What’s Included?
High-Quality Video, E-book & Audiobook
Module Quizzes
AI Mentor
Access for Tablet & Phone
Prerequisites
- Experience with Python programming
- Familiarity with ML frameworks (Scikit-Learn, PyTorch, TensorFlow)
- Basic understanding of data science workflows
- Completion of “Create Machine Learning Models” learning path recommended
Skills You’ll Gain
- Scalable Spark Training
- ML Lifecycle Management
- Hyperparameter Tuning with Optune
- Deep Learning Development
- Production Model Deployment
- Distributed Model Training
- MLflow Experiment Tracking
- AI Model Optimization
Self Study Materials Included
Videos
Engaging visual content to enhance understanding and learning experience.
Podcasts
Insightful audio sessions featuring expert discussions and real-world cases.
Audiobooks
Listen and learn anytime with convenient audio-based knowledge sharing.
E-Books
Comprehensive digital guides offering in-depth knowledge and learning support.
Module Wise Quizzes
Interactive assessments to reinforce learning and test conceptual clarity.
Additional Resources
Supplementary references and list of tools to deepen knowledge and practical application.
Tools You’ll Master
Azure Databricks
MLflow
Apache Spark
Optune
What You’ll Learn
Build ML Pipelines
Create scalable workflows using Databricks and Spark.
Train and Evaluate Models
Use ML frameworks for training and performance checks.
Automate Model Selection
Streamline hyperparameter tuning and model choice.
Deploy and Monitor Models
Put models into production and track performance.
Course Modules
Lesson 1: Mobile learning, microlearning, spaced repetition
Module 1: Explore Azure Databricks
Module 2: Use Apache Spark in Azure Databricks
Module 3: Train a machine learning model in Azure Databricks
Module 4: Use MLflow in Azure Databricks
Module 5: Tune hyperparameters in Azure Databricks
Module 6: Use AutoML in Azure Databricks
Module 7: Train deep learning models in Azure Databricks
Module 8: Manage machine learning in production with Azure Databricks
Frequently Asked Questions
Azure Databricks is a cloud platform for big data analytics and scalable machine learning.
Yes, Python experience is essential for working with ML frameworks and Databricks notebooks.
Absolutely. Databricks supports Scikit-Learn, PyTorch, TensorFlow, and more.
No, it’s designed for intermediate learners with prior ML and Python experience.
You’ll learn to use MLflow and Databricks tools to deploy models into production environments.