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Cybersecurity (MS) with an Emphasis in Data Analytics

Cybersecurity (MS) with an Emphasis in Data Analytics

Webster University

Apply with Advent
Location

United States of America

Qualification

Post Graduate(PG)

Fees

Duration

2.5 years

Next intake

Fall, Summer, Spring

Entry score

2.5 (on a 4.0 scale)

The MS in Cybersecurity with an Emphasis in Data Analytics expands on the knowledge gained from undergraduate studies. It focuses on developing advanced skills, theoretical knowledge, and critical thinking needed to master cybersecurity techniques. Students will learn to defend networks and systems, analyze attacks, and conduct forensic evaluations while addressing complex challenges related to “Big Data.”

🔍 Program Highlights:

  • Educational Foundation: Requires an undergraduate degree in Computer Science, Management Information Systems, Information Technology, or a related field, with knowledge of software programming, network management, and systems operations. 🖥️🔒
  • Professional Experience: Relevant experience may be considered upon evaluation. 🏢
  • Communication Skills: Proficiency in written and oral communication is essential. ✍️🗣️

📈 Data Analytics Emphasis:

  • Focus: Develops and applies data analytics skills to address significant business needs.
  • Skills: Integrates business concepts with data modeling, analysis, and problem-solving techniques related to “Big Data.”

🚫 Dual Majors: Not permitted due to the technical nature of the program. Sequential degrees are allowed as long as core courses are not duplicated. 🎓

Core Cybersecurity Curriculum:

🔐 Technical Expertise:

  • Explain key technical methods and theories used in cybersecurity. 🛡️

🖥️ Application of Knowledge:

  • Apply cybersecurity knowledge to analyze software and online issues. 💻

💡 Problem Solving:

  • Integrate cybersecurity knowledge to propose solutions for real-world problems. 🛠️

🔍 Social Engineering & Forensics:

  • Apply social engineering techniques, deterrence methods, and forensic analysis to information systems and applications. 🕵️‍♂️

Data Analytics Emphasis:

📊 Data in Decision Making:

  • Explain the role of data analytics in organizational decision-making. 📈

🗃️ Data Handling:

  • Compose query statements for data definition and manipulation, and construct multidimensional data cubes for analysis. 📊

🔎 Data Analysis Methods:

  • Apply effective methods for analyzing, presenting, and utilizing informational data. 📈

📋 Reporting & Visualization:

  • Develop meaningful reports and visualizations of business data analytics for both technical and non-technical audiences. 📉

🔮 Predictive Models:

  • Articulate forecasting and predictive models for real-world analytical applications. 🔍

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