Data and AI (Azure Databricks)

Overview

Unlock the transformative potential of Azure Databricks with this comprehensive course on Data Analytics, Machine Learning, Deep Learning, and Generative AI. Designed for professionals and enthusiasts, this course equips you with cutting-edge skills to harness the power of Apache Spark and seamlessly integrate it with Azure Databricks for data-driven solutions.

Syllabus

• Introduction to Azure Databricks
Overview of Azure Databricks
Key Features and Benefits
Setting up Your Environment
• Apache Spark Fundamentals
Introduction to Apache Spark
Spark Architecture and Components
RDDs, DataFrames, and Datasets
• Data Analytics with Azure Databricks
Data Ingestion and ETL Processes
Data Manipulation and Exploration
Visualization with Spark and Databricks
• Machine Learning with Azure Databricks
Introduction to Machine Learning Concepts
Building and Deploying Models with MLlib
Hyperparameter Tuning and Model Evaluation
• Deep Learning with Azure Databricks
Introduction to Deep Learning
Integrating TensorFlow and Keras
Building Neural Networks on Databricks
• Generative AI with Azure Databricks
Understanding Generative Models
Implementing GANs and VAEs
Case Studies in Generative AI
• Integrating Azure Databricks with Azure Services
Connecting with Azure Data Lake Storage
Utilizing Azure Synapse Analytics
Building AI Pipelines with Azure ML
• Best Practices and Use Cases
Performance Optimization and Cost Management
Real-World Case Studies
Ethical Considerations and Responsible AI
• Capstone Project
Designing a Data-Driven AI Solution
Implementing and Presenting Your Project
• Course Review and Next Steps
Recap of Key Concepts
Resources for Continued Learning
Certification Pathways and Career Opportunities

Taught by

Kuljot Singh Bakshi

Subjects

Programming