Graduate Certificate in AI Applications for Data Mining and Engineering
Graduate Certificate in AI Applications for Data Mining and Engineering
Overview
As artificial intelligence (AI) and machine learning (ML) become ubiquitous across industries, workers at all levels are seeking practical knowledge about AI: its implications, limitations, and uses across various domains. Northeastern’s Graduate Certificate in AI Applications for Data Mining and Engineering is designed for professionals seeking to harness the power of AI within their respective industries who may not have prior programming experience.
The program will introduce AI tools, explore how to use AI responsibly, analyze the foundational principles of human-centered AI, and introduce data mining concepts and statistics/machine learning techniques for analyzing and discovering knowledge from large data sets.
Innovative Curriculum
Students from a broad spectrum of academic and professional backgrounds will gain a comprehensive understanding of AI fundamentals and learn effective ways to apply AI applications to their own contexts and products. Through a blend of theoretical knowledge and practical skills development, students will be equipped with the tools to make informed decisions about when and how to leverage AI technologies. By the end of the program, students will gain skills in leveraging AI technologies responsibly, ethically, and effectively within their organizations. They will be equipped to advocate for the responsible use of AI and mitigate risks associated with AI deployment while also understanding the human-centered aspects of AI development and implementation.
Students in the AI Applications for Data Mining and Engineering track will be introduced to data mining concepts and statistics/machine learning techniques for analyzing and discovering knowledge from large data sets in engineering domains such as manufacturing, healthcare, sustainability, and energy. Drawing from data mining case studies, students will explore data reduction, data exploration, data visualization, concept description, mining association rules, classification, prediction, and clustering.
Locations
This program is available at the Boston and Silicon Valley campuses.
Unique Features
- Alignment with job functions and career opportunities: Northeastern’s program bridges the gap between theory and practice, emphasizing the practical applications of AI within various professions and industries. Through real-world case studies and industry collaborations, learners develop the knowledge and skills to effectively apply AI technologies in their respective fields, driving tangible results and advancements in industry.
- No programming experience required: Northeastern provides a diverse range of AI education opportunities tailored to learners with varying backgrounds and levels of experience. The Graduate Certificate in AI Applications is designed for learners with little to no programming experience seeking to harness the power of AI within their discipline.
- Real-world application through domain-level specializations: Northeastern prioritizes experiential and practice-based learning to prepare students for successful careers in AI. Through its renowned co-op and externship programs, students gain hands-on experience and exposure to real-world AI applications use cases based in their field of interest
- Credit-bearing pathways to advance your career: The Graduate Certificate in AI Applications is a credit-bearing graduate certificate with seamless on-ramps to various MS degree pathways. Incrementally advance your education with valuable credentials that immediately help you move forward in your career.
- Expert career guidance and professional networking: Leverage career coaching, resume optimization, career fairs, and networking events offered through Northeastern’s Institute for Experiential AI and Career Design Support resources.
Program Objectives
- Identify AI tools that can improve business or operational practices through applying a human-centered approach.
- Identify potential risks and benefits of using AI.
- Problem solve for AI-related issues and identify potential solutions.
- Exhibit awareness of known biases in AI systems and propose steps for mitigation and correction.
- Analyze and understand basic concepts in statistics and machine learning.
- Learn the fundamentals of data mining and learn components of data mining algorithms.
- Perform data mining tasks on specific applications.
Academic Advising
We have a variety of advisors to help make your graduate career a success, so use the link below to determine which one will help you the best.
Admissions & Aid
Ready to take the next step? Review degree requirements to see courses needed to complete this degree. Then, explore ways to fund your education. Finally, review admissions information to see our deadlines and gather the materials you need to Apply.