Course Outline
Introduction
Understanding Big Data
Spark Overview
Python Overview
PySpark Overview
- Distributing Data Using the Resilient Distributed Datasets Framework
- Distributing Computation Using Spark API Operators
Configuring Python with Spark
Configuring PySpark
Utilising Amazon Web Services (AWS) EC2 Instances for Spark
Configuring Databricks
Configuring the AWS EMR Cluster
Foundations of Python Programming
- Introduction to Python
- Working with Jupyter Notebook
- Variables and Basic Data Types
- Managing Lists
- Conditional Statements (if)
- Handling User Input
- While Loops
- Function Implementation
- Class-Oriented Programming
- File Handling and Exception Management
- Projects, Data, and API Interaction
Foundations of Spark DataFrames
- Getting Started with Spark DataFrames
- Basic Operations in Spark
- GroupBy and Aggregate Operations
- Handling Timestamps and Dates
Practical Spark DataFrame Project Exercise
Machine Learning with MLlib
Integrating MLlib, Spark, and Python for Machine Learning
Regressions Explained
- Linear Regression Theory
- Evaluating Regression Code
- Sample Linear Regression Exercise
- Logistic Regression Theory
- Implementing Logistic Regression Code
- Sample Logistic Regression Exercise
Random Forests and Decision Trees
- Tree-Based Methods Theory
- Implementing Decision Trees and Random Forests
- Sample Random Forest Classification Exercise
K-means Clustering
- K-means Clustering Theory
- Implementing K-means Clustering Code
- Sample Clustering Exercise
Recommender Systems
Implementing Natural Language Processing
- Understanding Natural Language Processing (NLP)
- NLP Tools Overview
- Sample NLP Exercise
Streaming with Spark and Python
- Spark Streaming Overview
- Sample Spark Streaming Exercise
Requirements
- General programming skills
Audience
- Developers
- IT Professionals
- Data Scientists
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3900 € + VAT*
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Testimonials (6)
I liked that it was practical. Loved to apply the theoretical knowledge with practical examples.
Aurelia-Adriana - Allianz Services Romania
Course - Python and Spark for Big Data (PySpark)
The course was about a series of very complex related topics & Pablo has in-depth expertise of each of them. Sometimes nuances were lost in communication and/or due to time pressures and possibly expectations were not quite met due to this. Also there were some UHG/Azure Databricks setup issues however Pablo / UHG resolved these quickly once they became apparent - this to me showed a high level of understanding and professionalism between UHG & Pablo,
Michael Monks - Tech NorthWest Skillnet
Course - Python and Spark for Big Data (PySpark)
Individual attention.
ARCHANA ANILKUMAR - PPL
Course - Python and Spark for Big Data (PySpark)
Hands on Training..
Abraham Thomas - PPL
Course - Python and Spark for Big Data (PySpark)
The lessons were taught in a Jupyter notebook. The topics were structured with a logical sequence and naturally helped develop the session from the easier parts to the more complex. I'm already an advanced user of Python with background in Machine Learning, so found the course easier to follow than, possibly, some of my classmates that took the training course. I appreciate that some of the most elementary concepts were skipped and that he focused on the most substantial matters.
Angela DeLaMora - ADT, LLC
Course - Python and Spark for Big Data (PySpark)
practice tasks
