#2nd worldwide
Business Analytics, QS Rankings (2018)
The PGP-AIML (Advanced) is a follow-up program to the PGP-AIML, designed to cover advanced concepts in the domains of Machine Learning, NLP, Neural Networks, and Computer Vision. It is suited for:
A current participant of the PGP-AIML program.
Professionals who are familiar with the basics of ML, NLP, Computer Vision & Neural Networks.
Ranked #2 worldwide in Analytics and Ranked #8 in Artificial Intelligence
Live and interactive learning in small groups
Learn advanced concepts of ML, NLP, Computer Vision & Neural Networks
All certificate images are for illustrative purposes only. The actual certificate may be subject to change at the discretion of the University.
H. Timothy (Tim) Harkins Centennial Professor Faculty Director, Center for Research and Analytics
MS & PhD: Stanford University
A structured 3.5-month online program with hands-on projects and mentor-led sessions on weekends
Access best-in-class recorded content from UT Austin faculty, global academicians and accomplished industry experts.
Apply your skills in real-time as you work end-to-end on 4 hands-on projects, focused on real-world business problems.
Practice on data sets and gain practical insights from leading data science & analytics professionals in live sessions.
Self-learning online can be difficult.
Our mentored learning model brings you 2 hours of live and
interactive mentor-led sessions every weekend in groups of 10 learners (micro-class).
Mentors are:
Each module has recorded content that is followed by a session with one of our distinguished industry mentors, in a small group of participants. These mentors are thought leaders in different domains with several years of industry experience that enables them to impart practical knowledge and real-world insights.
Participate in monthly webinars with leading UT Austin faculty to learn the applications of AI & ML to different industries through case studies and live examples.
Interspersed throughout the program, the 4 hands-on projects help you learn the real-world applications of concepts by applying them to real-world business problems.
Prepare for a successful career transition through career guidance by industry practitioners, focusing on resume and LinkedIn profile review, interview preparation and 1:1 career coaching.
As you complete your experiential projects, we will automatically create a document to showcase your learning & projects in a snapshot that we call an ePortfolio. This can also be easily shared on social media channels to establish your credibility in Artificial Intelligence & Machine Learning with potential employers.
The PGP-AIML (Advanced) curriculum has been carefully designed by UT Austin faculty and leading industry experts to help you master advanced AI and Machine Learning concepts in 4 key areas.
Learn from leading academicians in the field of Artificial Intelligence and Machine Learning and several experienced industry practitioners from top organizations. An indicative list of Artificial Intelligence and Machine Learning experts engaged with us include:
MS & PhD: Stanford University
H. Timothy (Tim) Harkins Centennial Professor,
Faculty
Director, Center for Research and Analytics, McCombs, The University of Texas at Austin
MS: The University of Texas at Austin
Director and Lecturer at The Center for Analytics and Transformative Technologies,
McCombs School of Business
PhD: Carnegie Mellon University - Tepper School of Business
Associate Professor,
McCombs School of Business
PhD: University of Arizona
Associate Dean for Instructional Innovation,
McCombs School of Business
PhD Statistics: Stanford University, M.Stat: Indian Statistical Institute
Academic Director, Data Science & Machine Learning
PhD: Max Planck Institute, Germany,
Post-doctoral: New York University
Faculty, Deep Learning and Computer Vision
MS & PhD: University of Illinois at Urbana-Champaign,
BTech: Indian Institute of Technology, Delhi
Faculty, Image Processing and Machine Learning
Machine Learning Developer at SAP
Resident Data Scientist at OfferZen
Program Manager – Data Science at Microsoft
Data Scientist at Mercedes-Benz
Register by filling up the online application form >
A program advisor is assigned to assist you through the selection process and answer all your questions.
A panel will review your application to determine your fit for the program. The panel will evaluate you on your work experience, past academic credentials and motivation for joining the program.
If shortlisted, you will go through a telephonic interview (this may be waived for candidates with strong profiles and experience).
After a final admissions committee and faculty review, if selected, you will receive an ‘offer of admission’ letter for a seat in the upcoming cohort of the program.
Candidates can pay the program fee through
Tuition Fee
Learning Material
Mentorship Sessions
We follow a rolling admission process and admissions are closed once the requisite number of participants enroll for the upcoming cohort. So, we encourage you to apply early to secure your seat.
Apply Now
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