Apache Spark Basics
Unleashing Big Data’s Potential with Apache Spark
Skills you will gain:
This course provides an in-depth exploration of Apache Spark, its core concepts, and its integration with AI technologies to enhance machine learning capabilities and handle big data with ease.
Aim: Equip participants with the knowledge to use Apache Spark for building robust AI applications, focusing on processing large datasets efficiently.
Program Objectives:
- Master Apache Spark’s capabilities for big data processing and its application in AI.
- Develop practical skills in building and optimizing AI models using Spark.
- Prepare for advanced roles in data science and artificial intelligence.
What you will learn?
- Introduction to Apache Spark:
- Fundamentals of Spark, its ecosystem, and advantages over other big data frameworks.
- Spark Core Concepts:
- Deep dive into Resilient Distributed Datasets (RDDs) and DataFrames for data manipulation.
- Spark for AI Applications:
- Utilizing Spark’s MLlib for machine learning and integrating with AI frameworks like TensorFlow and PyTorch.
- Advanced Data Processing:
- Techniques in stream processing and handling big data for AI applications.
- Real-World Applications and Case Studies:
- Exploring Spark’s application in various industries such as healthcare and finance, with a focus on performance tuning and best practices.
- Project Work:
- Designing and implementing a comprehensive Spark AI project from planning to deployment.
Intended For :
- Data professionals and AI enthusiasts looking to enhance their skill set in big data technologies.
- IT and Computer Science students or professionals aiming to specialize in scalable AI solutions.
Career Supporting Skills