Data Science drafted drafted

Program Overview

The Data Science program at the College of Artificial Intelligence-El Alamein provides students with a comprehensive understanding of data science principles and techniques. The program covers a wide range of topics, including machine learning, deep learning, and big data analytics. Students apply their knowledge and skills to real-world data science projects, preparing them for careers in the field. The program offers a variety of elective courses, allowing students to specialize in areas such as cyber security, biocomputing, and business analytics.

Program Outline

The curriculum covers a wide range of topics, including:

• Fundamentals of Data Science: This module introduces students to the core concepts of data science, including data collection, cleaning, and analysis.
• Machine Learning: Students learn about various machine learning algorithms and their applications in data science.
• Deep Learning: This module delves into the principles and techniques of deep learning, a powerful subset of machine learning.
• Computational Linguistics: Students learn about the intersection of data science and natural language processing.
Each course has a unique code, title, and prerequisites.

Individual Modules:

• NC263 Environmental Science and Technology:
No prerequisites
• Term 2:
• BA102 Calculus 2:
Prerequisite: BA101
• GN121 Data Structures:
Prerequisite: GN112
• GN113 Fundamentals of Electronics:
Prerequisite: BA113
• GN123 Digital Logic Design:
Prerequisite: GN111
• LH136 English for Specific Purposes II (ESP II):
Prerequisite: LH011
• BA216 Advanced Physics:
Prerequisite: BA113
• Term 3:
• BA203 Probability and Statistics:
Prerequisite: BA102
• BA304 Linear Algebra:
Prerequisite: BA102
• GN211 Computing Algorithms:
Prerequisite: GN121
• GN212 Discrete Structures:
Prerequisite: GN111
• GN213 Computer Organization:
Prerequisite: GN123
• IN211 Fundamentals of Artificial Intelligence:
Prerequisites: GN111, GN112
• Term 4:
• DS221 Fundamentals of Data Science:
Prerequisites: GN111, GN112
• GN221 Operating Systems:
Prerequisites: GN213, GN211
• GN222 Computer Networks:
Prerequisite: GN112
• GN223 Software Engineering:
Prerequisite: GN121
• IN221 Machine Learning:
Prerequisites: IN211, BA203
• Term 5:
• DS311 Advanced Database Systems:
Prerequisite: DS222
• GN311 Computer and Networks Security:
Prerequisites: GN221, GN222
• GN312 High Performance Computing:
Prerequisite: GN213
• IN311 Deep Learning:
Prerequisite: IN221
• DS312 Programming for Data Science:
Prerequisite: GN121
• Term 6:
• DS321 Big Data Analytics:
Prerequisite: DS121
• DS322 Statistics for Data Science:
Prerequisite: BA203
• DS323 Data Visualization:
Prerequisite: IN311
• DS324 Computational Linguistics:
Prerequisite: IN311
• Term 7:
• DS411 Data Mining and Analytics:
Prerequisite: DS321
• DS412 Information Retrieval and Web Search:
Prerequisite: DS321
• DS413 Project I:
Prerequisites: GPA>=2.0 & CH>=96
• Term 8:
• DS421 Project II:
Prerequisite: DS413

Elective Courses:

The program offers a wide range of elective courses, categorized into different areas:

• DS-Elective:
• CY003 Intrusion Detection and Prevention
• CY004 Machine Learning for Cyber Security
• CY005 Penetration Testing and Countermeasures
• MD001 Fundamentals of Modeling and Simulation
• MD002 Human-Computer Interface Development
• BC001 Fundamentals of Biocomputing and Genomics
• BC002 Applications of computer science in Genomics
• MD003 System Simulation
• BC003 Computational Modeling in Molecular Biology
• MD004 Computer Graphics and Visualization
• BC004 Analysis and Reconstruction of Biological Networks
• MD005 Game Theory and Simulation
• BC005 Evolutionary Computation
• BU001 Quantitative Analysis
• BU002 Business Intelligence and Decision Support Systems
• BU003 Logistics and Operations Management
• BU004 Data-Driven Marketing
• BU005 Data Science Pipeline and Critical Thinking
• CY001 Fundamentals of Digital Forensics
• CY002 Introduction to Block Chain & Distributed Legers
• Other Elective Courses:
• DS001 GIS and Spatial Data Mining
• DS002 Social Media Mining
• DS003 Distributed Data Analysis
• DS004 Theory and Practice of Data Analysis
• DS005 Computational Statistics and Data Analysis
• DS006 Big Data and IoT
• DS007 Forecasting and Predicative Analytics
• DS008 Data Compression Techniques