A real time and hands-on course on Flink
Duration : 6 months Classes : 36 Days : Weekdays / Weekends
The New Standard for Real-Time Data Apache Flink is the cutting-edge framework engineered to handle true streaming data and stateful computations with unparalleled low latency and high throughput. Unlike micro-batch systems, Flink processes data event-by-event, making it the preferred choice for applications requiring immediate insights, complex event processing, fraud detection, and real-time machine learning. Our comprehensive Flink training is designed to introduce you to its unified programming model, enabling you to build fault-tolerant, stateful applications that deliver accurate results, even when processing massive, endless data streams.
Deep Dive into Stateful Stream Processing This intensive course emphasizes the unique power of Flink: managing state accurately at scale. You will gain hands-on expertise with the DataStream API, mastering windowing strategies (Tumbling, Sliding, Session) and applying sophisticated time semantics (event time vs. processing time) for precise results. Crucially, you will learn how Flink manages checkpoints and savepoints to ensure exactly-once semantics and reliable recovery from failures, a non-negotiable requirement for mission-critical applications in finance, telecommunications, and IoT. This mastery of state and time sets Flink apart and will elevate your data engineering capabilities.
Career Acceleration in Low-Latency Architectures Proficiency in Apache Flink is a specialized and highly valuable skill that opens doors to high-paying roles as a Streaming Data Engineer, Low-Latency Architect, or Real-Time Analytics Specialist. As organizations rapidly shift from batch-centric to real-time architectures, expertise in Flink's unified approach (handling both streams and batches) is in enormous demand. By completing this program, you will be equipped to design, implement, and deploy production-ready stream processing applications, positioning you at the forefront of the modern data landscape.
Target Audience:-
- Data Engineers
- Software Architects
- IoT and Sensor Data Specialists
- Experienced Data Developers (Spark/Kafka)
Learning Outcomes:-
- Understand Flink Architecture
- Master the DataStream API
- Apply Time and Windowing
- Manage State Reliably
- Process Real-Time Data
- Optimize and Deploy
Course Format:-
✔ The course shall be delivered through a combination of lectures, interactive discussions & case studies
✔ Participants are exposed to practical exercises and new-age projects, where they learn by doing
✔ Participants shall have access to online resources, including reading materials, videos & business simulations
✔ Students shall receive all the study material
✔ Guest speakers from the industry may be invited to share insights and experiences
✔ Regular assessments and quizzes will be conducted to reinforce learning
✔ This is a Classroom only training
✔ Corporates: We understand your specific needs and goals. Contact us for customizations to this training
Trainers:-
✔ Equipped with multidisciplinary backgrounds
✔ Experts from the field of Maths, Financial Markets, AIML, Data Science & Management
✔ Each with over 25+ years of International experience working in EU / US / Australia
✔ All our trainers are Highly Qualified and Certified, in their respective subject areas
This syllabus provides a structured, module-by-module breakdown of this comprehensive training program focused on participants overall performance, retention, and engagement, covering foundational theory, implementation, best industry practices and advanced techniques in the subject.
Module 1: Introduction to Apache Flink
✔ What is Apache Flink and why use it
✔ Flink vs Spark vs Kafka Streams
✔ Flink architecture: JobManager, TaskManager, parallelism
✔ Setting up Flink locally and on clusters (YARN, Kubernetes)
Module 2: Core Concepts & DataStream API
✔ Bounded vs unbounded streams
✔ Transformations: map, filter, flatMap, keyBy, reduce
✔ Working with time: event time, processing time, ingestion time
✔ Watermarks and windowing basics
Module 3: Windowing & State Management
✔ Tumbling, sliding, and session windows
✔ Aggregations over windows
✔ Keyed state and operator state
✔ State backends and checkpointing
Module 4: Table & SQL API
✔ Introduction to Flink Table API and SQL
✔ Creating tables from streams and files
✔ SQL queries on streaming data
✔ Integrating with Hive and catalogs
Module 5: Connectors & Integrations
✔ Source and sink connectors: Kafka, JDBC, filesystem, Elasticsearch
✔ Working with formats: JSON, Avro, Parquet, CSV
✔ Integrating Flink with external systems (Hive, HBase, Pulsar)
✔ Custom connectors and serialization
Module 6: Fault Tolerance & Performance Tuning
✔ Checkpointing, savepoints, and recovery
✔ Exactly-once vs at-least-once semantics
✔ Backpressure and latency optimization
✔ Monitoring with Flink Dashboard and metrics
Module 7: Capstone Project & Deployment
✔ Building an end-to-end Flink streaming pipeline
✔ Packaging and deploying Flink jobs
✔ CI/CD for Flink applications
✔ Interview prep and certification guidance
Student Reviews
Bhawana
Fabulous NLP + ML course
I have eleven plus years of experience taking training courses. I do not usually complete surveys.
Your instructor was excellent, the best I've experienced on a software subject, and I couldn't imagine him doing a better job of seamlessly walking students through a breadth of information for such complex subject like AI and ML. he did a fabulous job pacing everything and addressing student questions. I am very impressed.
Harish
Excellent ML course!
The course was well structured and easy to understand. Good pace of learning.
The institute believes to provide knowledge as well as guidance in detail to each & every student.
I completed my ML course from the institute. Their international exp does help a lot !
Thanks for the training sir.