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Master Azure Databricks, PySpark, Delta Lake, Azure DevOps, Streaming, Machine Learning & OpenAI with hands-on projects.
🎯 Ideal for Aspiring Data Engineers, SQL Developers, BI Professionals & MIS Executives
Sr Data Analyst @MNC | Ex-Sr Software Engineer - Data Scientist
Video Content
Total Lectures
Industry-Focused Sections
Self-Paced Learning
Introduction to Azure Databricks and Data Engineering Concepts
Azure Databricks Setup and Environment Configuration
Azure Databricks Fundamentals and Core Concepts
PySpark Data Processing and Unity Catalog Configuration
Delta Lake Tables, Streaming, and Schema Management
End-to-End Azure Data Engineering Project
Azure DevOps Pipelines, Git Integration, and Automation
Applied Machine Learning with Databricks and OpenAI
Learn enterprise-level Databricks implementation with real-world workflows.
Build scalable big data processing pipelines using PySpark.
Understand Streaming, Schema Enforcement, and Data Lakehouse concepts.
Automate deployments using Git integration and CI/CD pipelines.
Explore practical Machine Learning and Generative AI use cases.
Designed for aspiring professionals preparing for real implementations.
Data Engineering is booming — are you ready?
Instructor: Dr Sachin SaxenaLanguage: English
I have explored the growing demand for Machine Learning roles across product-based companies like Prada Group, AT&T, Virgin Australia, Burberry, Michelin, Santander, Siemens, Toyota Motor Corporation, Warner Bros. Discovery Walgreens etc, and found that expertise in tools like Databricks AutoML, MLflow, Feature Store, and the Databricks Machine Learning environment—including clusters, Jobs, Repos, and Runtime for ML—is increasingly valued for building scalable ML solutions and managing the end-to-end ML lifecycle.
Databricks Certified Machine Learning has emerged as one of the most in-demand roles today.
Based on this trend, I’ve created a structured 25-day roadmap to help you become an Databricks Certified Machine Learning Engineer.
• Day 0 Basic Set and Compute Resource
• Day 1 AutoML Regression Databricks UI
• Day 2 AutoML Regression Databricks Python API
• Day 3 AutoML Classification using UI
• Day 4 AutoML Classification using Python API
• Day 5 AutoML Forecasting Databricks UI
• Day 6 AutoML Forecasting Python API
• Day 7 Feature Store
• Day 8 MLflow Logging API
• Day 9 Machine Learning End-to-End Example
• Day 10 MLflow Model Registry Example
• Day 11 Exploratory Data Analysis
• Day 12 Feature Engineering
• Day 13 Parallelize Hyperparameter Tuning with Automated MLflow
• Day 14 Model Selection with Hyperopt & MLflow
• Day 15 Tuning Distributed Training Algorithms with Hyperopt & Apache Spark MLlib
• Day 16 Automated MLflow Tracking and Cross-Validation
• Day 17 Spark ML Modeling APIs - Binary Classification
• Day 18 GenAI
• Day 19 GenAI AI Foundry
• Day 20 RAG Chatbot
• Day 21 Introduction to Agents
=====================
• Day 22 ATS compliant resume
• Day 23 Interview preparation
• Day 24 LinkedIn profile update
• Day 25 Naukri profile update
If you're aiming to start a career in Databricks Certified Machine Learning, then...
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• Course: Become Databricks Certified Machine Learning Engineer
• Start Date: July 14 (Monday)
• Time: 8:00 AM to 9:00 AM IST
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