Diploma Program
This program can be offered at the campus(es) below. Please contact the campus of your choosing for program availability and delivery methods.
View Campus Availability
View Delivery Methods
Median Wage
$38 /hour
*Jobbank.gc.ca; 2024;
Set yourself up for success in business and data analytics! CDI College's Data Analytics diploma program covers fundamental concepts, data analysis tools and techniques, and data visualization methods using Tableau and other approaches.
This program is approved by the Private Training Institutions Branch (PTIB) of British Columbia. CDI College is designated by the Education Quality Assurance (EQA).
Student Success Strategies
The purpose of this course is to provide students with the knowledge, skills and study techniques to help foster effective learning and a positive educational experience. This course explores two components of learning styles, Multiple Intelligence-based theory and Personality Spectrum – MBTI-based theory, and how learning styles and personality types affect learning. The course will cover the importance of values, their relationship to goals and goal setting. Strategies for setting personal goals, prioritizing tasks, managing time, and the stress that results from study or work situations will be explored and practiced through active participation in learner-centred activities. Effective study habits, techniques for preparing for tests and productive note taking strategies are key topics of this course that will provide the students with the necessary skills and attitudes to be successful in school. Having a sound understanding of financial, money, credit and debt matters and their implication on our lives is critical knowledge to have. Students taking this course will benefit from completing the Financial Management Workshops, which provides comprehensive coverage of financial and money management skills that will allow them to better save, budget, and manage their money and financial situations.
Fundamentals of Cloud-Based Workspaces
This course explores the fundamental concepts of cloud-based suite of applications for working and collaborating online. Students learn to confidently navigate a virtual workspace in their browser. This course focuses on tools necessary to communicate via chats and video conferencing, collaborate in shared environments, prepare documents, create presentations, utilize online spreadsheet, maintain a calendar, and operate a virtual drive.
Foundations of Data Analytics
This course introduces the students to the fundamentals of data analytics. Based on the objectives of the CompTIA Data+ certification, this course will highlight the importance of data analytics and its pivotal role in the communication of vital business intelligence. The course will explore how the collecting, analyzing, and reporting of data can drive priorities and be the cornerstone of data-driven business decision-making. The course will cover five major areas including data concepts and
environments, data mining, data analysis, visualization and reporting and data governance, quality and control.
Programming Logic and Design
This course is designed to provide the students with a languageindependent view of programming principles and structures and methodologies to foster the development of sound programming techniques before applying language specific syntax. Students will learn traditional and object oriented concepts, terminology and programming structures before learning the details of a specific programming language. Students will learn to develop objectoriented program logic and apply commonly used programming structures of sequence, iteration, selection and decision-making constructs. Common business examples will be used to illustrate key concepts.
Systems Analysis and Design
This course explores the fundamental concepts of systems analysis and design. The course will explore the different analysis and design approaches and methodologies. Students will learn how to gather requirements and information, model the needs, and create the various diagrams. The focus of the course will on the object-oriented approach with the use of the Unified Modeling Language. Students will learn the common UML vocabulary, object oriented terms and diagramming techniques allowing them to model any systems development project from analysis through implementation.
Database Programming Concepts with SQL
In this course, students will learn about the theory behind relational databases, relational database nomenclature, and relational algebra. Students will learn to create functional Structured Query Language (SQL) code to manage databases and manipulate data inputs and outputs. Students will learn to optimize databases through normalization. Students will apply their knowledge with hands-on exercises designed to teach the intricacies of database design methodology.
Fundamentals of Business analytics – statistics
This course explores the fundamental concepts of modern business analytics. Students will gain an understanding of how data analysis works in today’s business organizations. This course provide the foundations needed to understand business analytics and show students how to manipulate data and develop simple data models. The course will explore the fundamental tools and methods of data analysis and statistics with a focus on visual representations of data, descriptive statistical measures, probability distributions and data modeling, sampling and estimation, and statistical inference.
Predictive and Prescriptive Analytics
This course continues the exploration of business analytics from the point of view of predictive and prescriptive analytics. Students will learn to develop approaches for applying trendlines and regression analysis, forecasting and introductory data mining techniques, building and analyzing models on spreadsheets, and simulation and risk analysis. The course also explores linear, integer and nonlinear optimization models
Decision Support Systems with Artificial Intelligence
In this course, students will learn how business analytics, Data Science, artificial intelligence and decision support systems are interrelated and how they work together to provide businesses with the information needed to support decision-making. The course will review Predictive and prescriptive analytics with a focus on Artificial Intelligence, Machine Learning, Big Data, Robotics, social Networks and the Internet of Things and their roles in data science.
Data Science Tools and Techniques
This course explores the tools and techniques used to solve a variety of business and data science problems. Students will start by installing and configuring the tools needed to solve professional-level data science problems. The course will explore the use of the widely used R language and Git versioncontrol system within the context of data science and analytics. They explain how to wrangle data into a form where it can be easily used, analyzed, and visualized to support business decisions. Students will master the powerful R programming techniques and learn troubleshooting skills for probing data at larger scales.
Data Visualization and Interpretation
This course explores topics on data visualization within the context of the tools used to present data in various visual formats. Data visualizations are a powerful method of making data accessible and understandable to non-specialists. Students develop their skills in data presentation through the use of Tableau, a popular data visualization tool utilized by analysts, marketers, statisticians, and any business leadership role that depends on data. Students learn how to use graphs and charts, calculated fields, maps, and interactive dashboards to visualize data and refine the decision-making process.
Business Analysis Dashboards
This course focuses on the visual presentation of data to better support business decision making. Students will learn how to create world-class Power BI business analysis dashboards that transform generic data into visual stories that provide a deeper insight to the information that is being presented. Students will learn to create dashboards from Excel, SharePoint, SQL, Azure Oracle and Dynamics 365.
Programming Techniques for Data Science Part 1
This course will introduce the Python programming language within the context of data science and analytics. The course will start with the introduction of the Python programming environment, the language, and its syntax, control statements, functions and libraries. Students will learn to work with large datasets and data frames with Python.
Programming Techniques for Data Science Part 2
This course will continue the exploration of the Python programming language within the context advanced topics in data science including Artificial Intelligence, Big data and Natural Language Processing, Data Mining, Machine Learning and cognitive computing. The course will conclude with an overview of Big Data: Hadoop®, Spark™, NoSQL and IoT.
Data Analytics with Hadoop
This course focuses on the application of data science with Hadoop. Students will learn practical information about applying data science and Big Data in Hadoop environments. This course will explore practical business applications combined with technical details to offer insight into the Hadoop environment. The course will review the core topics of data science and then explore the Hadoop tools, the Hadoop Distributed File System, importing data, and working with data in the Hadoop environment. Topics include Hadoop tools and utilities, preparing data with Hadoop, Managing work and data flowsBatch Analytics and real-time analytics, visualizing big data and cloud computing.
Machine Learning
This course will introduce what is known about how humans and machines learn. Students will be introduced to the most important classes of machine learning algorithms, and what each of them can do. The course will review key concepts ranging from neural networks to supervised and unsupervised learning. Students will learn the key steps needed to build a successful machine learning solution, from collecting and finetuning source data to building and testing the solution. The course will guide students through the constructing of complete solutions with ML.NET, Microsoft’s powerful open source and cross-platform machine learning framework.
Career & Employment Strategies
In addition to learning career-oriented skills, students learn how to get a job in their chosen profession. Our Employment Services department will assist the graduate in resume writing, as well as preparing for job interviews. Our staff is sensitive to current job market trends and the needs of employers in each local market.
Our graduates receive guidance and training to use career tools that help job seekers build a better resume and cover letter, manage an online portfolio, hone interviewing skills, and develop a personal brand online.
Students will have the use of a computer lab which has unlimited Internet access, as well as job search resources. Facilitators will also be made available to advise on job finding resources, interview skills and techniques and to carry out mock interviews.
This course also looks at the planning, preparation, execution, and follow-up stages of an interview:
Data Analytics Practicum
This field placement will prepare students for their transition to the workforce. The practicum will be completed in a business environment working under the supervision of experienced personnel. Students are provided with a description of duties he/she will perform on the job. At the end of the placement, the practicum host will provide an evaluation on the student and the student will provide the college with an evaluation on the placement.
Admission
Benefits of this program
Employment Opportunities
Admission
Benefits of this program
Employment Opportunities
1. High school graduation or equivalent from an institution where the program is delivered in English; Or Grade 10 English or Equivalent for Mature Students
2. Accepted English Language Proficiency Assessment Test Scores
3. Successful completion of the College’s English for Academic Purposes Program – Intermediate level or higher
4. An equivalent English course taken at another institution -shown in the BCCAT transfer guide.
5. Completion of the required ESL Level at a qualified pathway program institution
| Test | Details | Minimum Score |
| Accepted English Language Proficiency Assessment Test Scores | ||
| IELTS | 5.0 | |
| TOEFL IBT | 35 | |
| CLB | 5 | |
| CAEL | 30 | |
| Cambridge CAE | 154 | |
| PTE Academic | 40 | |
| Pearson Level Test | CEFR Level B1 | |
Gain a distinct advantage by earning industry-recognized certifications that validate your expertise and skills in key areas such as digital marketing, project management, and CRM. Our program prepares you to succeed, whether you're advancing, switching careers, or starting your own business. Invest in yourself and join a community of certified professionals shaping the digital economy.
Our extensive network and reputation for excellence ensure that graduates are in high demand in today's competitive job market. Prepare to excel in sought-after roles with renowned companies and unlock limitless career opportunities. Elevate your career trajectory and secure your future with our program tailored to meet the demands of industry leaders.
I'm very proud to have had a teacher who is as kind and available as mine was. He was very supportive of all of us in the classroom and helped us make our way throughout education.
Anthony M.
Technology Program Graduate
I had a very good experience with all of the staff at CDI College. They were all very helpful, especially my program instructors.
Ian M.
Technology Program Graduate
Cookies help us provide essential site features, understand visitor behaviour, customize content, and display targeted advertisements. To learn more, please review our Cookie Policy.
BC
