DATA SCIENCE AND ARTIFICIAL INTELLIGENCE

Program Benefits

– Prepares you for valuable industry certifications
– Market-driven programs
– Growing demand for professionals in this area

Admission

– Grade 12 or equivalent
OR
– Mature student status (18 years of age or older) and a passing score on the entrance examination

Career Opportunities

– Data Scientist
– Statistician/Statistics Officer
– Big Data Developer
– Statistician/Statistics Officer

Program Objective

Data is growing at an unprecedented rate, becoming increasingly large, complex, and unstructured—commonly referred to as “big data.” As the Internet, mobile technologies, and user behaviors continue to evolve, the volume of data generated expands, creating valuable opportunities for businesses to leverage this information in their critical decision-making processes.

The Big Data and Data Science program at Bright Horizon Academy equips students with the knowledge and skills necessary to work with large datasets, perform advanced analytics, apply machine learning techniques, and utilize other key data science technologies effectively in real-world scenarios.

Required Skills and Personal Attributes

  • Strong technical background in computing and data handling

  • Excellent analytical and problem-solving abilities

  • Proficient in written and oral English communication

  • Solid understanding of database structures and architectures

  • Collaborative team player with a positive, self-motivated attitude

  • Detail-oriented and organized

  • Ability to manage time and handle stress effectively

Method of Delivery

  • Integrated Learning System™ training facilitated by Bright Horizon Academy instructors

  • Instructor-led classroom sessions

Program fees cover student manuals and all required course materials. Financial assistance may be available for those who qualify. To graduate, students must achieve an overall average of 75% or higher, with no individual course grade below 60%.

Salary

Qestions & Answers

What is the Cybersecurity Specialist program?

The Cybersecurity Specialist program is a comprehensive training program designed to provide students with the skills and knowledge needed to pursue a career in cybersecurity. It covers various aspects of cybersecurity, including network security, ethical hacking, vulnerability assessment, incident response, and digital forensics.

What are the admission requirements for the Cybersecurity Specialist program?

The specific admission requirements may vary, so it’s best to contact Rumi Academy directly for the most accurate and up-to-date information. Generally, applicants to the Cybersecurity Specialist program should have a high school diploma or equivalent. Some programs may have additional requirements, such as a criminal record check or an admissions interview.

 
What courses are included in the Cybersecurity Specialist program?

The Cybersecurity Specialist program typically includes a range of courses to provide students with a well-rounded education in cybersecurity. Some common courses may include Introduction to Cybersecurity, Network Security, Ethical Hacking, Security Operations, Cryptography, Incident Response, and Digital Forensics.

 
What career opportunities are available after completing the Cybersecurity Specialist program?

Graduates of the Cybersecurity Specialist program can pursue various career paths in the field of cybersecurity. Some potential job titles include Cybersecurity Analyst, Security Consultant, Network Security Engineer, Ethical Hacker, Incident Responder, and Digital Forensics Analyst. The demand for cybersecurity professionals is high, and graduates may find employment opportunities in various industries, including government, healthcare, finance, and technology.

 
 

Duties and Responsibilities

In this field, duties and responsibilities may include, but are not limited to, the following:

  • Conduct statistical analyses and develop algorithms for automated data analysis

  • Evaluate advanced statistical modeling and machine learning techniques using large historical datasets

  • Design artificial neural networks to extract patterns from large-scale sequencing databases

  • Perform data analysis, visualization, and modeling on extensive datasets

  • Handle data acquisition, cleaning, and transformation tasks

  • Define data requirements based on analytical objectives

  • Work with unstructured data from social media, video, audio, or other sources to extract, clean, and transform customer- and item-level data for analysis, modeling, segmentation, and reporting

  • Apply advanced machine learning techniques and statistical/econometric models to pricing, assortment, and marketing mix decisions

  • Interpret, document, and present analytical results to multiple business units, providing actionable conclusions and recommendations based on customer-centric data

  • Identify, develop, and recommend process improvements and best practices

Competencies Upon Completion

  • Identify, gather, and implement system and project requirements

  • Use modeling tools to develop enhanced analytical models

  • Develop, document, and maintain models effectively

  • Create functional, business, and system interface or capability interactions

  • Gather and analyze information to determine technical needs for systems or projects

  • Maintain functional standards for the system or functional framework

  • Document and develop forms, manuals, programs, data files, and procedures

  • Provide guidance, analysis, configuration, implementation, and problem resolution for Hadoop

  • Create attribute, analytic, and calculation views and integrate them into various reports

  • Develop complex business reporting and analytics models

  • Apply common business methodologies effectively

  • Communicate clearly and demonstrate leadership skills

  • Maintain proficiency with widely used data science tools in Canada

  • Use modeling and analytics tools efficiently

  • Possess in-depth knowledge of big data management and data modeling

  • Demonstrate reporting and documentation skills

  • Work proficiently with programming languages such as SQL, Python, and R

  • Automate tasks and processes using artificial intelligence

  • Understand and utilize major big data tools commonly used in Canada