The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Machine Learning methods will be presented by utilizing the KNIME Analytics Platform to discover patterns and relationships in data. Predicting future trends and behaviors allows for proactive, data-driven decisions. During the class learners will acquire new skills to apply predictive algorithms to real data, evaluate, validate and interpret the results without any pre requisites for any kind of programming. Participants will gain the essential skills to design, build, verify and test predictive models.
Code Free Data ScienceUniversity of California San Diego
Über diesen Kurs
University of California San Diego
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
- 5 stars57,06 %
- 4 stars28,24 %
- 3 stars7,34 %
- 2 stars2,82 %
- 1 star4,51 %
Top-Bewertungen von CODE FREE DATA SCIENCE
A lot of extra work must be done to reformat data examples into useful docs. Sometimes the courses require you to look ahead in order to obtain the tools needed for a quiz.
something was missing like a clarified explanation of the methods and resources for the quiz is totally incompetence
Overall this is a good course, but there are some places where it can be frustrating, whether it be lack of information, ambiguous questions, bad audio, etc.
Very nice and interesting Course.. Thank you team & University..
Häufig gestellte Fragen
Wann erhalte ich Zugang zu den Vorträgen und Aufgaben?
Was bekomme ich, wenn ich das Zertifikat erwerbe?
Ist finanzielle Unterstützung möglich?
Haben Sie weitere Fragen? Besuchen Sie das Learner Help Center.