Coursera

Introduction to PySpark (Coursera)

Offered by Edureka,
Introduction to PySpark (Coursera)

Welcome to Introduction to PySpark, a short course strategically crafted to empower you with the skills needed to assess the concepts of Big Data Management and efficiently perform data analysis using PySpark. Throughout this short course, you will acquire the expertise to perform data processing with PySpark, enabling you to efficiently handle large-scale datasets, conduct advanced analytics, and derive valuable insights from diverse data sources.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

During this short course, you will explore the industry-specific applications of PySpark. By the end of this course, you will be able to:

  1. Attain a basic understanding of the introduction of big data, including its characteristics, challenges, and importance in modern data-driven environments.
  2. Familiarize with Spark architecture and its components, such as Spark Core and Spark SQL.
  3. Familiarize with distributed computing concepts and how they apply to Spark's parallel processing model.
  4. Explore PySpark and big data concepts to solve data-related challenges.
  5. Write PySpark code to solve real-world data analysis and processing tasks.

This short course is designed for Data Analysts, Data Engineers, Data Scientists, and Big Data Developers seeking to enhance their skills in utilizing PySpark for data processing and analysis.
Prior experience with Python and Hadoop is beneficial but not mandatory for this course.
Join us on this journey to enhance your PySpark skills and elevate your analytical and design capabilities.

What you'll learn
Data processing with Pyspark

Syllabus

Big Data Processing with Pyspark
Welcome to Introduction to PySpark. In this short course, you will learn the fundamental concepts of PySpark and Bigdata, and learn to perform real-time data processing with PySpark to gain useful insights from the data.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Machine Learning: Concepts and Applications (Coursera) Coursera
University of Chicago

Machine Learning: Concepts and Applications (Coursera)

Data Science

This course gives you a comprehensive introduction to both the theory and practice of machine learning. You will learn to use Python along with industry-standard libraries and tools, including Pandas, Scikit-learn, and Tensorflow, to ingest, explore, and prepare data for modeling and then train and evaluate models using a wide variety of techniques. Those techniques include linear regression with ordinary least squares, logistic regression, support vector machines, decision trees and ensembles, clustering, principal component analysis, hidden Markov models, and deep learning.

Sep 21st 2026
5-12 Weeks
Python Machine Learning Clustering
Details
Security and Privacy for Big Data - Part 2 (Coursera) Coursera
EIT Digital

Security and Privacy for Big Data - Part 2 (Coursera)

CS: Information & Technology

This course sensitizes regarding privacy and data protection in Big Data environments. You will discover privacy preserving methodologies, as well as data protection regulations and concepts in your Big Data system. By the end of the course, you will be ready to plan your next Big Data project successfully, ensuring that all privacy and data protection related issues are under control.

Sep 21st 2026
1 Week
Security Big Data Privacy
Details
Programação para todos (Conceitos básicos de Python) (Coursera) Coursera
University of Michigan

Programação para todos (Conceitos básicos de Python) (Coursera)

CS: Programming

Este curso tem como objetivo ensinar a todos os conceitos básicos de programação de computadores usando Python. Abordamos o básico de como criar um programa a partir de uma série de instruções simples em Python. O curso não tem pré-requisitos e evita tudo, exceto a matemática mais simples. Qualquer pessoa com experiência moderada em computadores deve ser capaz de dominar os materiais deste curso. Este curso abordará os capítulos 1 ao 5 do livro “Python para Todos”.

Sep 21st 2026
5-12 Weeks
Programming Python Functions
Details
Analíticas de Datos con Pandas (Coursera) Coursera
Tecnológico de Monterrey

Analíticas de Datos con Pandas (Coursera)

Computer Science

La analítica de datos ha avanzado considerablemente en los últimos años y ahora existen diversas herramientas que nos permiten realizar tareas o procesos que antes eran complicados de realizar. Gracias a su versatilidad, el lenguaje de programación Python posee una serie de librerías que permiten realizar proyectos de analítica de datos de una forma muy sencilla y una de las librerías más populares es Pandas.

Sep 21st 2026
4 Weeks
Python Data Analytics Python Programming
Details
Exam Prep AI-102: Microsoft Azure AI Engineer Associate (Coursera) Coursera
Whizlabs

Exam Prep AI-102: Microsoft Azure AI Engineer Associate (Coursera)

CS: Information & Technology

The AI-102: Designing and Implementing a Microsoft Azure AI Solution certification exam tests the candidate’s experience and knowledge of the AI solutions that make the most of Azure Cognitive Services and Azure services. In addition, the exam also tests the candidate's ability to implement this knowledge by participating in all phases of AI solutions development—from defining requirements, and design to development, deployment, integration, maintenance, performance tuning, and monitoring.

Sep 21st 2026
5-12 Weeks
Python Artificial Intelligence Microsoft Azure
Details
Programming for Data Science (Coursera) Coursera
University of Leeds

Programming for Data Science (Coursera)

CS: Programming Data Science

Explore the basics of programming and familiarise yourself with the Python language. After completing this course, you will be able to write Python programs in Jupyter Notebook and describe basic programming. In this course, you will learn everything you need to start your programming journey. You will discover the different data types available in Python and how to use them, learn how to apply conditional and looping control structures, and write your own functions.

Sep 21st 2026
3 Weeks
Programming Python Data Science
Details
Problem Solving, Python Programming, and Video Games (Coursera) Coursera
University of Alberta

Problem Solving, Python Programming, and Video Games (Coursera)

CS: Programming

This course is an introduction to computer science and programming in Python. Important computer science concepts such as problem solving (computational thinking), problem decomposition, algorithms, abstraction, and software quality are emphasized throughout. The Python programming language and video games are used to demonstrate computer science concepts in a concrete and fun manner. However, a learner can take the knowledge and skills from this course and apply them to non-game problems, other programming languages, and other computer science courses.

Sep 21st 2026
5-12 Weeks
Programming Python Algorithms
Details
Machine Learning for Accounting with Python (Coursera) Coursera
University of Illinois at Urbana-Champaign

Machine Learning for Accounting with Python (Coursera)

Data Science

This course, Machine Learning for Accounting with Python, introduces machine learning algorithms (models) and their applications in accounting problems. It covers classification, regression, clustering, text analysis, time series analysis. It also discusses model evaluation and model optimization. This course provides an entry point for students to be able to apply proper machine learning models on business related datasets with Python to solve various problems.

Sep 21st 2026
5-12 Weeks
Algorithms Machine Learning Clustering
Details
Combining and Analyzing Complex Data (Coursera) Coursera
University of Maryland, College Park

Combining and Analyzing Complex Data (Coursera)

Statistics & Data Analysis

In this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions. Software capabilities will be covered with R® receiving particular emphasis. The course will also cover the basics of record linkage and statistical matching—both of which are becoming more important as ways of combining data from different sources. Combining of datasets raises ethical issues which the course reviews. Informed consent may have to be obtained from persons to allow their data to be linked. You will learn about differences in the legal requirements in different countries.

Sep 21st 2026
4 Weeks
Ethics Models Data Analysis
Details
Bayesian Statistics: Mixture Models (Coursera) Coursera
University of California, Santa Cruz

Bayesian Statistics: Mixture Models (Coursera)

Statistics & Data Analysis

Bayesian Statistics: Mixture Models introduces you to an important class of statistical models. The course is organized in five modules, each of which contains lecture videos, short quizzes, background reading, discussion prompts, and one or more peer-reviewed assignments. Statistics is best learned by doing it, not just watching a video, so the course is structured to help you learn through application.

Sep 21st 2026
5-12 Weeks
Statistics Data Analysis Statistical Models
Details