Real-Time Analytics Lectures for SGH students

Lets Start

Real time analytics

Summer 2022 SGH Warsaw School of Economics

Course Topics and Calendar

Below is a list of the topics i’m planning to cover in this course.

More information about this course can be found in the sylabus.

List of all the recommended books!

Part 1: Introduction

  • L01: Course overview
  • L02: The brief history of structured and unstructured data models
  • L03: Time for stream data
  • L04: Anomaly detection in stream data
  • L05: Test

  • C01: Python for ML (OOP, Numpy, Pandas)
  • C02: Structured and unstructured data in Python (SQLAlchemy, Flask)
  • C03: Apache Spark - Intro to structured and unstructured data (RDD, DataFrame)
  • C04: Apache Spark - Time Windows (Patryk Pilarski)
  • C05: Apache Kafka
  • C06: Apache Spark - Stream RDD
  • C07: Apache Spark - Stream DataFrame
  • C08: Apache Spark - ML - case study
  • C09: Apache Spark - ML - case study
  • C10: Cloud env for stream analytics



Lectures 1-5: C-5D Labs 1-9: C-5D


  • Instructor: Sebastian Zając

Overall Format and Participation

  • Starting after the first week of the semester, students will form teams of five to work and collaborate on an individual class project throuhout the semester. Students are expected to meet on a regular and weekly basis to make progress towards their project goals.


  1. Databricks Community edition. Web page.
  2. GIT
  3. Python, Juputer notebook, Colab
  4. Docker
  5. Spark, Flink, Kafka


QWorld, QPoland and Quantum AI Foundation:

Facebook Groups:






www pages:

YouTube Channels:

QWorld Quantum AI Foundation