Data Science with Databricks

Every Thursday | 11:00am – 3:00pm CST

Why Attend This Workshop?

You will practice data science workflow by exploring data, creating features and building models.
Also tracking and managing model with MLflow.

4 Hours Instructor Lead Training

Things You'll will Learn

Upon Completion of the course, students should be able to:

Create Machine Learning Models
Tune Machine Learning Models with SparkML
Track, Version, & Deploy Models with MLflow


Intermediate Experience with Python
Beginning Experience with the PySpark DataFrame API
Working Knowledge of Machine Learning & Data Science

Workshop Speakers

Hassan Sherwani

Hassan Sherwani

Head of Data Analytics & Data Science
at Royal Cyber


Umer Qaiser

Senior Data Scientist
at Royal Cyber

Course Topics

Part 1:
Machine Learning Problem Solving

  • Machine Learning Intro
  • Types of ML
  • Lifecycle of ML
  • Data Preprocessing
  • Data Cleansing - Lab (Optional)

Part 2:
Regression Analysis in Practice

  • Introduction to Regression Concept
  • OLS vs Ensemble Models
  • Use Case for Regression
  • Regression – Lab

Part 3:
Classification Analysis in Action

  • Introduction to Classification Problem
  • Difference in Logistic Classifier vs Ensemble Models
  • Use Case for Classification
  • Classification – Lab

Part 4:
Machine Learning Model Deployment Using Mlflow

  • Mlflow Tracking
  • Mlflow Project
  • Mlflow Models
  • Mlflow Registry
  • MLflow Lab
Every Thursday | 11:00am – 3:00pm CST

Data Science with Databricks

Register For Workshop

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