Focuses on configuring a Linux virtual machine, managing hardware, file operations, process management, basic security, and networking. This course helps prepare students to earn a Linux Professional Institute (LPI) Linux Essentials Certification. It will include lectures, practice questions, labs, and discussions needed to successfully pass LPI’s official exam. Prerequisite: general computer or programming experience may be helpful.

Establish knowledge to become sufficient as a beginner Python programmer. Identify the benefits and usefulness of Python including excellent readability and uncluttered simple-to-learn syntax which helps beginners to utilize this programming language. Basic computer experience is required. Programming experience is preferred.

Explores complex areas of Python programming. Discovers how to use this knowledge to work with data structures. Develops custom scripts, GUI applications, and portable exe programs. Recommended Preparation: experience with Python or object-oriented programming.

This course utilizes Python libraries like Pandas, NumPy, and Matplotlib to handle complex data operations efficiently. Provides opportunities to prepare, clean, and structure data for analysis, uncover patterns, and present findings using compelling visualizations. Demonstrates practical, hands-on experience through real-world datasets and projects.

This course covers the principles and techniques of predictive modeling using Python. Students will demonstrate time series analysis, statistical forecasting methods, and machine learning approaches. This course uses Python libraries such as pandas, statsmodels, and Prophet, to prepare data, develop forecasting models, and evaluate their performance. Provides an overview of the skills needed to develop and implement forecasting models to make informed data-driven decisions.