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2. IBM SkillsBuild - Wikipedia

   en.wikipedia.org/wiki/IBM_SkillsBuild

   IBM SkillsBuild offers 1,000 courses in 20 languages on artificial intelligence, cybersecurity, data analysis, cloud computing, sustainability, and many other technical disciplines — as well as in workplace skills such as Design Thinking. Participants can earn IBM-branded digital credentials that are recognized by the market.

3. SPSS - Wikipedia

   en.wikipedia.org/wiki/SPSS

   SPSS Statistics is a statistical software suite developed by IBM for data management, advanced analytics, multivariate analysis, business intelligence, and criminal investigation. Long produced by SPSS Inc. , it was acquired by IBM in 2009.

4. Data science - Wikipedia

   en.wikipedia.org/wiki/Data_science

   Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics , statistics, computer science , information science , and domain knowledge . [ 6 ]

5. List of statistical software - Wikipedia

   en.wikipedia.org/wiki/List_of_statistical_software

   Pandas – High-performance computing (HPC) data structures and data analysis tools for Python in Python and Cython (statsmodels, scikit-learn) Perl Data Language – Scientific computing with Perl; Ploticus – software for generating a variety of graphs from raw data; PSPP – A free software alternative to IBM SPSS Statistics

6. SPSS Modeler - Wikipedia

   en.wikipedia.org/wiki/SPSS_Modeler

   IBM sells the version of SPSS Modeler 18.2.1 in two separate bundles of features. These two bundles are called "editions" by IBM: SPSS Modeler Professional: used for structured data, such as databases, mainframe data systems, flat files or BI systems; SPSS Modeler Premium: Includes all the features of Modeler Professional, with the addition of:

7. Data analysis - Wikipedia

   en.wikipedia.org/wiki/Data_analysis

   Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]