Data science is the extraction of knowledge from data sets. It employs techniques and theories drawn from several other broader areas of mathematics, primarily analysis, optimization and statistics, information theory and information technology, including signal processing, probabilistic models, machine learning, statistical learning, computer programming, data engineering, pattern recognition and machine learning, visualization, prophetic analytics, uncertainty modeling, data warehousing, geo-visualization , data compression and high performance computing.
Produce methods (automated, as much as possible) for sorting and analyzing mass data and more or less complex or disjointed data sources.
Encourage the extraction of useful or potentially useful information.
Make information easier to use, protect and to value.
Enable more efficient production and use of data and statistics
Module 1: Data Science and Data Governance (Collect, Store, Process and Restore)
Module 2: Data lake and Datawarehouse (massive storage and data security)
Module 3: Manipulation and Visualization of data with R and Python
Module 4: Machine Learning (Designing Algorithms with R and Python)
Have basic knowledge of descriptive statistics
Have computer knowledge