Data Science Courses

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Azure Data Engineering: End-to-End Track (60-80 Hours)

13 Lessons
Intermediate
What you'll learn
Python and SQL Mastery: For data manipulation and querying
ETL Expertise: Build pipelines using Azure Data Factory
Real-Time Streaming: Work with Event Hubs and Databricks
Data Warehousing Skills: Create optimized data warehouses with Synapse Analytics
Monitoring and Automation: Use Azure Monitor and Automation tools

Data Engineering : Python, SQL, Snowflake, and ETL Focus Mastery

13 Lessons
Intermediate
What you'll learn
Learning Path and Outcome
Python Proficiency: Automate ETL workflows and interact with Snowflake.
SQL Mastery: Query, optimize, and transform data within Snowflake.
ETL Expertise: Build and automate data pipelines using dbt and Python.
Snowflake Knowledge: Master data warehousing concepts and prepare for certifications.
Job Readiness: Gain practical experience through projects and interview prep.

AWS Certified Developer – Associate Exam Preparation

39 Lessons
Intermediate
What you'll learn
AWS Services: Master core services like EC2, S3, Lambda, RDS, and API Gateway.
Application Development: Build and deploy cloud-native applications using AWS SDKs and AWS Lambda.
Automation: Implement CI/CD pipelines with AWS CodePipeline, CodeDeploy, and CodeBuild.
Serverless Architecture: Create serverless applications with AWS Lambda and manage event-driven workflows.
Security & Monitoring: Implement robust security using IAM and monitor application performance with CloudWatch.
Troubleshooting: Debug cloud applications and resolve issues using AWS Developer Tools.
Exam Preparation: Get exam-ready with practice quizzes, mock exams, and AWS certification strategies.