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Practical Engineering Data Mining: Techniques and Uses

This course delves into both the theoretical aspects and practical applications of data mining within the field of engineering. It provides a comprehensive review of the essential fundamentals and central concepts underpinning data mining. Additionally, it introduces pivotal data mining methodologies and offers a guide to executing these techniques through various algorithms. Students will be introduced to a range of data mining techniques, such as data preprocessing, the extraction of association rules, classification, prediction, clustering, and the exploration of complex data, and will implement a capstone project exploring the same. Additionally, we will use case studies to explore the application of data mining across diverse sectors, including but not limited to manufacturing, healthcare, medicine, business, and various service industries.
Duration 4 Months
Institution Northeastern University
Format Online

Eligibility Criteria

school

Academic Foundation

A recognized Bachelor’s degree or high school equivalent required for admission into Northeastern University.

language

Language Proficiency

English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.

Detailed Fees Breakdown

Base Tuition Fee $207
Total Est. Investment $207

Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.

Academic Trajectory

Program Outcome

Graduates of the Practical Engineering Data Mining: Techniques and Uses program at Northeastern University are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.

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