Machine Learning Using Spark 09+ Hours

2 Weekly, Instructor-led

1.5 Hours Online Sessions

Tuesdays and Thursdays

6:00 PM to 7:30 PM

Course Fee: PKR 7000 Only (USD 35)


  • Familiarity with Python
  • Familiarity with version control git/github/gitlab
  • Basic understanding of Machine Learning Sk-Learn.
  • Access to gmail account to open the google colab

Main Topics to be Covered

  • Google Colab
  • Spark Framework
  • Introduction to PySpark
  • What is Koalas
  • Preprocessing the data for ML pipeline
  • Introduction to Clustering and Classification
  • Regression with Spark

Week 1

  • Course Outline
  • Introduction to Google Colab
  • Getting Started with Spark

Week 2

  • Data Wrangling with Spark
  • Spark Under the Hood
  • Spark with Koalas and Pandas

Week 3

  • Machine Learning at Scale
  • Data Preparation with Spark
  • Regression and its Applications

Week 4

  • Cloud Computing
  • Data Pipelines with Spark
  • Challenge: Applications Pipelines

Course Overview

This course will provide a concise introduction of using spark framework to do machine learning. In three weeks, this online course from AI Lounge will walk you through the tool of Spark in detail.  

Verified Certificate

Earn a verified certificate upon completion.

100% Online

Enjoy live sessions with our instructors.

09+ Hours

3 hours per week to complete the course in 3+ weeks


Course will be held in English

Confirm your Registration

Kindly confirm your registration by sending the payment receipt to “info@ai-lounge.com”

IBAN: PK40MEZN0008020102445747
Bank Name: Meezan Bank Limited, Bahria Heights

Meet Your Instructor!

Muhammad A. Raza (Ph.D.) is the founder and CEO of Datafy2ai (A data science Consultancy firm based out of Melbourne, Australia). He has more than 10 years of working experience in various business domains. He is a critical thinker and business leader with a passion to solve complex industry problems. He has worked with companies like Samsung C&T, Mobilink, and a world-renowned Hedge fund. He has been involved in researching, developing, and deploying Machine learning solutions for Big Data Sets in Financial Markets. His interests include business development, machine learning, artificial intelligence, open-source projects and engineering projects.