Coming Spring 2017
The big data field offers untapped potential for discovering and analyzing complex problems faced by humankind. These include disease outbreaks, environmental changes, traffic patterns, urban dynamics, and business analytics. This potential has created an incredible demand for information management specialists who can analyze large data streams. To meet this demand, SDSU offers a new course – Big Data Science and Analytics Platforms.
This course introduces state-of-the-art computational platforms, tools, and skills for big data science and big data analytics with numerous real-world case studies:
- Classroom big data platforms include Amazon EC2, Google Compute Engine, and Windows Azure.
- Concepts include Cloud computing, virtualization, cybersecurity, and information privacy.
- Tools are Google Fusion Table, R, and Gephi.
- Skills in database management are relational databases, NoSQL databases, Hadoop, and MongoDB.
This course will have both the hands-on training of analytics tools and computer skills, as well as the fundamental concepts for big data science with critical thinking. Students will have opportunity to create their own big data platform on Amazon EC2 virtual servers, manage their own databases in MongoDB, and access and collect big data from their interested applications (e.g. Twitter data and business datasets).
Key Learning Outcomes
Master key skills and concepts of data science, including data searching, collecting, cleaning, sampling, management, exploratory analysis, statistics, prediction, and data visualization.
Equipment Required: Each student must bring their own laptop computers to the class for the web-based lab exercises and class assignments.
Prerequisites: Minimum computer programming experience, fundamental mathematics, or basic computer courses.
For inquiries, please contact Professor Ming-Hsiang Tsou at firstname.lastname@example.org.