Lectures related to Handling Data: Intro to Pandas

Handling Data: Data Models and Wrangling

Explores data handling fundamentals, including models, sources, and wrangling, emphasizing the importance of understanding and addressing data problems.

Data Modeling: Concepts and Applications

Introduces data modeling concepts, SQL usage, and Pandas library applications for efficient data processing.

Data Modeling: Concepts and Applications

Explores data modeling concepts, SQL implementations, and practical applications in handling missing data.

Data Wrangling with Hadoop: Storage Formats and Hive

Explores data wrangling with Hadoop, emphasizing storage formats and Hive for big data processing.

Spark Data Frames

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

Data: Clouds and Things

Covers the fundamentals of data, cloud storage, and the Internet of Things.

Data, big data, clouds and IoT

Explores data representation, databases, cloud computing, and challenges in the cloud environment.

Big Data Best Practices and Guidelines

Covers best practices and guidelines for big data, including data lakes, architecture, challenges, and technologies like Hadoop and Hive.

Data Wrangling Techniques: HBase and Hive Integration

Covers data wrangling techniques using HBase and Hive, focusing on integration and practical applications.

Introduction to Data Stream Processing: Concepts and Applications

Covers the principles of data stream processing and its applications in real-time data analysis.

Relational Databases: Fundamentals and ACID Properties MOOC: Geographical Information Systems 1

Covers relational databases, transactions, and data consistency in the context of historical database typologies.

Advanced Spark Optimization Techniques: Managing Big Data

Discusses advanced Spark optimization techniques for managing big data efficiently, focusing on parallelization, shuffle operations, and memory management.

Relational Databases: Fundamentals MOOC: Geographical Information Systems 1

Covers relational and spatial databases, including storage, management systems, ACID properties, historical typologies, primary and foreign keys, and spatial functions.

Data Science Essentials

Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.

Relational Model: Basics Log in to Mediaspace to watch this video

Introduces the relational model, SQL, keys, integrity constraints, ER translation, weak entities, ISA hierarchies, and SQL vs. noSQL.

Database Management Systems: Fundamentals Log in to Mediaspace to watch this video

Introduces the fundamentals of database management systems, covering relational model, storage options, data integrity, queries, and data manipulation languages.

Data-Intensive Systems: Relational Model and Algebra Log in to Mediaspace to watch this video

Introduces the relational model and algebra, essential for understanding data-intensive systems and effective database management.

Water Consumption in Geneva Log in to Mediaspace to watch this video

Explores water consumption data in Geneva, including charts on consumption and losses, available datasets, and data processing phases.

Distributed Information Systems: Overview and Models Log in to Mediaspace to watch this video

Covers Distributed Information Systems, key tasks, methods, projects, evaluation, and exam support.

Introduction to Database Systems Log in to Mediaspace to watch this video

Covers the fundamentals of database systems, including data modeling, information processing, and the challenges of managing large volumes of data.