Schoolhouse.world: peer tutoring, for free.
Schoolhouse.world: peer tutoring, for free.
Schoolhouse.world: peer tutoring, for free.
Introduction to Deep Learning

SAT Score Range

2 sessions

About

Session introduces the fundamentals of deep learning, neural networks, and major model types (CNNs, RNNs, Transformers, Autoencoders). Learners will engage through guided questions, a short neural network design activity, and a live coding walkthrough demonstrating how an image classification model works in practice.


Tutored by

Dwij V 🇮🇳

Certified in 2 topics

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I'm a high schooler from India. I’m a motivated learner with a strong interest in mathematics, problem-solving, and analytical thinking. I enjoy breaking down complex concepts into clear, logical steps and helping others build confidence through understanding rather than memorization. I’m joining Schoolhouse to both sharpen my own foundations and contribute by supporting peers in structured, concept-driven learning. I value discipline, consistency, and depth, and I believe collaborative learning is one of the fastest ways to grow intellectually while giving back to a serious academic community.

✋ ATTENDANCE POLICY

Students must join the session on time and remain present for the full duration. Active participation is expected during questions, discussions, and the neural network design activity. Repeated late arrivals, extended inactivity, or leaving early without notice may lead to removal from the session.

SESSION 1

12

Mar

SESSION 1

Study Spaces

Study Spaces

Thu 7:00 AM - 8:00 AM UTCMar 12, 7:00 AM - 8:00 AM UTC

This series introduces the foundations of deep learning and neural networks. Participants examine how models learn from data, explore major architectures such as CNNs, RNNs, Transformers, and Autoencoders, and analyze real-world applications.
SESSION 2

13

Mar

SESSION 2

Study Spaces

Study Spaces

Fri 7:00 AM - 8:00 AM UTCMar 13, 7:00 AM - 8:00 AM UTC

Additional to the 1st session, this session will indulge in engagement including guided discussion, conceptual network design exercises, and a short coding demonstration of an image classification model.

Public Discussion

Please log in to see discussion on this series.

Mar 12 - Mar 13

1 week

60 mins

/ session

Next session on March 12, 2026

SCHEDULE

Thursday, Mar 12

7:00AM

Friday, Mar 13

7:00AM