Data Analytics & Management

For those with basic database management knowledge, this course introduces important considerations in database application development and various technologies that have made possible database publishing on the Internet.

For those with SQL knowledge, this course covers advanced SQL statements used in inserting, retrieving, and updating a database. Students learn how to use advanced features of SQL commands and other advanced topics.

Learn tools for distributed data storage and large data set processing. This course focuses on architectures and technologies, including NoSQL and Hadoop.

Data governance is an integrated framework of policies and technology applied to ensure effective data management. This course will help students to gain an understanding of various components that allow an enterprise to manage data.

Designed for students with limited programming, statistics, or data analytics knowledge, this data science overview course is ideal for beginners, business analysts, or non-tech managers interested in the field.

This interactive session, led by experienced instructors and program advisors, provides an in-depth exploration of data science competencies, cutting-edge tools, real-world applications, course requirements, career pathways, and community engagement.

Learn the iterative process of exploratory data analysis (EDA), data analysis techniques, data exploration, and visualization. Course tools include R for data analysis and Tableau for data visualization.

This course covers the key knowledge domains in data science, including data development and management, machine learning and natural language processing, statistical analysis, data visualization, and inference.

This hands-on course helps you use predictive analytics for improving business performance using techniques such as data mining, statistics, modeling, machine learning, and artificial intelligence.

Python is a high-level, dynamically typed, and portable programming language that excels when the cost of software development outweighs performance considerations.

Get an introduction to core concepts in probability and statistics that will be useful throughout your data science career. This course also introduces students to important Python tools used by data scientists. 

This course introduces Pandas, one of the core Python data analysis packages, and uses it as the basis for performing various types of data analysis tasks. Essential data visualization techniques will also be covered. 

Numerical computing plays an essential role in data processing. Get an introduction to core numerical methods using Python. The Python package for numerical computing, Numpy, is used for implementing these methods.

Learn relational database technology, data modeling, SQL, the translation of logical designs to physical storage structures, database integrity, storage and client/server management, and introduction to query optimization.