The era of Big Data has arrived. From healthcare to retail to manufacturing to e-commerce, big data is now pervasive. The ubiquity of social media, sensor networks, and technological advances in data collection have resulted in massive datasets that demand methods for analysis and visualization. It is not a far stretch of the imagination to claim that every IT professional today, to be successful, must have a working understanding of data science.
Estimates place the need for Big Data professionals in the US over the next five years to range from 500,000 to 1.5 million. Compensation for Big Data professionals are amongst the highest in the IT industry, commanding annual salaries in the range $100 (entry level to $300K (with experience).
Effective Big Data practice entails a knowledge of storage and processing architectures for massive data, understanding of machine learning and data analytics, and the ability to use data visualizations to comprehend and communicate insights. Having a comprehensive understanding of systems, algorithms, and human factors provides the necessary skill set to lead big data practice across the IT enterprise.
Learn more about the growing opportunities for master's trained AI professionals in our industry insights article: Behind the Algorithm
Content Area Overview:
- Fundamentals of Big Data system architectures (Apache Hadoop, Apache Spark, NoSQL, MongoDB);
- Object oriented foundations to implementing data processing pipelines
- Practical programming issues underlying storing, retrieving, accessing, and processing large datasets;
- Implementing machine learning methods at scale;
- Fundamentals of data and information visualization;
- Social media analytics, including text analytics, network analytics, and action analytics;
- Case studies on real-world datasets;
- Applications of Big Data to domains such as advertising, marketing, electronic health records, Internet of Things (IoT).
CS 5044: Object-Oriented Programming with Java
CS 5644: Machine Learning with Big Data
CS 5664: Social Media Analytics