dataviz

“Data Visu...

dataviz

“Data Visualization with D3.js” by TODO

Data Visualization with D3.js

Teacher: Fabio Franchino — TODO

Immersive lecture on the key elements and concepts behind data visualization.

The workshop is an immersive tutorial about how to use the JavaScript open source library D3.js to represent data and to create customized and animated diagrams and charts.

Prerequisites: HTML, CSS, previous experience with JavaScript is welcome.

#dataviz #datavisualization #d3js #javascript

“Crash cou...

“Crash course in Python and data science libraries” by TOP-IX

Crash course in Python and data science libraries

Teacher: Stefania Delprete — TOP-IX

Interactive lessons using Jupyter Notebooks on Python and its most used libraries for data science: NumPy, Pandas, Matplotlib, and an initial Scikit-learn exposure. Plus you’ll get clear on what’s inside the Anaconda and SciPy ecosystems.

This session will include insights of the history and future of the open source libraries, how to contribute and participate to the community events.

Prerequisites: Exposure to Python and Jupyter Notebooks.

#datascience #python #numpy #pandas #matplotlib #seaborn

“Data Anal...

“Data Analysis with Spark Streaming” by Agile Lab

Data Analysis with Spark Streaming

Teacher: AgileLab

Big Data analysis is a hot trend and one of its major roles is to give new value to enterprise data. However data and information lose value as they become old, so it is important in a lot of contexts to do near real-time analysis of incoming data flows. Apache Spark is a major actor in the big data scenario and with its Streaming module aims to solve the main challenges in real-time data processing at scale in distributed environments.

This session aims to show the potential of streaming data analysis and how to leverage on Apache Spark with Structured Streaming to extract value from it without taking care of common problems of streaming processing at scale already solved by Apache Spark.

Prerequisites: Python.

#bigdata #dataengineering #dataframework #apachespark

“Real Time...

“Real Time Ingestion and Analysis of data with MongoDB and Python” by AXANT

Real Time Ingestion and Analysis of data with MongoDB and Python

Teacher: Alessandro Molina — AXANT

Nowadays more and more data is generated by companies and software products, especially in the IoT world records are saved with a throughput of thousands per second.

That requires solutions able to scale writes and perform real time cleanup and analysis of thousands of records per second and MongoDB is getting wildly used in those
environments in the role of what’s commonly named “speed layers” to perform fast analytics over the most recent data and adapt or cleanup incoming records.

This session aims to show how MongoDB can be used as a primary storage for your data, scaling it to thousand of records and thousand of writes per second while also acting as a real-time analysis and visualization channel thanks to change streams and as a flexible analytics tool thanks to the aggregation pipeline and MapReduce.

Prerequisites: Python, JavaScript.

#mongodb #realtime #scaling #mapreduce

“Machine L...

“Machine Learning and Deep Learning for Computer Vision” by ISI

Machine Learning and Deep Learning for Computer Vision

Teachers: Andrè Panisson, Alan Perotti — ISI Foundation

This in-depth part of the course allows to build an appealing and diversified Machine Learning portfolio. It starts with a Machine Learning introduction and application with Scikit-learn, and continues with Neural Networks and backpropagation lectures where you’ll start exploring Computer Vision techniques on a dataset of images.

Deep Learning methods. You’ll be challenged to use TensorFlow and Keras on a image classification real cases (such as distracted drivers, healthcare or plant diseases). The workshop ends with lessons in Transfer Learning and one last project building your data set by scraping Google images and practicing everything you learned.

Prerequisites: Python, Pandas, Statistics, exposure to Machine Learning is welcome.

#machinelearning #deeplearning #neuralnetworks #scikitlearn #tensorflow

map FBK

“Spatial i...

map FBK

“Spatial is special: geo technologies and data” by FBK

From local to global using community data

Teacher: Maurizio Napolitano — Fondazione Bruno Kessler

The workshop is an introduction to the geospatial technologies and everything needed to create maps and analyze geographical data.
As data sources will be used several open data sources including OpenStreetMap.

Prerequisites: Python and a complete installation of QGIS 3.6+

#geospatial #map #opendata #osm #qgis #geopandas

 

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MORE MODULES COMING UP SOON…

Stay tuned! More modules coming up soon…