DP-3014-Implementing a Machine Learning Solution with Microsoft Azure Databricks

Course Description

Curriculum for this course

14 Lessons
Module 01: Explore Azure Databricks
3 Lessons
  • Fully-managed data lake analytics platform
    .
  • Based on open-source technologies
    .
  • Integrated with Azure for resource management and security
    .
Module 02: Train a machine learning model in Azure Databricks
3 Lessons
  • Prepare data for machine learning
    .
  • Train a machine learning mode
    .
  • Evaluate a machine learning model
    .
Module 03: Use MLflow in Azure Databricks
2 Lessons
  • Use MLflow to log parameters, metrics, and other details from experiment runs.
    .
  • Use MLflow to manage and deploy trained models.
    .
Module 04: Tune hyperparameters in Azure Databricks
2 Lessons
  • Use the Hyperopt library to optimize hyperparameters.
    .
  • Distribute hyperparameter tuning across multiple worker nodes.
    .
Module 05: Use AutoML in Azure Databricks
2 Lessons
  • Use the AutoML user interface in Azure Databricks
    .
  • Use the AutoML API in Azure Databricks
    .
Module 06: Train deep learning models in Azure Databricks
2 Lessons
  • Train a deep learning model in Azure Databricks
    .
  • Distribute deep learning training by using the Horovod library
    .

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Course rating

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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

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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)
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Emerging Programming Frameworks
  • Quantum Computing Basics (IBM Qiskit, Google Cirq)
  • Web3 Development: Solidity, Smart Contracts
  • Low-code/No-code Platforms (OutSystems, Mendix)
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Infrastructure Modernization
  • Software-Defined Networking (SDN) and NFV
  • Advanced Virtualization (Citrix, VMware updates)
  • Hybrid and Edge Computing
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Soft Skills and Leadership in Tech
  • Agile Transformation and Leadership
  • Design Thinking for Problem Solving
  • Leading AI-Driven Innovation
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AI & Machine Learning
  • Generative AI (e.g., ChatGPT, Bard, MidJourney integrations)
  • Machine Learning Operations (MLOps)
  • Advanced NLP and Speech Recognition
  • AI for Edge Computing
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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
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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
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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