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Our Eligibility Criteria

Explore University of McCordsville’s Eligibility Criteria for Students Worldwide

Eligibility Criteria

Bachelor's Degree or equiv. international education

Credit Hours

60 Hours

Course Duration

1 Year (Self-Paced)

Courses Offered

10

Networks and Telecommunications

This course teaches about the technologies that are being used in the marketplace. The course covers market-driven content such as wireless LANs, security and network management, TCP/IP, and application layers.

Information Technology

This course covers the basic hardware of a personal computer, including installation, operations and interactions with software. Topics include component identification, memory-system, peripheral installation and configuration, preventive maintenance, hardware diagnostics/repair, installation and optimization of system software, commercial programs, system configuration, and device-drivers.

Computer Science

This course uses broad coverage and clear exposition to present a complete picture of the dynamic computer science field. An overview of each of the important areas of Computer Science (e.g. Networking, OS, Computer Architecture, Algorithms) provides you with a general level of proficiency for future courses.

Computing Concepts

This course covers the introduction to the computer science discipline, including an introduction to computing environments, general application software, computing hardware, operating systems, desktop publishing, internet, software applications and tools and computer usage concepts; introducing software engineering and information technology within the broader domain of computing.

It Project Management

This course explains how to successfully manage an IT project and prepare Track from Start to Finish. The course walks you through each step of the IT project management process, covering critical strategies for on-time and within-budget projects.

Advanced Machine Learning Concepts

This advanced course explores complex concepts in machine learning, providing students with expert knowledge and skills. Topics include advanced neural networks, cutting-edge algorithms, and innovative applications.

Machine Learning Innovations

This course explores the latest innovations and technologies in machine learning. Students will learn about emerging trends, new research, and innovative practices that are shaping the future of machine learning.

Machine Learning Leadership

This leadership course focuses on developing the skills necessary to lead and manage machine learning teams effectively. Students will learn about leadership styles, team dynamics, and strategic management in the context of machine learning.

Machine Learning Research Methods

This research-focused course provides students with the skills to conduct scientific research in machine learning. Students will learn research methodologies, data analysis, and how to apply research findings to improve machine learning practices.

Professional Practice in Machine Learning

This course provides students with the practical skills and knowledge needed for a professional career in machine learning. Students will learn about industry standards, professional practices, and how to excel in their careers.

Cost of Attendance

Tuition Fee Breakdown 1 Cost
MASTERS DEGREE $27,000
Medical Insurance $0.00
Personal Expenses $0.00
Study Materials $0.00
Food Cost $0.00
Total Tuition Fee $27,000
Accessible Learning Opportunities

Infinite Horizons Await

At University of McCordsville, we champion the convergence of affordability and opportunity. Our steadfast commitment to accessible education guarantees that high-quality learning is accessible to all. By eliminating financial obstacles, we grant students the freedom to thrive without the burden of overwhelming tuition costs, empowering them to carve out a bright and promising future.

Networks and Telecommunications

Topics Covered in This Course:
  In Section 1 of this course you will cover these topics:
    An introduction to networking
    Network standards
  In Section 2 of this course you will cover these topics:
    Physical layer propagation: utp and optical fiber
    Ethernet lans
  In Section 3 of this exam you will be evaluated on below listed topics:
    Wireless lans -wlans-
    Telecommunications
  In Section 4 of this course you will cover these topics:
    Wide area networks -wans-
    Tcp/ip internetworking
  In Section 5 of this course you will cover these topics:
    Security
    Network management
    Networked applications

Information technology

Topics Covered in This Course:
  In Section 1 of this course you will cover these topics:
    Managing it in an e-world.
    Computer systems.
  In Section 2 of this course you will cover these topics:
    Computer software.
    Telecommunications and networking.
  In Section 3 of this exam you will be evaluated on below listed topics:
    The data resource.
    Enterprise systems.
    Managerial support systems.
  In Section 4 of this course you will cover these topics:
    E-commerce applications.
    Basic information systems concepts.
    Methodologies for custom software development.
    Methodologies for purchased software packages.
  In Section 5 of this course you will cover these topics:
    It project management.
    Facilitating user computing.
    Setting a direction for information resources.
    Managing the information systems function.
    Social, ethical, and legal issues.

Computer science

Topics Covered in This Course:
  In Section 1 of this course you will cover these topics:
    Terms of endearment: defining information technology
    What the digerati know: exploring the human and ndash;computer interface
    Making the connection: the basics of networking
    Marking up with html: a hypertext markup language primer
  In Section 2 of this course you will cover these topics:
    Searching for truth: locating information on the www
    Searching for guinea pig b: case study in online research
    To err is human: an introduction to debugging
    Bits and the -why- of bytes: representing information digitally
  In Section 3 of this exam you will be evaluated on below listed topics:
    Following instructions: principles of computer operation
    What and #39;s the plan? algorithmic thinking
    Light, sound, magic: representing multimedia digitally
    Computers in polite society: social implications of it
  In Section 4 of this course you will cover these topics:
    Shhh, it and #39;s a secret: privacy and digital security
    Fill-in-the-blank computing: basics of spreadsheets
    And lsquo;what if and rsquo; thinking helps: advanced spreadsheets for planning
    A table with a view: database queries
  In Section 5 of this course you will cover these topics:
    Idiary: a case study in database design
    Get with the program: fundamental concepts expressed in javascript
    The bean counter: a javascript program
    Thinking big: programming functions

Computing Concepts

Topics Covered in This Course:
  In Section 1 of this course you will cover these topics:
    Why computers matter to you: becoming computer fluent
    Looking at computers: understanding the parts
  In Section 2 of this course you will cover these topics:
    Using the internet: making the most of the web and rsquo;s resources
    Application software: programs that let you work and play.
  In Section 3 of this exam you will be evaluated on below listed topics:
    Using system software: the operating system, utility programs, and file management
    Evaluating your system: understanding and assessing hardware
  In Section 4 of this course you will cover these topics:
    Networking and security: connecting computers and keeping them safe from hackers and viruses
    Mobile computing: keeping your data on hand
  In Section 5 of this course you will cover these topics:
    Behind the scenes: inside the system unit
    Behind the scenes: software programming
    Behind the scenes: databases and information systems
    Behind the scenes: networking and security
    Behind the scenes: the internet: how it works

IT project Management

Topics Covered in This Course:
  In Section 1 of this course you will cover these topics:
    Introduction.
  In Section 2 of this course you will cover these topics:
    Fundamentals.
  In Section 3 of this exam you will be evaluated on below listed topics:
    Idea stage.
  In Section 4 of this course you will cover these topics:
    The pre-launch stage.
  In Section 5 of this course you will cover these topics:
    Launch stage: planning.
    Launch stage: developing detailed estimates.
    Executive stage: schedule, track, and control the project.
    Implement stage.
    Operation stage.
    Project portfolio management.

Advanced Machine Learning Concepts

Topics Covered in This Course:
  In Section 1 Advanced Neural Networks of this course you will cover these topics:
  • Complex Neural Network Architectures
  • Optimizing Deep Learning Models
  • Transfer Learning and Pre-trained Models
  In Section 2 Cutting-Edge Machine Learning Algorithms of this course you will cover these topics:
  • Advanced Algorithm Development
  • Implementing Novel Algorithms
  • Performance Optimization Techniques
  In Section 3 Innovative Machine Learning Applications of this course you will cover these topics:
  • Emerging Trends in Machine Learning
  • Innovative Machine Learning Solutions
  • Future Directions in Machine Learning
  In Section 4 Ethical and Fair Machine Learning of this course you will cover these topics:
  • Addressing Bias and Fairness
  • Ensuring Transparency and Accountability
  • Ethical Considerations in Advanced Models
  In Section 5 Leadership in Machine Learning of this course you will cover these topics:
  • Leading Machine Learning Teams
  • Strategic Decision Making
  • Professional Development for Leaders

Machine Learning Innovations

Topics Covered in This Course:
  In Section 1 Emerging Trends in Machine Learning of this course you will cover these topics:
  • Latest Research Findings
  • Technological Advances
  • Future Directions in Machine Learning
  In Section 2 Innovations in Algorithms of this course you will cover these topics:
  • Novel Machine Learning Techniques
  • Advanced Algorithm Applications
  • Predictive Analytics in Machine Learning
  In Section 3 Innovative Applications of Machine Learning of this course you will cover these topics:
  • Smart Technology in Machine Learning
  • Innovations in Machine Learning Software
  • Using Technology for Problem Solving
  In Section 4 Sustainable Machine Learning Practices of this course you will cover these topics:
  • Environmental Sustainability
  • Green Technologies
  • Sustainable Machine Learning Operations
  In Section 5 Case Studies in Innovation of this course you will cover these topics:
  • Real-World Applications of Innovations
  • Success Stories
  • Lessons Learned

Machine Learning Leadership

Topics Covered in This Course:
  In Section 1 Leadership Theory and Practice of this course you will cover these topics:
  • Understanding Leadership Styles
  • Developing Leadership Skills
  • Applying Leadership Theories
  In Section 2 Team Dynamics and Management of this course you will cover these topics:
  • Building Effective Teams
  • Managing Team Performance
  • Conflict Resolution
  In Section 3 Strategic Planning in Machine Learning of this course you will cover these topics:
  • Developing Strategic Plans
  • Implementing Strategic Initiatives
  • Evaluating Outcomes
  In Section 4 Ethics and Professionalism of this course you will cover these topics:
  • Ethical Leadership Practices
  • Professional Standards and Conduct
  • Leading with Integrity
  In Section 5 Personal Development for Leaders of this course you will cover these topics:
  • Self-Assessment and Improvement
  • Building a Leadership Career
  • Networking and Professional Growth

Machine Learning Research Methods

Topics Covered in This Course:
  In Section 1 Research Methodology in Machine Learning of this course you will cover these topics:
  • Designing Research Studies
  • Quantitative and Qualitative Methods
  • Ethical Considerations in Research
  In Section 2 Data Collection and Analysis of this course you will cover these topics:
  • Collecting Reliable Machine Learning Data
  • Statistical Analysis Techniques
  • Using Software for Data Analysis
  In Section 3 Conducting Field Research of this course you will cover these topics:
  • Practical Field Research Techniques
  • Managing Research Projects
  • Case Studies in Machine Learning Research
  In Section 4 Applying Research Findings of this course you will cover these topics:
  • Translating Research into Practice
  • Developing Evidence-Based Practices
  • Impact of Research on Machine Learning Solutions
  In Section 5 Publishing and Presenting Research of this course you will cover these topics:
  • Writing Research Papers
  • Presenting Findings at Conferences
  • Building a Research Portfolio

Professional Practice in Machine Learning

Topics Covered in This Course:
  In Section 1 Industry Standards and Practices of this course you will cover these topics:
  • Understanding Industry Standards
  • Best Practices in Machine Learning
  • Regulatory Compliance
  In Section 2 Building a Professional Career of this course you will cover these topics:
  • Career Opportunities in Machine Learning
  • Developing Professional Skills
  • Networking and Professional Development
  In Section 3 Client Relations and Communication of this course you will cover these topics:
  • Building Client Relationships
  • Effective Communication Strategies
  • Managing Client Expectations
  In Section 4 Business Management Skills of this course you will cover these topics:
  • Running a Machine Learning Business
  • Financial Management
  • Marketing and Promotion
  In Section 5 Continuing Education and Growth of this course you will cover these topics:
  • Importance of Lifelong Learning
  • Pursuing Advanced Certifications
  • Staying Current with Industry Trends
✖

Course Details

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