Numpy Library
Master NumPy: array creation, manipulation, indexing, slicing, arithmetic operations, and matrix functions for efficient data handling and scientific computing in Python.
Python for Beginners - English
Learn Python fundamentals including data types, loops, functions, OOP, file handling, and advanced concepts like inheritance, decorators, and polymorphism in this comprehensive beginner's guide.
Python Projects
Learn Python through hands-on projects: build apps, games, and tools while mastering practical programming skills and real-world applications.
Introduction to R Software
Learn R programming essentials: data handling, visualization, statistical functions, and basic calculations. Develop skills for efficient data analysis and manipulation using R software.
R Training- Matrices in R
Learn to create, manipulate, and perform operations on matrices in R, covering creation methods, indexing, slicing, arithmetic, and advanced matrix operations for data science applications.
Data Frames in R
Learn to create, import, export, and manipulate data frames in R. Master essential techniques for data analysis, including subsetting, extending, and transforming datasets.
Scratch Programming and Pico Board Online Class
Learn Scratch programming and game development using the SparkFun Pico Board. Explore loops, motion, touch sensors, sliders, and code editing in this comprehensive tutorial.
RuDalle - The Russian Version of DALL-E
Explore ruDALL-E, a powerful Russian text-to-image model. Learn installation, usage, and techniques for generating impressive AI art from text prompts.
PySpark Best Practices
Learn best practices for PySpark, including dependency management, code structuring, testing, and performance optimization. Gain insights on writing efficient and scalable Python applications using Spark's distributed computing model.
Introduction to Python for Data Science
Learn Python for data science: cleanse data, perform exploratory analysis, and build predictive models using pandas and scikit-learn. Ideal for beginners with basic Python knowledge.
The Human Factors of Running a Data Driven Company
Insights on building a data-driven culture at QuizUp, focusing on team structure, communication, and leveraging data across the organization to inform product decisions.
Knowledge Graphs for the Greater Good - ODSC Europe 2020
Explore knowledge graphs' potential in enhancing machine learning, tackling misinformation, and addressing global challenges like climate change and COVID-19 through semantic web principles and real-world applications.
Tools for High Performance Python - Ian Ozsvald - ODSC Europe 2019
Discover techniques for optimizing Python performance, including efficient Pandas operations, Numba compilation, and Dask parallelization. Learn to identify bottlenecks and implement solutions for faster data processing and analysis.
How LinkedIn Navigates Streams Infrastructure Using Cruise Control - Adem Efe Gencer, PhD
Explore LinkedIn's Cruise Control for managing large-scale Kafka clusters, including architecture, operational challenges, and real-world demonstrations of dynamic load balancing and anomaly detection.
Prepping Data for Analysis Using R
Learn techniques for preparing data for analysis using R, covering common issues, automated solutions, and practical demonstrations for handling missing values and categorical variables.
ODSC West 2015 - Fundamentals of Neo4j
Learn Neo4j fundamentals and Cypher query language in this workshop. Explore graph database advantages, syntax basics, and advanced querying techniques for efficient data modeling and analysis.
Introducing Quine - A Streaming Graph for Modern Data Pipelines
Explore Quine: A streaming graph for modern data pipelines. Learn its inner workings, challenges faced during creation, and use cases illustrating its importance in data processing.
Medical Imaging with Azure Machine Learning
Explore Azure Machine Learning for medical imaging applications, covering data management, model development, deployment, and explainability in healthcare scenarios.
Building Multi-Cloud Success for Cross-Database Usage
Explore strategies for successful multi-cloud implementation, focusing on critical software layers between clouds, security challenges, and optimizing data management across heterogeneous environments.
Best Practices for Optimizing Migration to the Cloud
Learn best practices for cloud migration using automated lineage. Discover how to scope projects, compare lineage paths, prevent privacy issues, and accelerate execution with hybrid cloud data warehouses.
Build NLP Model with Azure ML AutoML NLP Capability
Learn to build NLP models using Azure ML AutoML for tasks like classification and named entity recognition. Explore multilingual support, data labeling, and distributed training for efficient model development.