Applied AI for Product Development & Innovation
About This Course
Designed for professionals in the Product Development track, including Product Managers, Product Designers, and Product Analysts, this intermediate course provides the skills to strategically integrate Artificial Intelligence (AI) into the product lifecycle. Participants will gain hands-on experience in mastering the end-to-end AI workflow, from managing and preparing data to building, deploying, and managing machine learning models using Machine Learning Operations (MLOps) principles. The course also emphasizes innovation by guiding learners to identify high-impact use cases, design AI-enabled features, and apply emerging technologies to enhance product value. Learners will apply frameworks for experimentation and continuous improvement to validate AI features and support data-driven innovation within their
organisations.
What You'll Learn
Implement ETL transformation pipelines using data modeling and schema mapping with SQL/NoSQL databases to ensure interoperability of heterogeneous sources in AI development.
Apply exploratory data analysis (EDA) and data sampling techniques using data science libraries to clean and prepare datasets for AI model development.
Implement model inference APIs with managed ML platforms and API frameworks to enable efficient development of AI-enabled applications.
Implement model monitoring workflows that use statistical drift detection and visualize metrics on dashboards to improve the performance reliability of AI models in production.
Implement pre-defined AI deployment workflows using CI/CD pipelines and container orchestration tools in staging and production environments to support timely product launches.
Entry Requirements
To ensure learners can meet the learning objectives and workplace application of this course, the following minimum entry requirements have been established:
Work Experience: Applicants should be currently working in the Product Development track in roles such as Associate Product Manager, Associate Product Designer, Associate Product Analyst, Lead Product Manager, Lead Product Designer, Lead Product Analyst, Product Manager, Product Designer, and Product Analyst.
Educational Qualification: Learners should possess a minimum of a Bachelor's Degree or its equivalent.
Technical Prerequisites: A demonstrable understanding of basic programming logic is required. Familiarity with Python is highly recommended as it will be used in the hands-on sessions.
Language Proficiency: Learners must have a level of English proficiency sufficient to actively participate in technical discussions, comprehend instructional materials, and communicate findings in written and spoken formats.