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DATA SCIENCE & BIG DATA

Theme: Information Technology Management & Uses
Type: Seminar
Status: Realized
Date: March 06, 2018 to March 07, 2018
Main Content: Section 1: Data Analysis Foundations
• Sampling
• Descriptive Statistics
• Estimations
Section 2: Profiling Techniques (Basic and Intermediate)
• Benchmarking techniques
• Comparing exhaustively two groups:
o Means and Variances
o Proportions and Distributions
Section 3: Profiling Techniques (Basic and Intermediate)
• Comparing exhaustively multiple groups:
o Means and Variances
o Proportions and Distributions
• Sample Size:
o Power Tests
o Calculating sample size
Section 4: Machine Learning (Unsupervised)
• Principle Component Analysis
• Clustering
• Clustering (or Segmentation)
• Multi-Dimensional Scaling analysis
Section 5: Machine Learning (Supervised)
• Regression models
• Decision trees
• Discriminant Analysis
• Neural Networks
Section 6: Quality and Forecasting
• SPC, process analysis, …
• Moving averages, Exponential Smoothing, Time Series and ARIMA
Section 7: Business Intelligence
• Data gathering
• ETL
• Data warehouse and Data marts
• Reporting tools
Section 8: Statistical Programming
• R
• Python
Section 9: PMP
• Integration, Scope, Time
• Cost, Quality, HR, Communication
• Risk, Procurement and Stakeholders
Section 10: Big Data
• Data security
• IoT
• BD Technologies
• BD Analytics
Objectives: To introduce the complete components of “Data Science and Big Data” and the required expertise and competencies needed in the fast emerging strategic numerical economy. It will help attendees understanding the “Sweet and Sour” methodologies of data collection, describing data with appropriate indicators, putting all analytics solutions at their right practical applications in comparison with Machine Learning algorithms. This workshop will also tackle the “when” and “when not” use of Big Data and its drawback against classical data. Moreover, this workshop explores the knowledge of the Business Intelligence process of technologies, vital for the synergy between Data Centers and stakeholders. Finally, it compares the pros and cons of Open Source vs. Proprietary Software solutions and their scope of application, with case studies for comparison between all technologies in the market.
Partitcipant Profile: Managers, heads of units, researchers and analysts, CRM, marketing managers, IT and programmers.
Duration: Two-day training activity.
Fees: 500$ (+11% VAT)
 
Index

Upcoming Activities
From: September 24, 2018
To: November 30, 2018
From: September 24, 2018
To: October 1, 2018
From: October 9, 2018
To: October 11, 2018
 
 
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