Deep Learning Bootcamp By NTU Graduate Students

Join us for an immersive learning experience designed by SCSE-GSC, IGP-GSC, MSE-GSC, and SPMS-GSC to deepen your understanding of Deep Learning. Our bootcamp consists of four in-depth sessions covering essential topics and practical applications, followed by an exciting Hackathon to put your newfound skills to the test.

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Bootcamp Sessions

1. Deep Learning Essentials

Get started with the fundamentals of Deep Learning. Explore key concepts, architectures, and understand the foundations that make Deep Learning a powerful tool in today's technological landscape.

2. Deep Learning for Regression and Classification

Dive into the application side of Deep Learning. Learn how to use Deep Learning models for regression and classification tasks, gaining hands-on experience with real-world datasets.

3. Deep Learning for Images

Uncover the secrets of working with image data in Deep Learning. From image recognition to convolutional neural networks (CNNs), this session will equip you with the skills to tackle image-related challenges.

4. Deep Learning for Sequence Data (Text and Time Series)

Extend your knowledge to sequential data, including text and time series. Explore the applications of recurrent neural networks (RNNs), Long Short-Term Memory networks (LSTMs), Large Language Models (LLMs) and dive into the world of natural language processing and time series analysis.

5. Hackathon

Apply what you've learned in a dynamic and collaborative setting. The Hackathon will challenge you to solve real-world problems using Deep Learning techniques. Work individually or in teams to showcase your skills and creativity.

To support your learning journey, we provide Jupyter notebooks with scaffold code for each session. Use these resources for hands-on practice during the bootcamp and keep them for future reference.

Ready to level up your Deep Learning skills? Secure your spot now and embark on this transformative learning journey with us!

Form your teams and put your skills to the test at the upcoming Hackathon! Refer to the Hackathon page for more information.