Data Science and Artificial Intelligence
Data is becoming increasingly large, complex, and unstructured,
becoming “big data”. There is ample opportunity to better realize
and unlock its value. As the Internet, mobile technology, and user
habits and demands continue to evolve, resulting in the mass
accumulation of data, more businesses are increasingly accepting
and using this data in all forms and sizes as part of their critical
decision-making processes.
This program will provide students with sufficient knowledge and
skills in the areas of big data analysis, analytics, machine learning,
and other related technologies, so that they may competently
apply them in the field of data science.
Program Notes
Program fees include student manuals and all other course
materials. Financial assistance may be available to those who
qualify.
Graduation requirements: In order to obtain a diploma, students
must obtain an overall average of 75% or better, with no final
course mark below 60%.
Combination of
- Integrated Learning System™ training facilitated by Academy
of Learning Career College facilitators
- Instructor-led classroom learning
Careers in data science and artificial intelligence are increasingly
growing. They include, but are not limited to:
- Data Scientist
- Statistician/Statistics Officer
- Big Data Developer
- Data Analyst
- Machine Learning Engineer
These and similar career paths can be realized through the
employment with businesses and organizations in a variety of
industries, not limited to just the IT industry.
In this area, duties and responsibilities may include, but are not
limited to the following:
- Perform statistical analyses and develop algorithms to be
used in automated analysis
- Evaluating state-of-the-art statistical modelling and machine
learning approaches using large amounts of historical data
- Design artificial neural networks that extract patterns from
large-scale sequencing databases
- Perform data analysis, visualization, and modeling with large
datasets
- Perform data acquisition, cleaning, and transformation
- Take analytical objectives and define data requirements
- Work with unstructured data from social media, video feeds,
audio, or other sources to extract, clean, and transform
customer and item-level statistical data for purposes
analysis, modelling/segmentation, and reporting
- Implement advanced machine learning techniques and
statistical and econometric models to pricing, assortment,
and marketing mix
- Interpret, document, and present/communicate analytical
results to multiple business disciplines, providing
conclusions, and recommendations based on customercentric data
- Identify, develop, and make recommendations for process
improvements and best practices
Grade 12 or equivalent or Mature Student status.
Courses are open to any applicant who possesses a good
command of the English language and is able to follow
instructions.
An admissions interview will be administered to determine if the
applicant has the required interest, motivation, and entry-level
skills to take this program.
Students must attend the required hours and times per week per
the course schedule.
- Strong technical background in computing and data work
- Excellent analytical and technical problem solving skills
- Excellent English communication skills (written and oral)
- Good knowledge of database architectures
- Collaborative team player with a positive self-motivated
can-do attitude
- Self-motivated
- Detail-oriented
- Ability to effectively manage time and stress
- dentify, gather, and implement requirements
- Use modelling tools and develop enhanced models
- Develop and document models
- Develop functional, business, and system interface or
capability interaction
- Gather and analyze information to establish the technical
needs of a system or project
- Develop and maintain functional standards for the
functional framework
- Document and develop forms, manuals, programs, data files,
and procedures
- Provide advice, analysis, configuration, implementation, and
problem resolution for Hadoop
- Create Attribute, Analytic, and Calculation views and use
them in various reports
- Develop complex business reporting and analytics models
- Be knowledgeable in machine learning techniques and
artificial intelligence
- Be familiar with methodologies used in business
- Communicate and take leadership
- Good understanding of most popular data science tools used
in Canada
- Efficient usage of modelling and analytics tools
- In-depth knowledge of big data management and data
modelling
- Reporting and documentation skills
- Proficiency with programming languages including SQL,
Python, and R
- Ability to do automation through artificial intelligence
- Understand and work with major big data tools in Canada
