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 Fall term is September 12, 2022.
The deadline to enroll in CIND119 for Winter term is January 16, 2023.
Students will also not be allowed to swap between sections of the Data Analytics courses after the above dates.
You must download the Microsoft Remote Desktop in order to access the software needed to complete the requirements for this course. Prior to your first class, you are strongly advised to test the computer you plan to use, as machines operated using a third-party administrator (such as laptops provided by a workplace) may not allow access to the required software/download(s).
International students should use their own virtual private network (VPN) software to connect to University resources.
- Data Analytics, Big Data, and Predictive Analytics : Required Courses
- Health Informatics : Electives (select 3)