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Data Science and Analytics
Lecturer / Staff
Student
Public
Big Data Analytics
University of Technology and Entrepreneurship, Phnom Penh
0 / 30 enrolled
About this programme
Course outline.
The Big Data Analytics with PySpark course introduces learners to big data processing and analytics using Apache Spark with Python (PySpark). Participants will learn how to handle large-scale datasets, perform distributed data processing, apply machine learning techniques, and integrate multiple data storage systems. The course also covers data visualization and reporting using Power BI, providing end-to-end big data analytics skills.
What you'll get
Programme highlights.
Industry-led teaching
Live materials from practitioners working in the field today.
Hands-on exercises
You'll apply what you learn through structured workshops and case studies.
Mentor access
Personal contact with the instructor for questions and feedback.
UTE Certificate
A signed certificate of completion you can add to your CV.
Course outline
What we'll cover.
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01
Introduction to Big Data Analytics
- • Big Data Concepts and Characteristics • Big Data Architecture • Use Cases of Big Data Analytics
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02
Introduction to Apache Spark and PySpark
- • Overview of Apache Spark • Setting Up PySpark Environment • RDDs and DataFrames
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03
Data Processing with PySpark
- • Data Ingestion and Transformation • Spark SQL • Performance Optimization Techniques
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04
Big Data Storage Systems
- • Relational Databases: MySQL and PostgreSQL • NoSQL Databases: MongoDB • Integrating Databases with Spark
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05
Machine Learning with PySpark
- • Introduction to Spark MLlib • Classification and Regression Models • Clustering and Recommendation Systems
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06
Data Visualization and Reporting
- • Preparing Data for Visualization • Integrating Spark Outputs with Power BI • Building Analytical Reports
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07
Big Data Analytics Project
- • End-to-End Big Data Pipeline • Data Processing
- Analysis
- and Visualization • Final Capstone Project