Microsoft Azure Data Engineer (DP-203)

Course Description

Overview
This course focuses on designing and implementing data solutions using Azure data services. Participants will prepare for the DP-203 certification exam.

What will you learn?

  • Design and implement scalable data pipelines.

  • Use Azure Data Factory, Data Lake, and Databricks.

  • Ensure data security and compliance.

Who is this course for?

  • Data engineers managing Azure data solutions.

  • Professionals preparing for the DP-203 certification exam.

Prerequisites

  • Familiarity with data processing and ETL concepts.

  • Basic knowledge of SQL and Python.

Curriculum for this course

6 Lessons
Designing Data Solutions in Azure
2 Lessons
  • Understanding Azure data architecture
    .
  • Selecting appropriate Azure data services
    .
Implementing Data Pipelines
2 Lessons
  • Managing big data with Azure Data Lake
    .
  • Using Azure Data Factory for ETL processes
    .
Securing and Monitoring Data Solutions
2 Lessons
  • Implementing encryption and monitoring tools
    .
  • Ensuring compliance with data governance policies.
    .

Drop us a message for any query

For more information about our courses, get in touch
with Alchemy contacts

Course rating

Star

90%

Star

80%

Star

65%

Star

60%

Reviews

  • Ruma Sriwastav

    Cover all my needs

    The course identify things we want to change and then figure out the things that need to be done to create the desired outcome. The course helped me in clearly define problems and generate a wider variety of quality solutions. Support more structures analysis of options.

All Courses

Skills Offered

Emerging Skills Offered by Alchemy for 2024-2025

Image
Image

Data Science & Analytics
  • Advanced Data Engineering (e.g., Snowflake, Databricks)
  • Real-Time Data Streaming (e.g., Kafka, Flink)
  • Predictive Analytics with AI/ML Models
  • Advanced Business Intelligence Tools (e.g., Power BI, Tableau)
Image

Emerging Programming Frameworks
  • Quantum Computing Basics (IBM Qiskit, Google Cirq)
  • Web3 Development: Solidity, Smart Contracts
  • Low-code/No-code Platforms (OutSystems, Mendix)
Image

Infrastructure Modernization
  • Software-Defined Networking (SDN) and NFV
  • Advanced Virtualization (Citrix, VMware updates)
  • Hybrid and Edge Computing
Image

Soft Skills and Leadership in Tech
  • Agile Transformation and Leadership
  • Design Thinking for Problem Solving
  • Leading AI-Driven Innovation
Image

AI & Machine Learning
  • Generative AI (e.g., ChatGPT, Bard, MidJourney integrations)
  • Machine Learning Operations (MLOps)
  • Advanced NLP and Speech Recognition
  • AI for Edge Computing
Image

Cloud Technologies
  • Multi-Cloud Management: Azure, AWS, GCP integrations
  • Cloud-Native Development: Kubernetes, Docker, Serverless Architectures
  • AI and ML integration in Cloud Platforms
  • FinOps: Cloud Cost Management
Image

Cybersecurity
  • Zero Trust Architecture (e.g., Illumio)
  • Incident Response and Threat Intelligence
  • Cloud Security (AWS, Azure, and GCP-focused)
  • Advanced Penetration Testing and Ethical Hacking
Image

DevOps and DevSecOps
  • Infrastructure as Code (IaC) with Terraform and Ansible
  • GitOps and Continuous Integration/Continuous Delivery (CI/CD)
  • Security in DevOps Pipelines
Image

Data Science & Analytics
  • Advanced Data Engineering (e.g., Snowflake, Databricks)
  • Real-Time Data Streaming (e.g., Kafka, Flink)
  • Predictive Analytics with AI/ML Models
  • Advanced Business Intelligence Tools (e.g., Power BI, Tableau)
Image

Emerging Programming Frameworks
  • Quantum Computing Basics (IBM Qiskit, Google Cirq)
  • Web3 Development: Solidity, Smart Contracts
  • Low-code/No-code Platforms (OutSystems, Mendix)
Image

Infrastructure Modernization
  • Software-Defined Networking (SDN) and NFV
  • Advanced Virtualization (Citrix, VMware updates)
  • Hybrid and Edge Computing
Image

Soft Skills and Leadership in Tech
  • Agile Transformation and Leadership
  • Design Thinking for Problem Solving
  • Leading AI-Driven Innovation
Image

AI & Machine Learning
  • Generative AI (e.g., ChatGPT, Bard, MidJourney integrations)
  • Machine Learning Operations (MLOps)
  • Advanced NLP and Speech Recognition
  • AI for Edge Computing
Image

Cloud Technologies
  • Multi-Cloud Management: Azure, AWS, GCP integrations
  • Cloud-Native Development: Kubernetes, Docker, Serverless Architectures
  • AI and ML integration in Cloud Platforms
  • FinOps: Cloud Cost Management
Image

Cybersecurity
  • Zero Trust Architecture (e.g., Illumio)
  • Incident Response and Threat Intelligence
  • Cloud Security (AWS, Azure, and GCP-focused)
  • Advanced Penetration Testing and Ethical Hacking
Image

DevOps and DevSecOps
  • Infrastructure as Code (IaC) with Terraform and Ansible
  • GitOps and Continuous Integration/Continuous Delivery (CI/CD)
  • Security in DevOps Pipelines