Lawyers and researchers are using computers to mine a variety of legal documents. This is changing the way lawyers work. Now, instead of guessing the likely outcome of a case, computers are able to predict results. Attorneys can use this information to inform their approach to working a case. A certificate in Legal Analytics prepares students to use technology in the workplace.
We are living in a time of revolutionary change in the way that the law is studied and practiced. Legal scholars, lawyers, data scientists and tech entrepreneurs are using machine learning, natural language processing, programming and high-performance computing to analyze legal documents in completely new ways. The demand for these skills is high. Students who are familiar with the tools of legal analytics can better prepare themselves for a lasting legal career with this certificate.
What is Legal Analytics?
The field of legal analytics uses computing power to analyze text from legal documents, treating words more like numerical data. Computer algorithms, combined with the knowledge of data scientists and lawyers, can provide insights about what happened in the past and what may happen in the future.
Students pursuing a certificate in Legal Analytics have the opportunity to participate in a number of research, experiential learning and extracurricular activities.
- Research: The Legal Analytics & Innovation Initiative also works with external partners in the legal community to put legal analytics advances into practice, develop new learning opportunities and share cutting-edge research insights.
- Hands-on Learning: Students can take part in workshops and training sessions hosted at the College of Law or Robinson College of Business. There are also opportunities to work with clients, serve as a graduate research assistant and pursue summer internship placements at firms that are using this technology.
- Legal Analytics Lab: In the Legal Analytics Lab at the J. Mack Robinson College of Business Institute for Insight, faculty, students and corporate partners use the tools of big data analytics to produce original research.
- Students learn to identify patterns, using big data analytics, including text mining, machine learning, image analysis and other methodologies to produce research. They unlock insights from thousands of pages of text, using computational techniques.
- They work with faculty, law firms and companies to help organizations examine predictive results from volumes of documents and other data.
- Research quantifies types and frequency of case outcomes with hopes of revealing predictive behavior and outcomes.
- Students examine analytics tools to leverage emerging technologies in law practices as informed consumers and competent technology partners.
Students must be in good academic standing, based on the successful completion of the first full year of law study (30 hours), to participate in the certificate program. Students must remain in good standing to continue program participation.
Required Courses (15 credit hours)
- LAW 7674 Legal Analytics I (3 credits)
- LAW 7675E/MSA 8350 Legal Analytics II (3 credits, experiential)
- LAW 7676E Applied Legal Analytics Lab (3 credits, experiential)
J.D. students with prior mathematics/computer programming background:
- Any two MSA-prefix courses, chosen in consultation with the student’s faculty advisor and LAII faculty. MSA courses may have their own prerequisites in addition to foundational math and computer science courses.
J.D. students without a strong math and programming background:
- MATH 7100– Basic Math for Analytics (1.5 credits)
- CSC 2032– Programming Foundations for Analytics (1.5 credits)
- MATH 7110 -Mathematical Foundations for Analytics (3 credits)
Foundation courses: The Executive Director, in consultation with the LAII Faculty Director and others, will determine whether a Certificate student is required to take the foundational math and programming courses. That decision is final.
Non-law courses and credits: J.D. law students are only eligible to count six hours of non-law school classes toward the 90 credits required to graduate. The student must obtain a grade of “B” or better in non-law school classes in order to count them toward graduation. Students may take additional non-law classes while enrolled; credits exceeding 6 hours, however, will not count towards law school graduation.
Elective Courses (minimum of 6 credit hours)
- LAW 7139– e-Discovery
- LAW 7050– Advanced Legal Research
- LAW 7137– Cyberlaw
- LAW 7631– Contract Drafting & Risk Analysis
- LAW 7138– Computers and the Law Seminar
- LAW 7136– Complex Litigation
- LAW 7336– Fundamentals of Law Practice
- LAW 7293– Seminar on Judicial Power (Corpus Linguistics)
- LAW 7355– Law and Emerging Technologies
- LAW 7632– The Role of In-House Counsel
- LAW– Legal Tech. Competency & Operations
- Additional approved electives
Legal analytics is a new and growing field. The list of eligible electives for students will be updated as new courses are developed or existing courses are dropped or changed and the LAII reserves the right to change the list of courses if required.
project will meet the writing requirement for this program.
- workshops and boot camp training sessions hosted at the College of Law or Robinson College of Business,
- participate in additional client-focused data projects (“sprints”),
- work with affiliated faculty as a GRA,
- and pursue internship placements as they become available
Grades and Honors
Honors will be awarded for achievement of a GPA of 3.6 or higher in all Legal Analytics & Innovation courses taken for the certificate and any additional Legal Analytics & Innovation electives taken above and beyond the requirements. If you do not pass a course taken toward the certificate and you retake the course, both the failing grade from the first attempt and the passing grade from the second attempt will be calculated in the GPA, and you must still maintain a 3.6 to receive honors in the certificate program.
To graduate with a certificate, students must submit a Verification for Certificate in Legal Analytics for review no later than the end of the drop/add period of a student’s last semester prior to graduation. The form must be signed by the student’s academic advisor.
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