Advanced Certificate in Data Science
Advanced Certificate in Data Science
In the swiftly evolving landscape of technology, data science skills are increasingly indispensable, particularly with the rapid advancements in artificial intelligence. Professionals across diverse sectors—including finance, business, journalism, healthcare, and education—are discovering that data science can profoundly enhance their analytical capabilities and decision-making processes. However, many professionals lack the opportunity to engage with this burgeoning field, which can be approached without intensive mathematical or programming prerequisites.
The Advanced Certificate in Data Science is designed to bridge this gap by providing an accessible, practical introduction to the essentials of data science. Our program focuses on core foundational knowledge and practical tools, enabling participants to effectively apply data science methodologies in various real-world scenarios. This targeted approach empowers professionals to leverage data-driven insights within their existing roles or transition to new positions in the dynamic field of data science.
Offered in a flexible online format, this program caters to the varied schedules of working individuals, allowing them to acquire critical data science competencies without disrupting their current professional engagements. It provides a vital educational pathway for those looking to enrich their skill set or explore new career opportunities in data science.
Educational Objectives
Our educational objectives are meticulously designed to equip students with a robust foundation in data science principles, complemented by practical skills immediately applicable in the workplace:
Foundational Knowledge: We aim to provide a solid grounding in the fundamental concepts of computer science and statistical analysis. Our approach utilizes intuitive visualizations and basic coding to enhance understanding, ensuring students grasp the core methodologies that underpin data science.
Data Processing and Visualization: Students will develop proficiency in modern data processing and visualization tools, including the use of Tableau for creating impactful visual representations and actionable insights. This training enables them to effectively transform raw data into coherent and visually engaging outputs.
Practical Data Science Skills: Our program emphasizes the teaching of practical skills in data mining and data engineering, using industry-standard tools such as Rapidminer. This focus ensures that graduates are well-prepared to effectively handle real-world data tasks and make significant contributions within various industries.
Program Learning Outcomes
Upon successful completion of this program, graduates will be able to:
Apply Fundamental Concepts: Utilize basic principles of computer science and statistics to solve data-related problems, minimizing the reliance on extensive programming.
Master Data Analysis and Database Tools: Employ modern tools such as R, Tableau, and Rapidminer for data analysis, and apply database management skills to create effective visual representations, develop predictive models, and manage data efficiently.
Implement Machine Learning and AI: Understand and apply machine learning and artificial intelligence concepts, preparing for their advanced applications across various sectors.
Gain Project Management Experience: Acquire practical experience by efficiently managing real-life data projects through all stages of the data lifecycle.
Career opportunities
Graduates of the Advanced Certificate in Data Science program will find themselves well-prepared to enhance their roles in their current fields or to step into new positions across diverse industries. Career paths may include data analyst, data consultant, business analyst, and roles in data-driven decision making. Additionally, the practical skills acquired through the program prepare graduates to tackle roles that require the application of data visualization, basic data engineering, and machine learning, broadening their employment opportunities in the burgeoning field of data science.
Our educational objectives are meticulously designed to equip students with a robust foundation in data science principles, complemented by practical skills immediately applicable in the workplace:
Foundational Knowledge: We aim to provide a solid grounding in the fundamental concepts of computer science and statistical analysis. Our approach utilizes intuitive visualizations and basic coding to enhance understanding, ensuring students grasp the core methodologies that underpin data science.
Data Processing and Visualization: Students will develop proficiency in modern data processing and visualization tools, including the use of Tableau for creating impactful visual representations and actionable insights. This training enables them to effectively transform raw data into coherent and visually engaging outputs.
Practical Data Science Skills: Our program emphasizes the teaching of practical skills in data mining and data engineering, using industry-standard tools such as Rapidminer. This focus ensures that graduates are well-prepared to effectively handle real-world data tasks and make significant contributions within various industries.
Upon successful completion of this program, graduates will be able to:
Apply Fundamental Concepts: Utilize basic principles of computer science and statistics to solve data-related problems, minimizing the reliance on extensive programming.
Master Data Analysis and Database Tools: Employ modern tools such as R, Tableau, and Rapidminer for data analysis, and apply database management skills to create effective visual representations, develop predictive models, and manage data efficiently.
Implement Machine Learning and AI: Understand and apply machine learning and artificial intelligence concepts, preparing for their advanced applications across various sectors.
Gain Project Management Experience: Acquire practical experience by efficiently managing real-life data projects through all stages of the data lifecycle.
Graduates of the Advanced Certificate in Data Science program will find themselves well-prepared to enhance their roles in their current fields or to step into new positions across diverse industries. Career paths may include data analyst, data consultant, business analyst, and roles in data-driven decision making. Additionally, the practical skills acquired through the program prepare graduates to tackle roles that require the application of data visualization, basic data engineering, and machine learning, broadening their employment opportunities in the burgeoning field of data science.
Admission Requirement and Process
To qualify for admission, applicants must satisfy the following criteria:
- Hold a Bachelor's degree before the start of the intended enrollment term.
- Demonstrate English proficiency through one of these methods:
- Submit official scores from recognized English language tests like TOEFL, IELTS, Duolingo, or equivalent.
- Earn a degree from an institution where English is the primary language of instruction.
Applicants must also submit a complete application package in accordance with the college’s standard admission procedures. Learn More
Completion Requirements
The Advanced Certificate in Data Science program comprises five core courses. To successfully complete the program, students must achieve a grade of C or higher in each course.
Curriculum and Course Description
Completion Requirements
The Advanced Certificate in Data Science program comprises five core courses. To successfully complete the program, students must achieve a grade of C or higher in each course.
Total Required Credits for Graduation (15 credits)
Total Required Credits for Graduation (15 credits)
Credits: 3
Exploring key mathematical concepts, this course equips students with the essential mathematical foundations for data science, including linear algebra, basic statistics, and optimization techniques. Emphasis is placed on practical computational and visualization programming exercises to solidify understanding and relevance in real-world applications.
Credits: 3
Throughout this course, students delve into data structures, database fundamentals, and essential data management and querying tools like SQL. By solidifying Python programming skills and introducing data structure analysis and computational complexity, the course prepares students for complex computational challenges in data science.
Credits: 3
This course prepares students to understand and leverage data mining and predictive modeling in business contexts. By using Python and PyTorch, and tackling real-world datasets, students gain practical skills that culminate in comprehensive projects designed to solve actual business problems.
Credits: 3
Students will learn the art and science of converting data into graphical representations that make complex information accessible and actionable. This course covers the basics of R programming, data cleaning, transformation techniques, and the use of Tableau for creating compelling dashboards. The curriculum is designed to help students master the skills needed to present data in visual formats that reveal patterns, trends, and correlations.
Credits: 3
A cornerstone of the Data Science Master’s Program, this course introduces advanced machine learning algorithms’ theoretical foundations and practical applications. Students engage with logistic regression, decision trees, support vector machines, and deep learning, applying these techniques to real-world data tasks.
Faculty Highlights
Meet our distinguished faculty members who are leading experts in their respective fields
