Business Analytics & Big Data-Μία Πρακτική Εισαγωγή, KEK-OΠΑ σεμινάριο 60 ωρών

Θεματική Ενότητα: Business Analytics & Big Data-Μία Πρακτική Εισαγωγή
ΚΕΚ Οικονομικό Πανεπιστήμιο Αθηνών
Σεμινάριο 60 ωρών - 10 εβδομάδες
Σκοπός του σεμιναρίου είναι να αποτελέσει για τους συμμετέχοντες μία αρχική εισαγωγή στους βασικούς τομείς των business analytics & big data: διαχείριση δεδομένων, στατιστική, μηχανική εκμάθηση. αδόμητα δεδομένα, εργαλεία και συστήματα. Ιδιαίτερη έμφαση δίνεται στην πρακτική διάσταση των παραπάνω τομέων και λιγότερο στις θεωρητικές έννοιες.
Πρόγραμμα Διαλέξεων:
• An Introduction to Big Data & Business Analytics: Fundamentals of data management: data modeling, query languages, query processing, parallel and distributed systems, transactions. The 3Vs of big data. The data lifecycle. Big data systems: an overview of data management systems that fuel the big data revolution.
• Business Intelligence, Fundamentals & Applications: Architectures, multi-dimensional modeling, data cubes, OLAP, indexing, applications. In-memory and column-oriented technologies. Business intelligence in the big data era: unstructured data, data streams, real-time analytics, non-relational engines.
• Statistics for Business Analytics, An Overview: An overview of statistical methods, techniques and principles used in predictive analytics along with examples.
• Big Data Systems, A Practical Outline: A brief presentation of five systems used in big data applications, along with representative applications: Hadoop/HDFS/Hive, Cassandra, MongoDB, Spark and Redis.
• Mining Big Datasets: An overview of data mining concepts such as clustering, classification, association rules, graph mining over large datasets, along with techniques, algorithms, examples.
• Working with Python for Analytics: An introduction to Python and examples on how to use it in analytics application.
• An Introduction to R with Applications: An introduction to Python and examples on how to use it in analytics application.
• Content Analytics: Methods, techniques, tools and systems to extract structure from unstructured data, such as text, audio, speech, images. Sentiment analysis.
• Visual Analytics: Advanced data visualization techniques and practices, specifically for big data interactive exploratory analysis, with live demos and applications.
• Analytics Cases Studies: Four representative end-to-end analytics case studies, presented by established consulting/software firms and ambitious startups alike. The case studies may be drawn from financial, energy, insurance, healthcare and other domains.
Περισσότερες πληροφορίες:
http://kek.aueb.gr/big-data-business-analytics/