High tech courses

This course provides an in-depth introduction to the field of digital forensics, focusing on the identification, preservation, analysis, and presentation of digital evidence. Students will learn forensic techniques for investigating cybercrimes, recovering deleted files, analyzing logs, and examining data from computers, mobile devices, and networks. Topics include legal and ethical considerations, forensic tools, chain of custody, and report writing. Hands-on labs and case studies prepare students for careers in cybersecurity, law enforcement, and incident response.

This course introduces the principles and practices of securing digital networks. Topics include network vulnerabilities, threat models, cryptographic protocols, firewalls, intrusion detection systems (IDS), virtual private networks (VPNs), and secure network design. Students will learn to identify and mitigate common cyber threats, configure security tools, and apply best practices in real-world network environments. The course blends theoretical knowledge with hands-on labs and case studies to prepare students for roles in cybersecurity and IT infrastructure protection.

This course introduces students to the principles, tools, and techniques of business analytics to support data-driven decision-making in organizations. It covers key concepts in data analysis, statistical modeling, and predictive analytics, with an emphasis on real-world business applications. Students will learn how to collect, process, and interpret data using tools such as Excel, SQL, and visualization platforms like Tableau or Power BI. Topics include descriptive analytics, diagnostic analytics, forecasting, and performance measurement through KPIs. By the end of the course, students will be able to use analytical thinking and quantitative methods to solve business problems and drive strategic decisions.

This course introduces the fundamentals of SQL (Structured Query Language) tailored for data analytics. Students will learn how to write efficient queries to extract, filter, aggregate, and manipulate data stored in relational databases. Emphasis is placed on using SQL to support data-driven decision-making by performing tasks such as data retrieval, joining tables, and creating reports. Hands-on exercises with real-world datasets help develop practical skills essential for any data analytics role.