Live Online Apache Kafka Course for Data Science

Apache Kafka for Data Science – Live Course Module

Total Duration: 2 Weeks (15 Hours)

Day 1: Introduction & Setup (2 Hours)

1. Role of Real-Time Data in Data Science (10 min)

2. Kafka Basics: Producers, Consumers, Brokers, Topics (30 min)

3. Kafka Architecture Overview (20 min)

4. Hands-on: Install Kafka & Run First Producer/Consumer (60 min)

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Day 2: Producers & Consumers (2 Hours)

1. Producer API & Partitioning Strategies (30 min)

2. Consumer API, Groups & Offsets (30 min)

3. Hands-on: Write Python Producer & Consumer (60 min)

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Day 3: Data Pipelines with Kafka (2 Hours)

1. Kafka Connect for ETL & Database Integration (30 min)

2. Integration with Spark Streaming / Flink (30 min)

3. Hands-on: Stream Data into Kafka & Process with Spark (60 min)

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Day 4: Kafka Streams API (2 Hours)

1. Kafka Streams Concepts: KStreams, KTables, Windowing (30 min)

2. Real-Time Processing for ML (30 min)

3. Hands-on: Build a Streaming App (e.g., Word Count / Anomaly Detection) (60 min)

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Day 5: Capstone Project & Wrap-Up (2 Hours)

1. Build a Mini Real-Time Data Science Pipeline (90 min)

   • Ingest live data (stock prices / IoT / social media)

   • Process with Kafka Streams/Spark

   • Apply ML model (sentiment / anomaly detection)

   • Visualize results

2. Q&A + Best Practices (30 min)

✅ Delivery Mode: Live sessions with hands-on labs
✅ Outcome: Build end-to-end real-time data pipelines using Kafka for data science