Real-Time Data with Kafka & Streaming
Event streaming fundamentals, producers/consumers, topics, schema handling and stream processing patterns.
- ✓ Instructor-led live sessions, online or in Bengaluru
- ✓ Hands-on labs in every module
- ✓ Capstone project with trainer review
- ✓ Curriculum customisable for corporate teams
- ✓ Certificate of completion
Next batch: Wed, 13 Jan 2027 · 24 hours · 3 days
Data EngineeringReal-Time Data with Kafka & Streaming
Duration: 24 hours · 3 days
Next batch: Wed, 13 Jan 2027
Format: Online live · Bengaluru classroom
Modules: 7 · Topics: 34
Level: Intermediate
Fee: ₹10,999
Trusted by leading experts
Upcoming batches
Open batches for individuals; corporate batches on your dates.
| Programme | Starts | Mode | Schedule | Duration | |
|---|---|---|---|---|---|
| Real-Time Data with Kafka & Streaming | Wed, 13 Jan 2027 | Bengaluru classroom | Weekday | 3 days | Enquire |
| Real-Time Data with Kafka & Streaming | Sat, 20 Mar 2027 | Online live | Weekend (Sat) | 4 Saturdays | Enquire |
Soaring demand, and where it takes you
Real-time use cases such as fraud detection, personalisation and monitoring continue to grow, increasing demand for streaming skills.
Become an expert
Roles this programme prepares you for:
Become a Streaming Data Engineer
Builds real-time ingestion and processing.
- Explain Kafka's architecture and guarantees
- Write producers and consumers
- Use consumer groups and manage offsets
About the course
Real-time data with Apache Kafka: topics and partitions, producers and consumers, consumer groups, schemas, Kafka Connect and stream processing patterns, with operational basics.
Event streaming fundamentals, producers/consumers, topics, schema handling and stream processing patterns.
Why should I attend?
Data engineers
Backend developers
Platform engineers
Architects designing event-driven systems
Prerequisites
Programming in Python or Java; basic distributed-systems concepts
Level
Intermediate
Delivery modes, duration and fee
Online live
Instructor-led virtual classroom; weekday (full-day) or weekend (Saturday) batches
Bengaluru classroom
In-person batches at our Bengaluru training venue
On-site at your office
Private corporate batch anywhere in India, scheduled around your teams
Blended
Live sessions plus guided self-paced labs and mentor check-ins
Duration: 24 hours · 3 days
Course fee (open batch): ₹10,999
Corporate / team batches: per-participant or flat batch pricing on request, based on group size, format and customisation.
What will you learn
- Explain Kafka's architecture and guarantees
- Write producers and consumers
- Use consumer groups and manage offsets
- Manage schemas with a schema registry
- Integrate systems with Kafka Connect
- Process streams with Spark Structured Streaming
Skills you will gain
Kafka core
Development
Processing
Tools and platforms covered
Apache KafkaKafka Connect
Apache Spark
Python
DockerCourse curriculum
M01 Streaming fundamentals
- Events vs batches
- Kafka architecture
- Delivery guarantees
- Topics and partitions
- Replication
🧪 Hands-on: Run a local cluster
M02 Producers and consumers
- Producing messages
- Consumer groups
- Offsets
- Idempotent producers
- Rebalancing
🧪 Hands-on: Build a producer and consumer
M03 Schemas
- Avro and JSON Schema
- Schema registry
- Compatibility
- Schema evolution rules
- Serialisation choices
🧪 Hands-on: Evolve a schema safely
M04 Kafka Connect
- Source and sink connectors
- Configuration
- Error handling
- Single message transforms
- Dead-letter queues
🧪 Hands-on: Stream a database table into Kafka
M05 Stream processing
- Spark Structured Streaming
- Windows and watermarks
- Joins
- Kafka Streams and Flink overview
- State stores
🧪 Hands-on: Compute real-time aggregates
M06 Operations
- Monitoring
- Retention and compaction
- Security basics
- Consumer lag
- ACLs and TLS
🧪 Hands-on: Monitor a cluster
M07 Capstone: real-time pipeline
- Event design
- Ingest
- Process
- Serve and monitor
🧪 Hands-on: Build a streaming pipeline from producer to dashboard
Hands-on projects
Real-time pipeline
Database changes streamed through Kafka into real-time aggregates.
Why train with us
Built around your stack
Labs and examples adapted to the tools, cloud and data your team actually uses.
Practice-first
Every module ends in a lab, and the course ends with a reviewed capstone.
Practitioner-led
Delivered by Karthick Selvam and vetted specialist trainers from our network.
Visible progress
Attendance, lab completion and assessment results shared with your L&D team.
Certificate of completion
Participants who complete the labs and capstone receive a Learning Dots certificate of completion for Real-Time Data with Kafka & Streaming. [confirm certificate wording / sample image]
Learner reviews
“[Verified learner review for this course]”
“[Verified learner review for this course]”
Meet your trainer
Karthick Selvam
Founder · Data Engineering Corporate Trainer, Bengaluru
[Trainer bio, experience and areas of expertise]
Frequently asked questions
Do you cover managed Kafka services?
Concepts transfer directly; we discuss managed options on major clouds.
Can the curriculum be customised for our team?
Yes. Modules, depth, duration and labs can be tailored to your stack and goals.
What delivery formats are available?
Online live instructor-led sessions, Bengaluru classroom, or on-site at your office.
How do we enquire or book?
Use the enquiry form on this page or the Enquire button next to any batch.
What does it cost?
The open-batch fee is ₹10,999 per participant plus GST. Corporate batches are priced on group size, format and customisation.
How long is the course?
24 hours · 3 days. Corporate batches can be split into half-day sessions.
A closer look
About this course
Real-time data with Apache Kafka: topics and partitions, producers and consumers, consumer groups, schemas, Kafka Connect and stream processing patterns, with operational basics.
What is Real-Time Data with Kafka & Streaming?
Event streaming fundamentals, producers/consumers, topics, schema handling and stream processing patterns.
Who this course is for
Data engineers, Backend developers, Platform engineers, Architects designing event-driven systems.
What you will be able to do
Explain Kafka's architecture and guarantees. Write producers and consumers. Use consumer groups and manage offsets. Manage schemas with a schema registry. Integrate systems with Kafka Connect. Process streams with Spark Structured Streaming.
Career paths
Roles this course supports include Streaming Data Engineer, Event-Driven Developer, Kafka Administrator. Real-time use cases such as fraud detection, personalisation and monitoring continue to grow, increasing demand for streaming skills.
Related courses
Data Engineering Foundations
Pipelines, warehouses, lakes and the modern data stack explained hands-on, from first principles to a working end-to-end pipeline.
Data EngineeringApache Spark & PySpark for Data Engineers
Distributed processing with DataFrames, Spark SQL, partitioning, joins and performance tuning on realistic datasets.
Databricks & Lakehouse Engineering
Delta Lake, medallion architecture, workflows, Unity Catalog concepts and production-grade lakehouse patterns.
Data Engineering guides
What Is Data Engineering? A Plain-English Guide
Data engineering is the discipline of collecting, moving, transforming and storing data so analysts, applications and AI can use it reliably.
ETL vs ELT: What Is the Difference?
Two patterns for moving and transforming data, differing in where the transformation happens.
Data Lake vs Data Warehouse vs Lakehouse
Three architectures for storing analytical data.
What Is Apache Spark and When Should You Use It?
Apache Spark is an open-source engine for processing large datasets in parallel across a cluster.