ApplyWe re-create the learning environment and rigour of the world’s most renowned and elite institutions. Top professors teach you. World class TAs mentor you.
At Univ.AI, we do absolutely everything LIVE.
*The Geoffrey Hinton Fellowship (GHF) is currently open to only Indian participants only. We will launch the fellowship for international participants soon.
Professors teach in a series of short 20–30 minute segments, with exercise and quizzes between segments. The system ensures high-comprehension and high-retention learning. A lecture session comprises 2–3 such segments.
Each segment is followed by a quick problem-solving exercise, supervised by a teaching assistant (TA), or an in-class quiz. Even during class, help is always on-hand to ensure you have conceptual clarity.
TAs conduct highly interactive, hands-on labs, once or twice a week. Labs greatly accelerate learning by providing a structured and mentored environment to get started on new ideas and concepts learnt in preceding classes.
The learning experience during a Lab is further enriched by a peer-learning environment guided by a TA. Students enjoy sharing learnings with one another, and collectively learn quicker during these sessions.
Homework assignments comprising larger, more complex problems are ideal follow-ups to the exploration of new concepts and ideas that the learners get started with during their labs. Typically, homework is done in groups.
Students build on the peer-learning in labs to work-together in groups on homework assignments. This results in superior work, significantly increased comprehension of key ides, and greater facility at hands-on problem solving.
TAs and faculty conduct office hours to address specific questions regarding concepts, labs, and homework. These live, high-contact interventions ensure that students have conceptual clarity at every step of their learning journey.
TAs are also available to guide students via conversations on discussion boards outside of their stipulated hours. Such discussions add greatly to the learning experience, when combined with the immediate guidance available from frequent live sessions.
In the final week of every 5- to 6-week course, students work on a complex, hands-on project that challenges them to apply their learnings to a real-world problem in Data Science and Machine Learning. Students work in small Groups and learn to address complexity by breaking down different parts of a problem into simpler units. They learn to make real-world trade-offs to reach solutions.
Projects train students to apply their learnings in work-settings and become “production-ready.” They are carefully evaluated and become part of a student’s long-term repository at Univ.AI.
Rigorous, multi-dimensional evaluation is a cornerstone of our program. Your grade is a weighted average of your scores in different work-sections. Program grades are calculated by averaging course-grades. A typical representation of evaluation weightages is illustrated here.
We have a 2-tier certification system:
A course-wise grade report is included in your evaluation
