// 10 courses indexed
The course directory
Every course we track across 10+ providers, in one searchable index. Want a shortlist picked for your goals? Run a free skill gap analysis.
Graduate Admission Prediction with Pyspark ML
In this 1 hour long project-based course, you will learn to build a linear regression model using Pyspark ML to predict students' admission at the university. We will use the graduate admission 2 data set from Kaggle. Our goal is to use a Simple Linear Regression Machine Learning Algorithm from the Pyspark Machine learning library to predict the chances of getting admission. We will be carrying out the entire project on the Google Colab environment with the installation of Pyspark. You will need a free Gmail account to complete this project. Please be aware of the fact that the dataset and th
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Apache Spark: Design & Execute ETL Pipelines Hands-On
Build practical data engineering skills by learning how to design, develop, and execute end-to-end ETL (Extract, Transform, Load) pipelines using Apache Spark. In this hands-on course, you will begin by setting up a Spark development environment, installing and configuring PySpark, Hadoop, and MySQL, organizing ETL project structures, and exploring real-world datasets. As you progress, you will implement complete and incremental ETL workflows using Apache Spark. You'll integrate Spark with MySQL through JDBC, apply data transformation logic with Spark SQL, perform business-rule filtering, and
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Data Analysis Using Hadoop Tools
The course "Data Analysis Using Hadoop Tools" provides a thorough and hands-on introduction to key tools within the Hadoop ecosystem, such as Hive, Pig, HBase, and Apache Spark, for data processing, management, and analysis. Learners will gain practical experience with Hive's SQL-like interface for complex data querying, Pig Latin scripting for data transformation, and HBase's NoSQL capabilities for efficient big data management. The course also covers Apache Spark's powerful in-memory computation capabilities for high-performance data processing tasks. By the end, participants will be equippe
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Leading with Questions
Based on the best-selling book by Michael J. Marquardt and Bob Tiede. In today's fast-paced and ever-evolving business environment, the ability to ask the right questions is a powerful leadership skill. "Leading with Questions" focuses on equipping leaders with the tools to foster innovation, build trust, and improve team collaboration through strategic inquiry. By mastering the art of asking insightful questions, leaders can uncover new perspectives, spark creativity, and drive organizational success. This course will help learners enhance their leadership capabilities by teaching them how t
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Create an Affinity Diagram Using Creately
By the end of this project you will create an affinity diagram using Creately.com. Learning to collect and organize ideas and information increases productivity and fosters positive teamwork. Learners will engage in the Affinity process to develop an understanding of how to spark, gather, consolidate, sort and present ideas and information.
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Azure SQL Data Warehouse Synapse Analytics Service
Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Unlock the potential of cloud data warehousing with Azure Synapse Analytics. This course begins by introducing the core concepts of cloud-based warehousing, highlighting the advantages over traditional systems. You will gain insights into Synapse Analytics' unified approach to data, enabling you to manage SQL and Spark workloads with ease, al
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PySpark Foundations: Process, analyze, and summarize data
Did you know that a billion records are processed daily in PySpark by companies worldwide? As big data is on the rise, you’ll need tools like PySpark to process massive amounts of data. This guided project was designed to introduce data analysts and data science beginners to data analysis in PySpark. By the end of this 2-hour-long guided project, you’ll create a Jupyter Notebook that processes, analyzes, and summarizes data using PySpark. Specifically, you will set up a PySpark environment, explore and clean large data, aggregate and summarize data, and visualize data using real-life examples
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Optimizing Spark and Cloud Data Storage for Analytics
You will master advanced performance optimization techniques for large-scale data processing using Apache Spark and cloud storage technologies. In this hands-on course, you'll learn to diagnose and resolve performance bottlenecks that plague distributed data systems, implement strategic partitioning and caching strategies that can improve job performance by 30% or more, and design secure, cost-effective cloud data infrastructure. You will gain expertise in transactional data lake technologies like Delta Lake, evaluate storage formats to optimize analytical workloads, and provision enterprise-
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Big Data: Demystifying the Big Idea
By the end of this course, you'll be able to define what makes data "big," distinguish Big Data from a traditional data warehouse, and map the core layers of a Big Data architecture from ingestion to serving. You'll compare processing approaches like batch, streaming, and Lambda, weigh core technologies such as Hadoop, Spark, and Kafka, and evaluate on-premise, cloud, and hybrid hosting against the principles that matter most: performance, availability, scalability, flexibility, and cost. Led by a data and AI cloud architect with over a decade of hands-on experience building solutions for com
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Streaming Data Pipelines with Kafka and Spark
Build practical expertise in real-time data engineering using Apache Kafka, Apache Spark, Spark Structured Streaming, PySpark, Python, Docker, and Docker Compose. You will learn how data engineers design, process, monitor, and maintain streaming pipelines that continuously move event data from source systems to reliable downstream outputs. You will begin by exploring event streaming fundamentals and the architecture of Apache Kafka. You will examine brokers, topics, partitions, producers, consumers, offsets, consumer groups, message ordering, and delivery behavior. Through guided demonstratio
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