Data science is a discipline that combines the use of statistics, the computer science and the knowledge from the domain to extract valuable information from the data. Data science has become an essential tool for businesses and organisations seeking to improve their decision-making decisions, his innovation and his competitiveness. In Data analytics, you will learn the basics of data science and the tools required for data analysis, such as Python and its main libraries for data analysis, including NumPy, Pandas, Matplotlib o Scikit-learn, and how to apply them to different practical scenarios. You’ll also learn about the legal aspects you need to bear in mind to protect data and privacy.
Sector-specific
Big Data and Business Intelligence Development
25 hours
Data Analytics
Big Data and Business Intelligence Development
25 hours
Introduction
Objectives
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To find out what the data science and what are their applications and benefits.
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Learn how to use Python, one of the most popular and versatile languages for data analysis.
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To familiarise yourself with the main Python libraries for the data analysis.
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Learn how to use MongoDB y Hadoop, two systems that facilitate the management of unstructured or distributed data.
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Apply the knowledge applied to various case studies.
Table of Contents
TEACHING UNIT 1. INTRODUCTION TO DATA SCIENCE
1. What is data science?
2. Tools required for data scientists
3. Data Science & Cloud Computing
4. Legal aspects of data protection
TEACHING UNIT 2. PYTHON AND DATA ANALYSIS
1. Introduction to Python
2. What do you need?
3. Libraries for data analysis in Python
4. MongoDB, Hadoop and Python: The Big Data Dream Team
TEACHING UNIT 3. DATA ANALYSIS
1. Analytical Business Intelligence
2. Graph theory and social network analysis
3. Presentation of results
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