- Requires a prerequisite course
This micro-course can be applied toward the AI Skills Accelerator for IT, Digital and Enterprise Systems Professionals and is the introductory level 2 micro-course in the AI and Data Literary track.
Building on foundational data literacy, this proficiency level micro-course empowers IT professionals to implement advanced data strategies for AI applications. Develop practical skills in data pipeline design, advanced analytics implementation and data governance while learning to manage complex data workflows that support enterprise AI initiatives.
By the end of this course, you will be able to:
- Design and implement comprehensive data pipelines for AI applications
- Establish data governance frameworks and quality assurance protocols
- Integrate multiple data sources using advanced API and orchestration techniques
- Deploy and manage enterprise-scale ML platforms and data infrastructure
- Apply advanced statistical modeling and analytics techniques to complex datasets
- Implement data security and privacy controls for AI systems
- Lead cross-functional teams in data-driven AI initiatives
- Optimize data processing performance and plan for enterprise scalability
Platform and tool selection varies and is regularly updated to reflect current industry trends. Students can expect to interact with:
- Advanced data pipeline tools (Apache Airflow, Azure Data Factory, AWS Glue)
- Enterprise machine learning platforms (Databricks, Azure Machine Learning, AWS SageMaker)
- Data governance platforms (Collibra, Apache Atlas, Microsoft Purview)
- Advanced analytics tools (Python with pandas/scikit-learn, R, Spark)
- API orchestration and integration platforms
- Data security and privacy management tools
Course outline
- Module 1: Advanced data pipeline design and management
- Module 2: Data governance and quality frameworks
- Module 3: Advanced API iIntegration and data orchestration
- Module 4: Enterprise machine learning platform implementation
- Module 5: Advanced analytics and statistical modeling
- Module 6: Data security and privacy in AI systems
- Module 7: Cross-functional data team leadership
- Module 8: Performance optimization and scalability
How am I assessed?
You will be assessed on successfully completing weekly activities, including exercises, quizzes, applied case study projects (based on real-life scenarios) and your contributions to discussion posts. These activities are marked using a proficiency scale, and your instructor provides you informal feedback during live online sessions.
While you are not assessed on your attendance of the live online sessions, we encourage you to attend so you can learn and interact with your instructor and other participants. All sessions are recorded in case you miss one.
This micro-course operates on a pass/fail basis. You must achieve an overall grade of 70% or greater to pass and be eligible to earn the UBC Certificate in AI Skills Accelerator for IT, Digital and Enterprise Systems Professionals.
Expected effort
Expect to spend approximately 14 hours per week per course completing all learning activities, including attending live sessions online.
Requisites
Completion of AI and Data Literacy 1: Foundations
Course format
This 100% online part-time program consists of instructor-supported real-time classes combined with independent study.
Each micro-course will consist of a weekly virtual class taught by subject matter experts and a high degree of personal engagement and interactivity. Outside of class, you can access online materials on your own time.
One business day before the micro-course start date, we’ll email you step-by-step instructions for accessing your micro-course.