What You’ll Learn: Real-Time AI Fundamentals
You’ll go from understanding batch processing to architecting and implementing systems that process and learn from data as it arrives.
Apache Kafka
Set up Kafka clusters, produce/consume events, and manage topics and partitions.
Spark Streaming
Process real-time data streams with Spark, including windowing and stateful operations.
Online Learning
Implement incremental model updates and online learning algorithms.
Real-Time Model Serving
Deploy models to serve predictions on live data streams with low latency.
Who Is This Course For?
Ideal for experienced ML engineers and data engineers ready to build real-time AI systems.
- ML engineers wanting to specialize in streaming inference
- Data engineers building real-time analytics platforms
- Developers creating AI applications requiring instant responses
Hands-On Projects
Live Log Anomaly Detector
Use Kafka to stream log data and Spark Streaming to detect anomalies in real-time.
Real-Time Fraud Classifier
Deploy a model to classify financial transactions as fraudulent or legitimate as they occur.
Capstone
Streaming Recommendation Engine
Build a system that updates user recommendations based on live interaction streams.
3-Week Streaming AI Syllabus
~36 hours total • Lifetime LMS access • 1:1 mentor support
Week 1: Kafka Fundamentals
- Introduction to event streaming and Kafka architecture
- Setting up Kafka brokers and Zookeeper
- Producing and consuming messages
- Topics, partitions, and replication
Week 2: Spark Streaming & DStreams
- Spark Streaming concepts and DStreams
- Windowed operations and sliding windows
- Stateful transformations
- Connecting Spark to Kafka streams
Week 3: Real-Time ML & Deployment
- Online learning algorithms
- Model serving for streaming data (e.g., KServe, Seldon)
- Monitoring and alerting for streaming pipelines
- Capstone project: End-to-end streaming ML system
NSTC‑Accredited Certificate
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Frequently Asked Questions
Prior experience is helpful but not mandatory. A strong understanding of machine learning concepts, Python (or Scala/Java), and distributed systems principles is essential. We will cover the fundamentals before advancing.
Yes! You will work with live data streams using Kafka and deploy models to make real-time predictions using Spark Streaming or similar frameworks.
