Data Analyst Diploma Program

Students who complete this course will have the information and skills necessary to interact with others in the workplace effectively and professionally. The use of technology to improve corporate communication will also be covered. Students will learn the fundamentals of speaking, writing, and giving formal presentations.

Students work with a professional career counsellor to develop and optimize a professional resume to put forward for employers. Additional support in job searching, interview techniques, and other career transition skills is offered to ensure students have the best possible work prospects.

Students will learn how to design and create dashboards. Students will develop the skills to create dashboards that best suit organizational and reporting requirements, develop effective data dashboards, and use dashboard technology effectively. Through efficient dashboard representations, students will have the abilities to support data analytics.

This Capstone Project course is the culmination of the Data Analyst Diploma program, designed to give students an opportunity to apply their knowledge and skills in a real-world scenario. The course is divided into 6 modules, each focusing on a critical phase of the data analysis process—from problem identification to data cleaning, analysis, and presentation. By the end of the course, students will have developed a comprehensive data analysis project, demonstrating their ability to solve complex business problems using data.

This course will develop the foundation on the process of data acquisition and storage. Students will be introduced to the processes of data collection, integration, storage, cleaning, de-duping and data security. They will also learn the concept of ethical collection, storage, and use of data.

This course will teach the skills to design & develop databases. Students will learn common models & structures and how to use them to design databases. They will learn different elements of databases and how to develop schema using those elements. Students will also learn different database structures, which can be used for Business Analytics/Business Intelligence.

This course explains the structure & role of data governance within an organization. Students will learn about data governance, the data governance board, board responsibilities, how the board looks at data as an important asset of the organization, how the board provides guidance & setup policies/procedures for the acquisition, storage, manipulation, cleansing, and quality of the data, and eventually how the business reports/decisions are made.

Students will learn the basics of data manipulation in this course. Students will learn scripting languages like Python and SQL as well as how to modify data in Excel. Students will have a thorough understanding of technology and methods used in data manipulation.

In this course, students will learn about various methods and approaches for data visualization. Students will build the ability to create data representations that efficiently meet organizational and reporting goals. They will also learn how to use data visualization technology effectively. Students will have the ability to assist data analytics through powerful storytelling and visualization.

This course will teach students the concept of Business Analytics/Business Intelligence (BI) and how this serves as a foundation for the data analysis profession. Students will learn how Business Analytics/Business Intelligence (BI) is used in different industries like healthcare, banking, education, and government. They will also learn different technologies used in this profession and will develop the skills to make intelligent decisions based on data analytics.

This course presents a brief introduction into the concepts of data analysis, the role of a Data Analyst in organizations, and the tools that are used to perform daily functions. Foundational knowledge in machine learning and artificial intelligence, including Deep Learning and Large Language Models (LLM) will be covered so students will develop a holistic understanding of the data environment and the fundamentals of data analysis. Students will learn the different skills required to become successful data analysts and develop a broad understanding of the profession.

Students will learn how to carry out tasks that are common to all Microsoft Windows apps in this course. The ability to build and alter Word, Excel, or PowerPoint programs; change how toolbars and other on-screen features are displayed; getting online help; and conducting file management, editing, formatting, and printing tasks typical of most Windows applications are all elements.

Students learn the techniques for creating powerful written and oral presentations in this course. The essential elements of creating compelling reports and presentations will be covered with the students. A range of technologies that can be utilized to support these tasks will be introduced to them. Students will acquire the basic abilities needed to share data insights with important audiences and stakeholders.

The Project Management Institute's Body of Knowledge, which defines the key knowledge areas of project management, is introduced to students in this course. The use of reporting tools and methodologies for descriptive and predictive analytics will be stressed in class.

Students who take this course will leave with a solid foundation in probability and statistics as they apply to data analytics. Students will improve their knowledge of descriptive and inferential statistics, sampling and probability, and statistical thinking. Students will learn how to apply statistical reasoning and inference to sets of data and compare the pros and cons of statistical and machine learning models.

Students will be introduced to Tableau basics, such as its features and dashboards, through this course. A comprehensive knowledge of dashboards will be provided to accelerate business performance with Tableau dashboards. Students will be taught advanced analytics and visualizations along with the processes to connect Tableau to different data sources and prepare data for better analysis.