Introduction to Data Stream Processing

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (32)

Page 3 of 4

Covers Spark Data Frames, distributed collections of data organized into named columns, and the benefits of using them over RDDs.

Big Data: Processing and Dimensions

Explores Big Data generation, storage, processing, and dimensions, along with challenges in data analytics, cloud computing elasticity, and security.

Introduction to Spark Runtime Architecture

Introduces Apache Spark, covering its architecture, RDDs, transformations, actions, fault tolerance, deployment options, and practical exercises in Jupyter notebooks.

Gitlab Agent for Kubernetes (`agentk`)

Covers the setup of a Gitlab agent for Kubernetes, focusing on installation, version control, and troubleshooting.

Apache Spark Ecosystem: Basics and Operations

Provides an overview of the Apache Spark ecosystem, covering basics, operations, and key components.

Collaborative Data Science: Tools and Techniques

Introduces collaborative data science tools like Git and Docker, emphasizing teamwork and practical exercises for effective learning.

Digital Transformation: Solutions and Data

Explores digital transformation opportunities, big data, analytics, and technology innovations in business and research.

Data Science for Engineers: Part 2

Explores data manipulation, exploration, and visualization in data science projects using Python.

Introduction to Applied Data Analysis

Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.

Accelerating Data Analytics: Innovations in Post-Moore Era

Covers advancements in data analytics systems and the role of hardware-software co-design in enhancing performance in the Post-Moore era.