Data Science And
Analytics
The objective of the program is to educate students on data-related programming and querying languages. The program would help them to use these programming languages to clean, query, and analyze large datasets. It would develop an understanding of machine learning principles and common modeling techniques and a core understanding of both numerical and categorical models to propel business objectives. The program also provides students with useful insights into some of the popular big data tools.
Throughout the program, you’ll delve into a diverse range of topics, from statistical analysis and data manipulation to predictive modeling and data ethics. Guided by experienced instructors, you’ll develop proficiency in programming languages such as Python and R, and gain insights into extracting meaningful insights from large datasets.
PTIB Approved
Data Science and Analytics Diploma was reviewed and approved by the registrar of the Private Training Institutions Branch (PTIB) of the Ministry of Post-Secondary Education and Future Skills.
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Program Length: Campus: | Program Hours: Delivery Method: |
Domestic Fees Tuition: Application Fee: Administrative Fee: Textbooks Fee: Other Fee: Total: | International Fees Tuition: Application Fee: Administrative Fee: Textbooks Fee: Other Fee: Total: |
* For full tuition breakdown please contact us
46-Week Data Science and Analytics Program
DSA101 Relational Database Design
DSA102 Fundamentals of Analytics
DSA103 Predictive and Prescriptive Analytics
DSA104 Neural Networks, Deep Learning and Big Data
DSA105 Introduction to Python Programming
DSA106 Intermediate Python Programming Techniques
DSA107 Advanced Python Programming Techniques
DSA108 Python for Data Science
DSA109 Introduction to Project Management
DSA110 Career and Employment Skills
* For full credit breakdown please contact us
1. Is the program focused on specific applications of data science?
The program covers a wide range of data science topics, including statistical analysis, machine learning algorithms, data visualization, and business intelligence. You’ll gain a well-rounded understanding of various aspects of data science and its applications.
2. How hands-on is the program? Will I be working with real datasets?
Absolutely, the program includes hands-on projects that involve working with real datasets. You’ll analyze data, build models, and create visualizations using industry-standard tools and techniques.
3. How does the program stay updated with the latest data science trends?
The program is designed to stay current with the latest trends and technologies in data science. You’ll learn about emerging tools, techniques, and best practices that are relevant in today’s data-driven world.
4. Can I continue my education after completing this program?
Certainly, this program can serve as a foundation if you’re considering further education in data science, computer science, or related fields. It’s also a strong starting point for individuals looking to build a portfolio and transition into a career in data science and analytics.
Upon successful completion of this program, students will demonstrate the ability to:
- Understand the concept of relational databases
- Create and manipulate databases
- Understand the syntax of various programming and querying languages
- Understand the packages used for data analysis and machine learning
- Work, manipulate and model data using programming languages
- Use various tools to build data visualizations
- Use machine-learning technique to model and build data
- Exposure to deep learning and advanced machine learning models
- Use statistical knowledge to test the accuracy of data models
- Use and implement common big data tools
- Use and implement neural networks
Admission Prerequisites:
- Grade 12 graduation or equivalent (BC High School Diploma, BC Adult Graduation Diploma, General Education Development- GEC, or an equivalent secondary school completion from another jurisdiction). Or a minimum of 19 years of age.
- For domestic students, a minimum of grade 10 English. Students who have English as a second language may be required to provide evidence of proficiency in English. Or
- IELTS 6.0 (with a minimum of 6 in Speaking and Listening and no score lower than 5.5 in Reading and Writing), or
- TOEFL iBT score – 78 or higher.
- TOEFL Paper score – 546 or higher.
- CELPIP score – 7 or higher.
- PTE Academic score – 50 or higher.
- CAEL score – 50 or higher.
- CLB score – 7 or higher.
- Duolingo score – 95 or higher.
Admission Requirements:
- Language proficiency to a specific standard
- Prior education, relevant work, or volunteer experience
- Assessment of specific background through an interview, portfolio review, or audition to a specific standard
- Two letters of recommendation (sent directly to KCC)
Application fee of $250.00 CDN (non-refundable) payable to KCC. - Out-of-country applicants should submit the application fee in the form of a money order in Canadian Funds. In case you have difficulty obtaining Canadian funds please contact KCC. The Registrar may request a personal or telephone/Skype interview with any applicant.
Upon successful completion of this program, students can expect to work as:
- Data Analyst
- Junior Data Scientist
- Database Analyst
- Database Designer
- Data Visualization Analyst
