Databricks - Program-Participants

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Provides hands-on training in using the Databricks platform for data engineering, data science, and machine learning, covering topics like big data processing with Apache Spark, building data pipelines, and advanced analytics. It equips learners with practical skills for managing and analyzing large-scale datasets in a collaborative cloud environment.

Program Framework & Schedule

Course Content

Module 1: Introduction to Advanced Databricks Features

Overview of Databricks architecture and advanced features
Understanding Delta Lake for big data reliability
Managing clusters and autoscaling for optimization

Module 2: Advanced Data Engineering

Building ETL pipelines using Databricks and Spark
Data ingestion techniques with structured and unstructured data
Performance tuning and optimization for Spark jobs
Working with Delta Live Tables for real-time processing

Module 3: Machine Learning on Databricks

Creating and managing ML workflows in Databricks
Feature engineering using MLflow and AutoML
Hyperparameter tuning and distributed training with MLflow
Deployment of machine learning models using Databricks ML Runtime

Module 4: Advanced Analytics and Visualization

Writing complex SQL queries and performing advanced analytics
Using Databricks SQL for BI and reporting
Integrating Databricks with visualization tools like Tableau or Power BI
Building interactive dashboards within Databricks notebooks

Module 5: Databricks Integration and Automation

Integrating Databricks with cloud storage (Azure, AWS, GCP)
Using REST APIs for automation and custom workflows
CI/CD pipelines for Databricks notebooks and jobs
Managing and monitoring jobs using Databricks Workflows

Module 6: Security and Governance

Data governance with Unity Catalog
Role-based access control (RBAC) and workspace permissions
Managing audit logs and compliance requirements
Securing data with encryption and data masking techniques

Module 7: Real-World Project Implementation

Hands-on project: Building an end-to-end data pipeline
Implementing machine learning workflows for predictive analytics
Creating dashboards for real-time insights and reporting
Group collaboration and final project presentation

Outcomes

Master advanced Databricks functionalities for data engineering and ML.
Build, optimize, and deploy end-to-end pipelines.
Gain expertise in integrating Databricks with cloud services and BI tools.

Program Framework & Schedule

Course Content

Module 1: Introduction to Advanced Databricks Features

Module 2: Advanced Data Engineering

Module 3: Machine Learning on Databricks

Module 4: Advanced Analytics and Visualization

Module 5: Databricks Integration and Automation

Module 6: Security and Governance

Module 7: Real-World Project Implementation

Outcomes

Total Program Fee:

INR 25,000/-

INR 2,50,000/-

Eligibility Criteria

Age

Technical Requirements

Education

Other Key Qualities

Language Skills

Coding Experience

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