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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.
Watson Studio provides access to data sets that are available through Watson Data Platform, on-premises or on the cloud. The platform also has a large community and embedded resources such as articles on the latest developments from the data science world and public data sets. The platform is available in on-premises, cloud, and desktop forms.
A free course can be "upgraded" to the paid version of a course, which includes instructor's feedback and grades for the submitted assignments, and (if the student gets a passing grade) a certificate of completion. [57] [60] Other Coursera courses, projects, specializations, etc. cannot be audited—they are only available in paid versions ...
Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...
[13] [14] All CS50x course materials are free and there is no fee to complete the course, though various verified certificates are available for a fee. [15] As of 2024, CS50x teaches the languages C, Python, SQL, HTML, CSS, and JavaScript. It also teaches fundamental computer science concepts including data structures and the Flask framework. [13]
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Analytics is the systematic computational analysis of data or statistics. [1] It is used for the discovery, interpretation, and communication of meaningful patterns in data, which also falls under and directly relates to the umbrella term, data science. [2] Analytics also entails applying data patterns toward effective decision-making.