✓ Certified Course AI & Machine Learning

Databricks Machine Learning – Instructor-Led Training

Live instructor-led training focused on Databricks, Apache Spark, Delta Lake, Machine Learning workflows, MLflow, model management, and production-oriented MLOps practices.

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Accreditation
2–3 Weeks Duration
Live Online Format
Certificate On Completion
Enrol Now — $800.00
Course Overview

About this course

This instructor-led Databricks Machine Learning program provides practical training on building and managing Machine Learning workflows within the Databricks platform. Participants will learn Databricks workspace concepts, Apache Spark, Delta Lake, data processing, ML workflows, MLflow experiment tracking, model management, model serving, and production-oriented MLOps practices through hands-on exercises and a practical project.
What's Included

Everything you get

✓ Live Instructor-Led Online Training
✓ Databricks Platform and Workspace Fundamentals
✓ Apache Spark Fundamentals
✓ Spark DataFrames and Data Processing
✓ Delta Lake Fundamentals
✓ Data Ingestion and ETL Workflows
✓ Data Preparation for Machine Learning
✓ Feature Engineering in Databricks
✓ Machine Learning Workflows in Databricks
✓ MLflow Experiment Tracking
✓ Model Registration and Model Management
✓ Model Serving Fundamentals
✓ MLOps and Production Workflows
✓ Hands-on Databricks Labs
✓ Real-World Databricks Use Cases
✓ Practical Databricks ML Project
✓ Course Materials
✓ Instructor Guidance and Q&A Support
✓ Training Completion Certificate
What You'll Achieve

Learning outcomes

OUTCOME 1

Understand the Databricks Lakehouse environment

OUTCOME 2

Navigate and work within Databricks workspaces

OUTCOME 3

Use Apache Spark for large-scale data processing

OUTCOME 4

Work with Spark DataFrames

OUTCOME 5

Understand Delta Lake and data management

OUTCOME 6

Build data ingestion and ETL workflows

OUTCOME 7

Prepare datasets for Machine Learning in Databricks

OUTCOME 8

Develop Machine Learning workflows using Databricks

OUTCOME 9

Track experiments using MLflow

OUTCOME 10

Register and manage Machine Learning models

OUTCOME 11

Understand model serving and deployment workflows

OUTCOME 12

Understand MLOps concepts for production Machine Learning

OUTCOME 13

Build a practical end-to-end Databricks ML workflow

Skills You'll Gain

Practical, job-ready skills

Databricks Databricks Lakehouse Apache Spark Spark DataFrames Delta Lake Data Processing Data Ingestion ETL Workflows Feature Engineering Databricks Machine Learning MLflow Experiment Tracking Model Management Model Serving MLOps Production ML Workflows Databricks ML Project Development
Career Outcomes

Where this can take you

Step 1

Databricks ML Engineer

Build and manage Machine Learning workflows on the Databricks platform.

Step 2

Data Scientist

Develop and operationalize Machine Learning solutions using Databricks.

Step 3

Data Engineer

Build scalable data processing and ETL workflows using Spark and Delta Lake.

Step 4

MLOps Engineer

Support Machine Learning deployment, model management, and production workflows.

Step 5

Databricks Developer

Develop data and Machine Learning solutions within Databricks.

Step 6

Machine Learning Engineer

Build and manage production-oriented Machine Learning workflows.

Curriculum

Course modules

1
Module 1 – Databricks Lakehouse & Workspace Fundamentals
2
Module 2 – Apache Spark & Spark DataFrames
3
Module 3 – Delta Lake & Data Management
4
Module 4 – Data Ingestion & ETL Workflows
5
Module 5 – Data Preparation for Machine Learning
6
Module 6 – Feature Engineering in Databricks
7
Module 7 – Machine Learning Workflows with Databricks
8
Module 8 – MLflow Experiment Tracking
9
Module 9 – Model Registry & Model Management
10
Module 10 – Model Serving & Deployment Fundamentals
11
Module 11 – MLOps & Production ML Workflows
12
Module 12 – End-to-End Databricks ML Project
How You'll Learn

Format & delivery

✓ Live Instructor-Led Online Sessions
✓ Databricks Platform Demonstrations
✓ Hands-on Databricks Labs
✓ Apache Spark Exercises
✓ Delta Lake Practical Exercises
✓ Data Processing and ETL Labs
✓ MLflow Demonstrations
✓ Model Management Exercises
✓ Model Serving Demonstrations
✓ Real-World Databricks Use Cases
✓ Guided Databricks ML Project
✓ Instructor Q&A Sessions
✓ Project-Based Learning
✓ Final Practical Project
Assessment & Certification

How you're assessed

Module-Based Knowledge Checks
Hands-on Databricks Exercises
Apache Spark Practical Assessments
Data Processing and ML Workflow Exercises
MLflow Practical Assessment
Project-Based Assessment
End-to-End Databricks ML Project Assessment
Final Course Assessment
Certificate of Completion upon Successful Completion
Is This Course For You?

Who should attend

  • Data Scientists
  • Machine Learning Engineers
  • Data Engineers
  • MLOps Professionals
  • AI/ML Professionals
  • Software Developers
  • Data Analysts
  • IT Professionals
  • Professionals working with Apache Spark
  • Professionals interested in Databricks
  • Students pursuing Data and Machine Learning careers