Python and Spark for Big Data (PySpark) Training

Python and Spark for Big Data (PySpark)

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.

What will you learn?

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.

Requirements:

General programming skills and ideally knowledge of Python.

Course Outline*:

*We know each team has their own needs and specifications. That is why we can modify the training outline per need.

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.

Level:

Intermediate

Duration:

Hours (days:

)

Training customized to your needs

Immersive hands-on experience in a dedicated setting

*Price can range depending on number of participants, change of outline, location etc.

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Master new skills guided by experienced instructors from anywhere.

Level:

Intermediate

Duration:

Hours (days:

)

Training customized to your needs

Reduced training costs

*Price can range depending on number of participants, change of outline, location etc.

Get Quote

You can participate in a Public Course with people from other organisations.

/per trainee

Thanks for the numbers, they could be going to your emails. But they're going to mine... Thanks ;D

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Level:

Intermediate

Duration:

Hours (days:

)

Fits ideally for individuals and small groups

Networking opportunities with fellow participants.

*Price can range depending on number of participants, change of outline, location etc.

Get Quote

Python and Spark for Big Data (PySpark)

What will you learn?

Requirements:

Course Outline*:

Introduction to Big Data Technologies

Distributing Data & Computation

Setting Up Your Environment

Python Programming Essentials

Spark DataFrame Basics

Machine Learning with MLlib

Natural Language Processing

Spark Streaming on Python

Get Quote for:

Python and Spark for Big Data (PySpark)

Start your training experience here!