Courses Offered In BACHELORS DEGREE

General Course
Core Course
Specialized Course

Courses Name
Courses Description
Credit Hours

Introduction to the Humanities
The course explores philosophic and artistic heritage of humanity expressed through a historical perspective on visual arts, music, and literature. Topics include myth, literature, art, music, television, cinema, and the theater. Also discussed are provocative issues in the humanities - religion, morality, happiness, death, freedom, and controversies in the arts.
6 Credits

Social and Cultural Geography
Social and Cultural Geography considers why geography matters to the analysis and understanding social relations, cultural identity and social inequality. Course examines how social life is structured at a variety of scales with respect to ethnicity, industries, services, urban patterns, and resources of world as a whole.
6 Credits

English Composition
English Composition provides you with rhetorical foundations that prepare them for academic and professional writing. You will learn the strategies and processes that successful writers employ as you work to accomplish specific purposes. You will develop skills in writing unified, coherent, well-developed essays using correct grammar and effective sentence structure.
6 Credits

College Algebra
College Algebra provides an overview of the fundamental concepts of algebra: an understanding of the general concepts of relation and function; and the ability to solve practical problems using algebra.
6 Credits

World Religions
World Religions course offers the broadest coverage of world religions as they exist today; helping you understand the ideology behind the many religions that strive today. While it is impossible to cover all religions, it does cover those of the vast majority of people.
6 Credits

Ethics
Evenly balanced between theory and applications, this course shows you how to establish an ethical theory and how to apply it to a range of specific moral issues. This course examines ethical problems in such areas as mercy killing, personal relations, business, sexuality, medicine, and the environment.
6 Credits

Art Appreciation
This course introduces the origins and historical development of art. Emphasis is placed on the relationship of design principles to various art forms including but not limited to sculpture, painting, and architecture. Upon completion, you should be able to identify and analyze a variety of artistic styles, periods, and media.
6 Credits

Pre-Calculus
This course provides the mathematical foundation for an introductory calculus course. In addition to a brief review of basic algebra, the course covers equations and inequalities; functions, models, and graphs; polynomial and rational functions; exponential and logarithmic functions; trigonometric functions; and trigonometric identities and equations.
6 Credits

Human Biology
This course is an introductory study of the human body, including the basic structure and function of the major organ systems (nervous, endocrine, circulatory, reproductive, etc.) and the effects of diet, exercise, stress and environmental change on human health.
6 Credits

World History
World History course present the big picture, to facilitate comparison and assessment of change, and to highlight major developments in world's history. This course emphasizes the global interactions of major civilizations so that you can compare and assess changes in the patterns of interaction and the impact of global forces.
6 Credits

Introduction to E-Commerce
This course explains the fundamentals of analyzing, designing and building an E-Commerce website. The course is taught from the viewpoint of a web developer working with a small business client and covers such topics as proposals, contracts, site design, marketing, financial and billing, order processing, shipping and much more.
6 Credits

Introduction to Data Communication
This course is a thorough introduction to the concepts underlying networking technology, from physical carrier media to protocol. It includes historical material to show the logic behind the development of a given mechanism, and also includes comprehensive discussions of increasingly important material, such as B-ISDN and ATM.
6 Credits

Introduction to Computing
Introduction to Computing is designed to give you a better understanding of computing in order to give you a stronger foundation for later courses. The course is in two parts: (a) the underlying structure of a computer, and (b) operating systems and databases
6 Credits

Networking Basics
This course covers topics such as networking basics, network security, setting up TCP/IP and connecting to the Internet, and much more. It will greatly assist the Network administrators in knowing all the information that they need.
6 Credits

Introduction to Programming
This solid foundation in the basics of C++ programming will allow you to create efficient, elegant code ready for any production environment. This course will motivate you by demonstrating why you need to learn the concepts and skills presented.
6 Credits

Essentials of Computer Science
This course contains topics related to computer systems, architecture, Number Systems, Data Formats, The Little Man Computer, The Cpu And Memory, Computer Peripherals, Modern Computer Systems and Regular Languages And Regular Expressions.
6 Credits

Foundations of Information Technology
The goal of this course is to provide you with the foundations of information technologies and their use in knowledge-based organizations. It will also prepare you to understand and manage key technologies and the way they enable business initiatives that were inconceivable a few years ago.
6 Credits

Computer & Internet Search
The course lays emphasis on using the Internet as an educational tool including the use of web browsers, search engines and directories, email basics, acceptable use policies, equity, law and ethics, and evaluation and citation of Internet resources.
6 Credits

Fundamentals of Machine Learning
This course provides a comprehensive understanding of the fundamental principles of machine learning. Students will gain knowledge and skills in algorithm development, model training, and performance evaluation.
6 Credits

Introduction to Machine Learning
This introductory course covers the basics of machine learning, including essential concepts and practices for developing machine learning models. Students will learn about supervised and unsupervised learning, neural networks, and practical applications.
6 Credits

Machine Learning Principles
This course delves into the key principles of machine learning, emphasizing algorithm development, model optimization, and practical applications. Students will learn how to develop and deploy machine learning models effectively.
6 Credits

Machine Learning Analysis
This analytical course equips students with the skills to critically evaluate and improve machine learning models and practices. Students will learn how to use data and research to make informed decisions and optimize machine learning solutions.
6 Credits

Machine Learning Applications
This course offers practical experience in machine learning, focusing on real-world applications of machine learning principles. Students will engage in hands-on activities and projects to apply their knowledge effectively.
6 Credits

Machine Learning Strategies
This course focuses on strategic approaches to machine learning, providing students with advanced skills to develop and implement effective machine learning strategies. Topics include strategic planning, model deployment, and performance evaluation.
6 Credits

College Algebra

Topics Covered in This Course:

In Section 1 of this course you will cover these topics:

Review of the real number system

Linear equations, inequalities, and applications

In Section 2 of this course you will cover these topics:

Graphs, linear equations, and functions

In Section 3 of this exam you will be evaluated on below listed topics:

Systems of linear equations

In Section 4 of this course you will cover these topics:

Exponents, polynomials, and polynomial functions

Factoring

Rational expressions and functions

Roots, radicals, and root functions

In Section 5 of this course you will cover these topics:

Quadratic equations and inequalities

Additional graphs of functions and relations

Inverse, exponential, and logarithmic functions

Polynomial and rational functions

Conic sections and systems of inequalities

Further topics in algebra

Ethics

Topics Covered in This Course:

In Section 1 of this course you will cover these topics:

What is morality?

Consequentialist -teleological- theories of morality

Nonconsequentialist -deontological- theories of morality

In Section 2 of this course you will cover these topics:

Virtue ethics

Absolutism versus relativism

Freedom versus determinism

In Section 3 of this exam you will be evaluated on below listed topics:

Reward and punishment

Setting up a moral system: basic assumptions and basic principles

The taking of human life

In Section 4 of this course you will cover these topics:

Allowing someone to die, mercy death, and mercy killing

Abortion

Lying, cheating, breaking promises, and stealing

In Section 5 of this course you will cover these topics:

Morality, marriage, and human sexuality

Bioethicsethical issues in medicine

Business and media ethics

Environmental ethics

Human Biology

Topics Covered in This Course:

In Section 1 of this course you will cover these topics:

Why study biology?

Basics of biology, anatomy, and physiology.

Determinism, biology, culture, and the ecological perspective.

In Section 2 of this course you will cover these topics:

Biological development and the human lifespan.

Genetics, evolution, and human behavior.

Human biology and intellect.

The human genome project.

In Section 3 of this exam you will be evaluated on below listed topics:

The biology of disability, health, illness, and treatment.

Biology and mental illness

In Section 4 of this course you will cover these topics:

Biological elements of drugs, alcohol, and tobacco

Human sexuality and sexual orientation.

The biology of aging.

In Section 5 of this course you will cover these topics:

Public health and biology.

Critical thinking and human biology

World History

Topics Covered in This Course:

In Section 1 of this course you will cover these topics:

From human prehistory to the rise of agriculture

Early civilization

Nomadic societies

Classical civilization: china

In Section 2 of this course you will cover these topics:

Classical civilization: india

Classical civilization in the mediterranean: persia, greece and rome

The classical period: directions, diversities, and declines by 500 c.e.

The rise of islam: civilization in the middle east

In Section 3 of this exam you will be evaluated on below listed topics:

India and southeast asia under the impact of islam

Africa and islam

East european civilization: byzantium and russia

Western civilization: the middle ages

In Section 4 of this course you will cover these topics:

The spread of east asian civilization

Centers of civilization in the americas

The mongol interlude and the end of the postclassical period

The west and the world: discovery, colonization, and trade

Western civilization changes shape in the early modern centuries

In Section 5 of this course you will cover these topics:

The rise of eastern europe

The ottoman and mughal empires

East asia: vital trends in politics and trade

The first industrial revolution: western society, 17801914

World economy and western imperialism: africa and south asia

The settler societies: the west on frontiers

The development of latin american civilization

The middle east and china in the imperialist century

Russia and japan: industrialization outside the west

World war i and the end of an era

The west in the contemporary period

Eastern european civilization

East asia in the 20th- 22nd centuries

India and southeast asia

Introduction to Data Communication

Topics Covered in This Course:

In Section 1 of this course you will cover these topics:

Introduction and overview.

Network classification.

Network architectures and standards.

Introduction to protocols.

In Section 2 of this course you will cover these topics:

Data coding.

Data communication fundamentals.

Data link control protocols.

Transmission media.

In Section 3 of this exam you will be evaluated on below listed topics:

Communication circuits.

Local area networks -lans-.

Lan systems.

Lan installation and operation.

In Section 4 of this course you will cover these topics:

Wide area networks -wans-.

Internetworking.

The internet.

Internet applications.

In Section 5 of this course you will cover these topics:

Network security.

Network design and implementation.

Network management and operation.

Introduction to Computing

Topics Covered in This Course:

In Section 1 of this course you will cover these topics:

Identifying types of computers

Identifying computer hardware components and their functions

Evaluating, purchasing, and maintaining computer equipment

Identifying software and hardware interaction and types of software

In Section 2 of this course you will cover these topics:

Identifying operating system functions

Using windows

Taking a tour of windows applications

Creating and editing files

In Section 3 of this exam you will be evaluated on below listed topics:

Formatting text and performing common printing functions

Using graphic tools

Working with tables

Using outline, track changes, and language tools

In Section 4 of this course you will cover these topics:

Working with text and numbers in a spreadsheet

Using formulas, functions, and charts

Creating and delivering presentations

Identifying network fundamentals

In Section 5 of this course you will cover these topics:

Identifying the relationships between computer networks, telephone networks, and the internet

Understanding e-mail

Identifying how to use e-mail

Identifying information sources on the internet

Using a web browser and searching the internet

Identifying how computers are used at work, school, and home

Using computers and the internet safely, legally, ethically, and responsibly

Foundations of information technology

Topics Covered in This Course:

In Section 1 of this course you will cover these topics:

Information technology: principles, practices, and opportunities.

Essentials of computing.

In Section 2 of this course you will cover these topics:

Essentials of the internet and the worldwide web.

The central processor and memory.

In Section 3 of this exam you will be evaluated on below listed topics:

Storage and input/output devices.

Personal and pc databases.

In Section 4 of this course you will cover these topics:

Enterprise databases and warehouses.

Enterprise and personal communications networks.

In Section 5 of this course you will cover these topics:

Electronic commerce and electronic business.

Launching application development projects.

Creating enterprise applications.

Creating web-enabled applications.

Information systems in the enterprise.

Issues in information technology.

Fundamentals of Machine Learning

Topics Covered in This Course:

In Section 1 Principles of Machine Learning of this course you will cover these topics:

Core Concepts and Definitions
Machine Learning Frameworks
Role of Data Scientists

In Section 2 Supervised Learning Techniques of this course you will cover these topics:

Advanced Supervised Learning Algorithms
Model Training and Validation
Performance Metrics for Supervised Learning

In Section 3 Unsupervised Learning Techniques of this course you will cover these topics:

Advanced Unsupervised Learning Algorithms
Model Training and Validation
Performance Metrics for Unsupervised Learning

In Section 4 Neural Networks and Deep Learning of this course you will cover these topics:

Deep Learning Fundamentals
Training Deep Neural Networks
Evaluating Deep Learning Models

In Section 5 Applications of Machine Learning of this course you will cover these topics:

Natural Language Processing
Computer Vision
Predictive Analytics

Introduction to Machine Learning

Topics Covered in This Course:

In Section 1 Overview of Machine Learning of this course you will cover these topics:

Introduction to Machine Learning
History and Evolution of Machine Learning
Key Components of Machine Learning

In Section 2 Supervised Learning Basics of this course you will cover these topics:

Fundamentals of Supervised Learning
Common Algorithms in Supervised Learning
Evaluating Supervised Models

In Section 3 Unsupervised Learning Basics of this course you will cover these topics:

Fundamentals of Unsupervised Learning
Common Algorithms in Unsupervised Learning
Evaluating Unsupervised Models

In Section 4 Introduction to Neural Networks of this course you will cover these topics:

Basics of Neural Networks
Types of Neural Networks
Applications of Neural Networks

In Section 5 Applications of Machine Learning of this course you will cover these topics:

Machine Learning in Different Industries
Benefits of Machine Learning
Real-World Applications

Machine Learning Principles

Topics Covered in This Course:

In Section 1 Algorithm Development in Machine Learning of this course you will cover these topics:

Developing Machine Learning Algorithms
Optimizing Algorithm Performance
Implementing Machine Learning Models

In Section 2 Model Optimization Techniques of this course you will cover these topics:

Hyperparameter Tuning
Model Selection and Evaluation
Overfitting and Underfitting

In Section 3 Neural Networks and Advanced Learning of this course you will cover these topics:

Advanced Neural Network Architectures
Training and Optimizing Deep Learning Models
Transfer Learning and Pre-trained Models

In Section 4 Practical Applications of Machine Learning of this course you will cover these topics:

Real-World Machine Learning Projects
Implementing Machine Learning Solutions
Case Studies in Machine Learning

In Section 5 Ethics and Fairness in Machine Learning of this course you will cover these topics:

Addressing Bias in Machine Learning
Ensuring Fairness and Transparency
Ethical Considerations in Model Development

Machine Learning Analysis

Topics Covered in This Course:

In Section 1 Machine Learning Data Analysis of this course you will cover these topics:

Collecting and Analyzing Data for Machine Learning
Using Data for Decision Making
Data Management Tools

In Section 2 Model Performance Analysis of this course you will cover these topics:

Evaluating Model Accuracy and Precision
Identifying Model Inefficiencies
Implementing Improvements

In Section 3 Algorithm Performance Analysis of this course you will cover these topics:

Assessing Algorithm Performance
Using Key Performance Indicators
Benchmarking Against Industry Standards

In Section 4 Ethical and Regulatory Analysis of this course you will cover these topics:

Ensuring Ethical Model Development
Compliance with Data Protection Regulations
Improving Ethical Practices

In Section 5 Research and Development in Machine Learning of this course you will cover these topics:

Conducting Machine Learning Research
Applying Research Findings
Developing Innovative Machine Learning Solutions

Machine Learning Applications

Topics Covered in This Course:

In Section 1 Practical Machine Learning Projects of this course you will cover these topics:

Developing Machine Learning Models
Hands-On Machine Learning Activities
Real-World Machine Learning Challenges

In Section 2 Algorithm Implementation Projects of this course you will cover these topics:

Implementing Machine Learning Algorithms
Training and Optimizing Models
Real-World Algorithm Challenges

In Section 3 Industry-Specific Applications of this course you will cover these topics:

Applying Machine Learning in Healthcare
Machine Learning in Finance
Applications in Marketing and E-commerce

In Section 4 Ethics and Compliance Projects of this course you will cover these topics:

Ensuring Ethical Model Development
Complying with Data Protection Laws
Real-World Ethical Challenges

In Section 5 Professional Practice in Machine Learning of this course you will cover these topics:

Developing Professional Skills
Ethics and Standards in Practice
Building a Career in Machine Learning

Machine Learning Strategies

Topics Covered in This Course:

In Section 1 Developing Machine Learning Strategies of this course you will cover these topics:

Strategic Planning Processes
Setting Machine Learning Objectives
Implementing Machine Learning Strategies

In Section 2 Model Deployment and Scalability of this course you will cover these topics:

Deploying Machine Learning Models
Scaling Machine Learning Solutions
Managing Machine Learning Infrastructure

In Section 3 Performance Evaluation and Monitoring of this course you will cover these topics:

Evaluating Model Performance
Continuous Monitoring and Improvement
Using Performance Metrics

In Section 4 Integration with Business Processes of this course you will cover these topics:

Integrating Machine Learning into Business Operations
Aligning Machine Learning Goals with Business Objectives
Measuring Business Impact

In Section 5 Innovation in Machine Learning of this course you will cover these topics:

Leveraging Cutting-Edge Technologies
Developing Innovative Machine Learning Solutions
Future Trends in Machine Learning

Bachelors Degree in Machine Learning

Our Eligibility Criteria

Eligibility Criteria

Credit Hours

Course Duration

Courses Offered

Courses Offered In BACHELORS DEGREE

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Admissions

Bachelors Degree in Machine Learning

Our Eligibility Criteria

Eligibility Criteria

Credit Hours

Course Duration

Courses Offered

Courses Offered In BACHELORS DEGREE

Course Details

Introduction to the Humanities

Social and Cultural Geography

English Composition

College Algebra

World Religions

Ethics

Art Appreciation

Pre-Calculus

Human Biology

World History

Introduction to E-commerce

Introduction to Data Communication

Introduction to Computing

Networking Basics

Introduction to programming

Essentials of computer science

Foundations of information technology

Computer & internet search

Fundamentals of Machine Learning

Introduction to Machine Learning

Machine Learning Principles

Machine Learning Analysis

Machine Learning Applications

Machine Learning Strategies