10 Apr, 2018

“A journey of the unexpected: Big data, humanities data” by Oohmm

10 Apr, 2018

A journey of the unexpected: Big data, humanities data Teacher: Renato Gabriele — Oohmm A journey through years of advancement in the big data analysis related with the computational propaganda, crisis, disaster, social events or general elections, researching for new models, analysis covering data and metadata if “polluted”, by...

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10 Apr, 2018

“Data Visualization with D3.js” by TODO

dataviz
10 Apr, 2018

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. Duration:...

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10 Apr, 2018

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

10 Apr, 2018

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...

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10 Apr, 2018

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

10 Apr, 2018

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...

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09 Apr, 2018

“Data Analysis with Spark Streaming” by Agile Lab

09 Apr, 2018

Data Analysis with Spark Streaming Teacher: Nicolò Bidotti — 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...

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08 Apr, 2018

“Excursus: Agent-based modelling and synthetic populations” by GCF

08 Apr, 2018

Excursus: Agent-based modelling and synthetic populations Teachers: Sarah Wolf, Andreas Geiges — Global Climate Forum To understand possible transitions of complex systems (like e.g.societies, markets, systems of socio-technical co-evolution) pure data analysis might not be sufficient because such transitions often imply substantial shifts that can hardly be described by pure...

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07 Apr, 2018

“Data Citizenship and NetScience: technology for data-culture” by HER

07 Apr, 2018

Data Citizenship and NetScience: technology for data-culture Teachers: Salvatore Iaconesi, Oriana Persico — Human Ecosystems Relazioni We constantly generate data, whether we realize it or not, whether we want it or not, and a very limited number of subjects has access to all of this data. This is a very...

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07 Apr, 2018

“Data matching and deduplication with Python” by Oval Money

07 Apr, 2018

Data matching and deduplication with Python Teacher: Simone Marzola — Oval Money In the era of multi-tiered big-data infrastructures, data is commonly spread in multiple datasources and duplicates are everywhere. As a data scientist you’ll need to focus on consolidation of data to improve the data quality and build comprehensive...

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07 Apr, 2018

“Data Visualization using the open source KNOWAGE suite” by KNOWAGE

07 Apr, 2018

Data Visualization using the open source KNOWAGE suite Teachers: Isabella Iennaco, Paolo Raineri — KNOWAGE (Engineering S.p.A) Business analytics lecture on a real KNOWAGE use case of predictive maintenance with an Open Source full stack! The lecture is an interesting journey around KNOWAGE data visualization and data discovery capabilities and...

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06 Apr, 2018

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

06 Apr, 2018

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...

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