Preliminary Education Specialist Credential: Moderate/Severe with Internship Option (CA) Program Page

Preliminary Education
Specialist Authorization:

Extensive Support Needs Teaching Credential
with Internship option (California)

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Home » Programs » Preliminary Education Specialist Authorization: Extensive Support Needs Teaching Credential with Internship option (California)

Program Overview

The preliminary education specialist Extensive Support Needs (ESN) credential program is aligned with the new Education Specialist Authorizations and Standards of the California Commission on Teacher Credentialing (CTC), approved in 2022. The program allows candidates to obtain a Preliminary Education Specialist Credential: ESN Credential with Intern Option (CA). The program provides the knowledge and skills needed to successfully teach and impact the lives of students who have extensive learning support needs. This program explores the range of educational learning problems and applies the latest teaching strategies to enhance the performance of students, no matter their abilities. The program focusses on practical field-based experience that helps candidates understand and critically evaluate education practices and provides strategies that can be immediately applied in teaching practices.

The preliminary education specialist Extensive Support Needs (ESN) credential program is designed for courses to be taken in sequential order and provides candidates with the opportunity to gain professional understanding, integrate research-based teaching practices with appropriate assessment of student work, meet the needs of diverse learners, and learn and apply the principles of specially designed instruction in the 21st century classroom and global learning community.

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Course Details

Course Listing

Program Requirements

  • 14 courses; 63 quarter units

Core Requirements

  • 7 courses; 31.5 quarter units

Course Name

Introduction to statistical modeling and data analysis using R programming to explore data variation, model the data, and evaluate the models. Analysis and evaluation of different types of regression models and error analysis methods.

Forms of data, gap analysis, model building, and interpretation will form the foundation for students to ethically apply data analytics to facilitate modern knowledge discovery techniques.

Application of the data management process for analytics including acquiring and auditing data, assembling data into a modeling sample, performing basic data integrity checks, cleansing data, feature engineering and data visualization.

Students must select one area of specialization.

Specialization in Business Analytics

  • 4 courses; 18 quarter units

Course Name

Performance Management (PM) and Supply Chain Management (SCM) require metrics and indicators to measure value, weaknesses and opportunities through business intelligence. Using data to set objectives and measure the internal and external performances through analytics has been a proven method to business success. Business analytics provide a proactive approach to identify and solve problems before it takes place. Data improvement, data quality assessment, data cleansing and normalization, methods and process improvements will be discussed.

New technologies have opened new arenas in prediction and marketing. Subjects of predictive analytics topics and its role in enterprise marketing will be discussed. The course applies predictive analytic tools to derive the organization’s strategic direction. Market and product analysis will be used to illustrate the development process. Results will be drawn from actual predictive analytics applications and interpreted in the context of business impact.

Financial world faces uncertainty that affects the outcome of sound investments. Leaders are utilizing probabilistic analytic models that alleviate ambiguity on making decision for profitable returns. Theories and practical tools focusing on model building; constructing, processing, and presenting probabilistic information will be discussed. Utilization of analytical software to solve problems on axioms of probability, conditioning and probability trees, random variables and distributions expectation.

Every step of online transactions should be considered with security in mind. Accessing the organizations’ data requires operators to apply the proper security and privacy while the data is stored, transmitted, accessed and when it is worked on. Work with confidential data involves strong ethical practices to be aware of security breaches and how to mitigate threats.

Degree and Course Requirements

To obtain the Master of Science in Data Science, students must complete at least 63 graduate units. A total of 13.5 quarter units of graduate credit may be granted for equivalent graduate work completed at another regionally accredited institution, as it applies to this degree, and provided the units were not used in earning another advanced degree. Please refer to the graduate admissions requirements for specific information regarding application and evaluation.

Reach out today to speak to an admissions counselor directly or download the Course Catalog for additional course requirements and elective options.

Program Learning Outcomes

Upon successful completion of this program, students will be able to:

  • Integrate knowledge/skills to engage and support all extensive support needs students in learning
  • Integrate knowledge/skills to create and maintain effective environments for learning for students with extensive support needs.
  • Synthesize and apply knowledge of how to organize subject matter for learning̶̶ of students with extensive support needs.
  • Integrate knowledge needed for planning instruction and designing learning experiences for Students with extensive support needs
  • Integrate knowledge /skills to administer and analyze formal and informal assessments to determine eligibility, inform instruction, and identify research-based interventions for all learners with ESN
  • Integrate the knowledge to meet legal, ethical, and professional obligations to advocate for all leaners with ESN.
  • Reflect critically on the application of professional beliefs and teaching/learning principles necessary to work collaboratively with all stakeholders including families, other professionals, and community members serving students with extensive support needs.
  • Critique current research in special education theory and practices within inclusive and culturally responsive frameworks.


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Successful completion and attainment of National University degrees do not lead to automatic or immediate licensure, employment, or certification in any state/country. The University cannot guarantee that any professional organization or business will accept a graduate’s application to sit for any certification, licensure, or related exam for the purpose of professional certification.

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