Python and Spark for Big Data for Banking (PySpark) Training Course

Day 1: Data Processing and Python Essentials for Government

Session 1: Spark DataFrames and Basic Operations

• Working with Spark DataFrames: Implementing Basic Operations
• Groupby and Aggregate Operations
• Handling Timestamps and Dates
• Hands-on Exercise: Data Analysis Using Spark DataFrames for Government

Session 2: Python Programming for Big Data

• Core Python for Data Handling: Using Variables, Lists, and Functions
• Working with Classes and Files
• Integrating APIs and External Data
• Hands-on Exercise: Building a Python Project That Processes and Analyzes Data with PySpark for Government

Day 2: Advanced PySpark and Machine Learning

Session 3: Machine Learning with PySpark

• Implementing Machine Learning with Spark MLlib: Linear and Logistic Regression
• Random Forest Classification Models
• Hands-on Exercise: Building and Evaluating Machine Learning Models Using PySpark for Government

Session 4: Clustering and Recommender Systems

• K-means Clustering: Theory and Practical Implementation
• Hands-on Exercise: Building a K-means Clustering Model for Government
• Recommender Systems: Building a Recommendation Engine with Spark MLlib
• Hands-on Exercise: Recommender System Project for Government

Session 5: Spark Streaming and NLP

• Real-Time Data Streaming with Spark: Implementing Real-Time Data Processing
• Hands-on Exercise: Streaming Data with Spark for Government
• Natural Language Processing (NLP) with PySpark: Implementing Basic NLP Tasks
• Hands-on Exercise: NLP Pipeline Using PySpark for Government