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Harness the combined power of Python and Spark in this intensive course on PySpark. Dive deep into big data processing, machine learning, and advanced analytics, tailored for developers, IT professionals, and data scientists.
Harness the combined power of Python and Spark in this intensive course on PySpark. Dive deep into big data processing, machine learning, and advanced analytics, tailored for developers, IT professionals, and data scientists. By the course's end, participants will confidently employ PySpark for a diverse range of big data challenges.
Throughout this course, participants will:
• Mastery of Basics: Get foundational knowledge of Python programming and Spark's core capabilities.
• Hands-on Learning: Engage in practical exercises mirroring real-world scenarios.
• Advanced Analytics: Delve into machine learning with MLlib, regressions, and clustering.
• Streaming & NLP: Learn about Spark streaming and natural language processing.
General programming skills and ideally knowledge of Python.
*We customize the course outline and content to your specific needs and relevant use cases.
Introduction to Big Data Technologies
• Understanding Big Data
• Introduction to Spark, Python, and PySpark
Distributing Data & Computation
• Exploring Resilient Distributed Datasets Framework
• Grasping Spark API Operators
Setting Up Your Environment
• Integrating Python with Spark and PySpark Setup
• Utilizing AWS EC2 Instances for Spark and Databricks
• AWS EMR Cluster Initialization
Python Programming Essentials
• Introduction to Python via Jupyter Notebook
• Core Python Concepts: Variables, Data Types, Lists, Loops, Functions, and Classes
• Handling Files, Exceptions, and Integrating with Data & APIs
Spark DataFrame Basics
• Getting Acquainted with Spark DataFrames
• Basic Operations, Groupby, Aggregates, Timestamps, and Date Handling
• Hands-on Spark DataFrame Project Exercise
Machine Learning with MLlib
• Introduction to Regressions: Linear and Logistic Theories
• Practical exercises on Linear Regression, Logistic Regression
• Delving into Tree Methods: Random Forests, Decision Trees
• Clustering with K-means and its practical application
Natural Language Processing
• Basics of NLP and its toolsets
• Practical NLP Exercise
Spark Streaming on Python
• Understanding Spark Streaming
• Hands-on Spark Streaming Exercise
Hands-on learning with expert instructors at your location for organizations.
Master new skills guided by experienced instructors from anywhere.
