by leading professionals from the industry
Gain professionals insights through leading industry experts across domains
Enhance your career with 42+ in-demand skills and 20+ services
Databricks Spark Certification Overview
This Databricks Spark live-learning courses cover deep into designing, developing, deploying, and managing scalable solutions and infrastructure across Databricks platforms, equipping you for success in today’s fast-evolving technology landscape
- Benefit from ongoing access to all self-paced videos and archived session recordings
- Success Aimers supports you in gaining visibility among leading employers
- Get prepared for 5+ Databricks official certifications with our role based courses tailored to your specific needs
- Engage with real-world capstone projects
- Engage in live virtual classes led by industry experts, complemented by hands-on projects
- Job interview rehearsal sessions
Assesses understanding of Apache Spark architecture and components, plus proficiency in using the Spark DataFrame API for basic data manipulation tasks like selecting/renaming/manipulating columns, filtering/dropping/sorting/aggregating rows, handling missing data, combining/reading/writing/partitioning DataFrames with schemas, and working with UDFs/Spark SQL functions. Evaluates knowledge of Spark fundamentals including execution/deployment modes, execution hierarchy, fault tolerance, garbage collection, lazy evaluation, shuffling, Actions/broadcasting, Structured Streaming, Spark Connect, and common troubleshooting/tuning techniques. Tests ability to apply these concepts within Spark sessions using Python. Successful candidates demonstrate competence in completing basic Spark DataFrame tasks with Python
What is Databricks Spark Developer?
Databricks Certified Spark Developer are essential for driving Data & AI innovation in ETL development and testing. They manage the full Data lifecycle—deploying ETL apps, building and maintaining Data pipelines for Data applications and ETL workflows, and automating Data development and testing processes. By streamlining ETL workflows and resolving challenges in ETL deployment on cloud, and maintenance, they help organizations deliver reliable, high-performance applications faster and more efficiently.
The role of Databricks Spark Developer ?
Databricks Certified Spark Developer in ETL development and testing oversees the end-to-end lifecycle of ETL(Spark) applications, from development to deployment and Spark Jobs performance optimization. Key responsibilities include:
Exploring Emerging Technologies: Leveraging Cloud technologies, Cloud networking, and security techniques to enhance efficiency and streamline ETL (Spark) workflows.
Scalable Data, AI & ETL Development: Designing and implementing ETL (Data) applications that address critical business needs.
Seamless Deployment: Coordinating Data deployment with infrastructure management for smooth delivery.
ETL Workflow Optimization: Creating, analyzing, and refining ETL automation scripts and Spark deployment workflows to maximize productivity.
For professionals aspiring to excel in this field, the Success Aimers Databricks Spark Developer Course provides hands-on training to master these skills. The program equips you to confidently manage ETL deployment lifecycles, Data pipelines, automation, and ETL deployment processes, positioning you as a high-impact Databricks Certified Spark Developer in ETL development and testing.”**
Who should take this Databricks Certified Spark Developer course?
The Databricks Certified Spark Developer Course is tailored for professionals aiming to accelerate their careers in Cloud, data, and technology-driven sectors. It is particularly valuable for roles including:
Data Cloud Team Leaders
PySpark Developers
Data Cloud Engineers and IT Managers
Data Cloud & Infrastructure Engineers
Data Cloud Researchers and Data Engineers
This program equips participants with the skills to lead Data & AI initiatives, implement advanced ETL deployment workflows, and drive innovation in Data development and testing.
What are the prerequisites of Databricks Certified Spark Developer Course?
Prerequisites for the Databricks Certified Spark Developer Certification Course”
To ensure a seamless learning experience, candidates are expected to have:
Educational Background: An undergraduate degree or high school diploma in a relevant field.
Technical Foundation: Knowledge of IT, Data development, or data science fundamentals.
Programming Skills: Basic proficiency in languages such as Python or Scala.
Cloud Familiarity: Experience with cloud platforms like AWS or Microsoft Azure.
Meeting these prerequisites enables learners to effectively grasp advanced Cloud concepts, including Spark tool, ETL Pipeline workflows, Spark Job deployment, and automation throughout the course.
Kind of Job Placement/Offers after Databricks Certification Course?
- Databricks Certified Spark Developer
- Databricks Spark Engineer
- Databricks Cloud Solutions Architect
- Databricks Spark Developer
- Databricks Cloud Engineer / Databricks Cloud Architect
- Databricks Cloud Infrastructure Engineer
- Databricks Cloud Deployment Engineer
| Training Options | Weekdays (Mon-Fri) | Weekends (Sat-Sun) | Fast Track |
|---|---|---|---|
| Duration of Course | 2 months | 3 months | 15 days |
| Hours / day | 1-2 hours | 2-3 hours | 5 hours |
| Mode of Training | Offline / Online | Offline / Online | Offline / Online |
Databricks Spark Course Overview
This Databricks Certified Spark Developer training enhances your career after choosing the relevant certification path based on the roles. You can practice with hands-on labs and capstone projects and gain proficiency with Databricks tools. After completion of the course, you can leverage Job assistance services and enhance career prospects.
Development
Databricks Certified Spark Developer Associate Course
Apache Spark Architecture: Distributed Processing
- Distributed Processing: How Apache Spark Runs on a Cluster
- Azure Databricks: How to Create a Cluster
- Databricks Community Edition: How to Create a Cluster
Apache Spark Architecture: Distributed Data
- Distributed Data: The DataFrame
- How To Define the Structure of a DataFrame
DataFrame Transformations
- Selecting Columns
- Renaming Columns
- Change Columns data type
- How to access column
- Adding Columns to a DataFrame
- Removing Columns from a DataFrame
- Basics Arithmetic with DataFrame
- Apache Spark Architecture: DataFrame Immutability
- How To Filter A DataFrame
- Apache Spark Architecture: Narrow Transformations
- Dropping Rows
- How to Drop rows and columns
- Handling Null Values Part I - Null Functions
- Handling Null Values Part II – DataFrameNaFunctions
- Sort and Order Rows - Sort & OrderBy
- Create Group of Rows: GroupBy
- DataFrame Statistics
- Joining Data Frames - Inner Join
- Joining Data Frames - Right Outer Join
- Joining Data Frames - Left Outer Join
- Appending Rows to a DataFrame – Union
- Caching a DataFrame
- DataFrameWriter Part I
- DataFrameWriter Part II – Partition By
- User Defined Functions
Apache Spark Architecture: Execution
- Query Planning
- Execution Hierarchy
- Portioning a DataFrame
- Adaptive Query Execution - An Introduction
--------------------Spark Streaming - Stream Processing in Lakehouse-------------------
Getting Started with Spark Streaming
- Batch processing to Stream processing
- Your Spark application - Applying Best Practice
- Your first streaming application - Implementing Stream
- Stream Processing Model in Spark
- Create Another Streaming Application
- Stream Triggers
- Incremental Batch Processing
- Streaming Sources and Sinks
- Creating Chain of Streams
Kafka for Data Engineers
- An Introduction to Kafka
- Creating Kafka Cluster in Cloud
- Kafka Core Concepts
- Producing Data to Kafka Topic
- Consuming Data from Kafka Topic
- Working with Kafka Topic Data
- How to Implement Idempotence
- Working with Kafka Sink
Streaming Aggregates and State Management
- Streaming Aggregates and State Store
- Incremental Aggregates and Update Mode
- Spark Streaming Output Modes
- Stateful Vs Stateless Aggregation
- Implementing Stateless Streaming Aggregation
- Timebound Stateful Tumbling Window Aggregation
- Watermarking and State Store Cleanup
- Sliding Window Aggregates
Working with Databricks Platform
- Introduction to Databricks
- Creating Azure Free Account
- Azure Portal Overview
- Creating Azure Databricks Service
- Introduction to Azure Databricks Workspace
- Azure Databricks Architecture
- Creating Azure Databricks Cluster
- Introduction to Databricks Notebooks
- Notebooks Magic Commands and Utilities
- Databricks Notebooks Utilities
- Introduction to Databricks Unity Catalog
- Introduction to Databricks Workflow Jobs
- Introduction to Databricks Rest API
- Introduction to Databricks CLI
Capstone Project – Implementing Real-Time Project in Lakehouse
- Introduction to Delta aProject Scope and Backgroundive Tables
- Taking out the operational requirement
- Storage Design
- Implement Data Security
- Implement Resource Policies
- Decouple Data Ingestion
- Design Bronze Layer
- Design Silver and Gold Layer
- Setup your source control
- Setup your environment
- Create a development workspace
- Create and Configure Storage Layer
- Create Unity Catalog Metastore
- Create Catalog and External Locations
- Start Coding
- Test your code
- Load historical data
- Ingest into bronze layer
- Process the silver layer
- Handling multiple updates
- Implementing Gold Layer
- Creating a run script
- Preparing for Integration testing
- Creating Test Data Producer
- Creating Integration Test for Batch mode
- Creating Integration Test for Stream mode
- Implementing CI CD Pipeline
- Develop Build Pipeline
- Develop Release Pipeline
- Creating Databricks CLI Script
--------------------Master Azure Databricks---------------------------
Working in Databricks Workspace
- How to create Spark Cluster
- Working with Databricks Notebook
- Notebook Magic Commands
- Databricks Utilities Package
Working with Databricks File Systems (DBFS)
- Introduction to DBFS
- Working with DBFS Root
- Mounting ADLS to DBFS
- Working with Unity Catalog
Working with Unity Catalog
- Introduction to Unity Catalog
- Setup Unity Catalog
- Unity Catalog User Provisioning
- Working with Securable Objects
Working with Delta Lake and Delta Tables
- Introduction to Delta Lake
- Creating Delta Table
- Sharing data for External Delta Table
- Reading Delta Table
- Delta Table Operations
- Delta Table Time Travel
- Convert Parquet to Delta
- Delta Table Schema Validation
- Delta Table Schema Evolution
- Look Inside Delta Table
- Delta Table Utilities and Optimization
Working with Databricks Incremental Ingestion Tools
- Architecture and Need for Incremental Ingestion
- Using Copy Into with Manual Schema Evolution
- Using Copy Into with Automatic Schema Evolution
- Streaming Ingestion with Manual Schema Evolution
- Streaming Ingestion with Automatic Schema Evolution
- Introduction to Databricks Autoloader
- Autoloader with Automatic Schema Evolution
Working with Databricks Delta Live Tables (DLT)
- Introduction to Databricks DLT
- Understand DLT Use Case Scenario
- Setup DLT Scenario Dataset
- Creating DLT Workload in SQL
- Creating DLT Pipeline for your Workload
- Creating DLT Workload in Python
Working with Databricks Project and Automation Features
- Introduction to Databricks DLT
- Understand DLT Use Case Scenario
Delta Lakeflow Declarative Pipeline (DLT) Overview
- Working with Databricks Repos
- Working with Databricks Workflows
- Working with Databricks Rest API
- Working with Databricks CLI
Capstone Project
- Introduction to Delta Project Scope and Backgroundive Tables
- Taking out the operational requirement
- Storage Design
- Implement Data Security
- Implement Resource Policies
- Decouple Data Ingestion
- Design Bronze Layer
- Design Silver and Gold Layer
- Setup your source control
- Setup your environment
- Create a development workspace
- Create and Configure Storage Layer
- Create Unity Catalog Metastore
- Create Catalog and External Locations
- Start Coding
- Test your code
- Load historical data
- Ingest into bronze layer
- Process the silver layer
- Handling multiple updates
- Implementing Gold Layer
- Creating a run script
- Preparing for Integration testing
- Creating Test Data Producer
- Creating Integration Test for Batch mode
- Creating Integration Test for Stream mode
- Implementing CI CD Pipeline
- Develop Build Pipeline
- Develop Release Pipeline
- Creating Databricks CLI Script
Hours of content
Live Sessions
Software Tools
After completion of this training program you will be able to launch your carrer in the world of AI being certified as Databricks Certified Spark Developer Associate course.
With the Databricks Certified Spark Developer Associate course in-hand you can boost your profile on Linked, Meta, Twitter & other platform to boost your visibility
- Get your certificate upon successful completion of the course.
- Certificates for each course
- Azure BLOB Storage
- AWS Polly
- Azure Databricks
- Azure SQL Server
- Azure Functions
- Azure App Services
- DBFS
- Azure Document DB
- Azure Fabric
- Azure Kubernetes Service (AKS)
- Azure Container Registry (ACR)
- Databricks Spark
- Delta Lake
- Azure Moniter
35% - 50%
Designed to provide guidance on current interview practices, personality development, soft skills enhancement, and HR-related questions
Receive expert assistance from our placement team to craft your resume and optimize your Job Profile. Learn effective strategies to capture the attention of HR professionals and maximize your chances of getting shortlisted.
Engage in mock interview sessions led by our industry experts to receive continuous, detailed feedback along with a customized improvement plan. Our dedicated support will help refine your skills until your desired job in the industry.
Join interactive sessions with industry professionals to understand the key skills companies seek. Practice solving interview question worksheets designed to improve your readiness and boost your chances of success in interviews
Build meaningful relationships with key decision-makers and open doors to exciting job prospects in Product and Service based partner
Your path to job placement starts immediately after you finish the course with guaranteed interview calls
Why should you choose to pursue a Databricks Certified Spark Developer Associate Course with Success Aimers?
Success Aimers teaching strategy follow a methodology where in we believe in realtime job scenarios that covers industry use-cases & this will help in building the carrer in the field of Databricks & also delivers training with help of leading industry experts that helps students to confidently answers questions confidently & excel projects as well while working in a real-world
What is the time frame to become competent as a Databricks Certified Spark Developer Associate?
To become a successful Databricks Certified Spark Developer required 1-2 years of consistent learning with dedicated 3-4 hours on daily basis.
But with Success Aimers with the help of leading industry experts & specialized trainers you able to achieve that degree of mastery in 6 months or one year or so and it’s because our curriculum & labs we had formed with hands-on projects.
Will skipping a session prevent me from completing the course?
Missing a live session doesn’t impact your training because we have the live recorded session that’s students can refer later.
What industries lead in Databricks implementation?
- Manufacturing
- Financial Services
- Healthcare
- E-commerce
- Telecommunications
- BFSI (Banking, Finance & Insurance)
- “Travel Industry
Does Success Aimers offer corporate training solutions?
At Success Aimers, we have tied up with 500 + Corporate Partners to support their talent development through online training. Our corporate training programme delivers training based on industry use-cases & focused on ever-evolving tech space.
How is the Success Aimers Databricks Certified Spark Developer Associate Course reviewed by learners?
Our Databricks Certified Spark Developer Associate Course features a well-designed curriculum frameworks focused on delivering training based on industry needs & aligned on ever-changing evolving needs of today’s workforce due to Cloud Computing (Databricks). Also our training curriculum has been reviewed by alumi & praises the through content & real along practical use-cases that we covered during the training. Our program helps working professionals to upgrade their skills & help them grow further in their roles…
Can I attend a demo session before I enroll?
Yes, we offer one-to-one discussion before the training and also schedule one demo session to have a gist of trainer teaching style & also the students have questions around training programme placements & job growth after training completion.
What batch size do you consider for the course?
On an average we keep 5-10 students in a batch to have a interactive session & this way trainer can focus on each individual instead of having a large group
Do you offer learning content as part of the program?
Students are provided with training content wherein the trainer share the Code Snippets, PPT Materials along with recordings of all the batches
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