Course DescriptionThis course is designed to give students an overview of big data, state of the practice in analytics, the role of the data scientist, big data analytics in industry verticals, and analytics life-cycle as an end-to-end process. It focuses on key roles for a successful analytic project, main phases of the life-cycle, developing core deliverables for stakeholders, team work skills, and problem solving skills.
What Will You Learn?
This course provides a technical foundation with skills in critical thinking, knowledge extension and transfer, research application, and report writing with respect to big data and data analytics.
Learn how to:
- Engage in machine learning using Weka and IBM Watson.
- Employ appropriate statistical tests to test hypotheses on data.
- Implement machine learning algorithms both in supervised and unsupervised learning.
- Utilize relational database management systems, NoSQL and Hadoop databases.
- Produce relevant visualizations from data.
The deadline to enroll in CIND119 for Spring term (courses that begin the week of May 3,2021) is April 29, 2021.
The deadline to enroll in CIND119 for Summer term (courses that begin the week of June 21, 2021) is June 16, 2021.
Students will also not be allowed to swap between sections of the Data Analytics courses after April 29, 2021 for Spring term and June 16, 2021 for Summer term.
Course materials, video lectures and discussions are delivered and facilitated online within the D2L Learning Management System.
Throughout the semester, student questions related to course content may be answered either by the instructor on discussion board or by an online tutor via email.
- Data Analytics, Big Data, and Predictive Analytics : Required Courses
- Health Informatics : Electives (select 3)