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.
ofrecido por
Code Free Data Science
Universidad de California en San DiegoAcerca de este Curso
Qué aprenderás
How to design Data Science workflows without any programming involved
Essential Data Science skills to design, build, test and evaluate predictive models
Data Manipulation, preparation and cclassification and clustering methods
Ways to apply Data Science algorithms to real data and evaluate and interpret the results
ofrecido por
Universidad de California en 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.
Programa - Qué aprenderás en este curso
Welcome to the world of Big Data
Welcome to the first module of the Code Free Data Science course. This first module will provide insight into Big Data Hype, its technologies opportunities and challenges. We will take a deeper look into the Big Data Analytics and methodology associated with Data Science approaches.
Introduction to KNIME Analytics Platform
This module will introduce the KNIME analytics platform. Learners will be guided to download, install and setup KNIME. We will explore and become familiar with the KNIME workflow editor and its components. In this module we will create the very first basic workflow, and explore the kinds of analysis KNIME empowers users to perform.
Data Manipulation and Visualization
Machine Learning
Preguntas Frecuentes
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.
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