Microsoft Course: Implement a machine learning solution with Azure Databricks
Master Scalable Machine Learning with Azure Databricks: From Data to Deployment
- Process big data efficiently
- Train and track models
- Optimize performance
- Build advanced AI models
- Deploy at scale
- Build a base for specialized roles in AI development or cloud engineering
- Prepare for more advanced Microsoft certifications in AI
What you will learn
This 8.5-hour course, Implement a Machine Learning Solution with Azure Databricks, equips data scientists and engineers to build, optimize, and deploy scalable ML workflows using Azure Databricks. Designed for professionals familiar with machine learning, the course covers end-to-end processes—from data preparation with Apache Spark to production deployment. Dive into hyperparameter tuning with Hyperopt, automate model development with AutoML, manage experiments with MLflow, and train deep learning models for advanced AI tasks. Learn to streamline collaboration and operationalize ML pipelines in a unified cloud environment.
Microsoft's Implement a machine learning solution with Azure Databricks course Outline
Learn the Implement a machine learning solution with Azure Databricks
Want to master scalable machine learning in the cloud? Implement a Machine Learning Solution with Azure Databricks is your ultimate guide. In 8.5 hours, learn to build end-to-end ML workflows—from data prep with Spark to deploying deep learning models in production. Perfect for data teams aiming to streamline collaboration and automate model management with MLflow and AutoML. Start your journey today and see why companies like Netflix and Walmart trust Azure Databricks for AI innovation!
Start your journey today:
Course Structure Includes:
Module 1: Azure Databricks Basics (48 min)
- Platform overview and core features.
Module 2: Apache Spark Integration (1 hr 14 min)
- Large-scale data processing and analytics.
Module 3: ML Model Training (1 hr 24 min)
- Frameworks for supervised/unsupervised learning.
Module 4: MLflow for Lifecycle Management (1 hr 3 min)
- Track experiments, log models, and manage versions.
Module 5: Hyperparameter Tuning with Hyperopt (1 hr 8 min)
- Optimize model performance automatically.
Module 6: AutoML for Rapid Development (44 min)
- Simplify model creation with automated pipelines.
Module 7: Deep Learning Models (1 hr 10 min)
- Neural networks for vision, NLP, and forecasting.
Module 8: Production Deployment (1 hr 2 min)
- Operationalize models and manage MLOps workflows.
Training Options
Self Paced Learning
- Lifelong access to high-quality content
- Curated by industry experts
- Customized learning progress
- 24/7 learner assistance and support
- Follow the latest technology trends
Exam Dump
- 100% Real Exam Practice Tests
- 100% Verified Exam Questions & Answers
- 100% Guarantee Passing Rate
- Average 7 Days to Practice & Pass
Description
Learn to build, train, and deploy ML models at scale using Azure Databricks. Master Spark, MLflow, AutoML, and deep learning in end-to-end course.
Pre-requisites
This learning path assumes that you have experience of using Python to explore data and train machine learning models with common open source frameworks, like Scikit-Learn, PyTorch, and TensorFlow.
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SPOTO's study resources provide comprehensive coverage of the exam syllabus, aligning with key topics like ML problem framing, data processing, model optimization, and pipeline automation. The materials include structured learning paths, practice exams, and real-world case studies that mirror the certification's focus on designing, implementing, and deploying machine learning solutions with Microsoft services and ML workflows. By leveraging SPOTO's targeted content, candidates can efficiently bridge knowledge gaps, reinforce practical skills, and gain familiarity with the exam format. This focused preparation increases confidence and readiness, particularly for complex tasks such as deploying CI/CD pipelines or optimizing model performance—areas emphasized in the certification. Combined with hands-on experience, SPOTO's resources offer a strategic advantage for achieving certification success.
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