糖心Vlog

Apply data-driven and AI-enabled approaches grounded in appropriate analytical techniques to support decision-making while implementing data governance, privacy/security controls, and responsible-AI practices across global contexts.

Evaluate and apply information policies, laws, and standards to support ethical technology use and equitable access to information and technology. 

Assess the information needs of communities and design inclusive and accessible programs, resources, and services to address varied community needs.

Design and architect complex software systems using established architectural models, design principles, and AI-assisted development practices. 

Analyze existing software systems and evaluate architectural trade-offs with respect to quality attributes, including performance, maintainability, and scalability. 

Make and justify software design decisions using systematic reasoning and quality attribute analysis.  

Apply advanced software engineering methods and quality assurance techniques to the development and evolution of industrial-scale software systems. 

Deliver a substantial real-world software project, integrating human-centered judgment with AI-enhanced engineering tools. 

analyze a problem and identify and define the use of artificial intelligence and/or machine learning (AI/ML) as appropriate to its solution

interpret and communicate the output of statistical and algorithmic methods

function effectively on a team to design and implement a computer-based AI/ML system

understand the implementation and use of AI/ML tools and systems

apply mathematical foundations, algorithmic principles, and computational knowledge in the modeling and design of AI/ML systems in a way that demonstrates comprehension of the tradeoffs involved in design choices

design, implement, and evaluate a computer-based AI/ML system, process, component, or program to meet desired needs

present material based on existing research papers in the field of artificial intelligence

present material based on their own research findings

Use data to provide quantitative insights on questions of scientific, organizational, and social interest.

Collaborate, communicate, and function effectively on data science projects in multidisciplinary teams.

Apply knowledge of Data Science (DS) fundamentals to analyze and solve complex problems.

Identify, formulate, and design efficient and effective solutions using appropriate DS processes and paradigms.

Design, implement, test, and maintain different DS components, systems, or programs to meet desired needs.

Identify, formulate, and solve DS problems with the techniques, skills, and modern DS tools necessary in practice for application domains.

Engage in continuous learning to keep pace with evolving tools, technologies, and methodologies in DS

Analyze and evaluate algorithms based on theoretical foundations for varied computational environments.

Employ appropriate tools and methods to write, read, and analyze computer code in a variety of programming languages.

Define, implement, test and maintain software components and systems to meet diverse functional and deployment specifications.

Apply computer science principles and practices to solve a broad range of computational problems.

Employ human-centered methods and processes for human needs and values by incorporating accessibility principles and ethical considerations across all stages of design.

Select and apply qualitative and quantitative research methods to address user experience needs across various design contexts.

Incorporate new interaction paradigms and novel approaches at the frontiers of human-computer interaction that address problems in applied domains. 

Apply fundamental knowledge of concepts related to human cognitive, affective, and social in the context of technologies and systems to determine design opportunities, risks, and constraints.

Design artifacts, processes, systems, and user interface prototypes using a variety of tools at different levels of complexity and fidelity.