Deep Learning Study Group 2024
We are thrilled to announce that the Deep Learning Study Group is back! Our community creates and curates the materials for you to dive into Deep Learning and introduce the new concepts of AI, and to get more hands-on experience!
This 12-week online study group is designed to fulfill the curiosity of those who want to improve themselves in Deep Learning and want to meet and study with like-minded people.
Starting from September 7, we will meet on Saturdays at 10.00 am to discuss our brand-new materials!
Note: BEV Foundation (inzva) reserves the right to change or modify any of the conduct, design, and rules of the program at any time and in their sole discretion.
This study group is open to anyone who is qualified to join and studies/lives in Turkey. The sessions will be held in Turkish while the materials will be provided in English. You should be comfortable with both languages to fully benefit from the program.
This batch, we have developed a brand-new curriculum, complete with bundles and notebooks for this study group!
The program will start with an introduction to Neural Networks and Deep Learning, continue with common tasks like Image Classification and Object Detection, and will conclude with more trend topics in deep learning such as Large Language Models and Generative Models. Throughout the program, participants will engage in two assignments and take part in a Kaggle challenge as their graduation project!
We expect participants to study the materials in advance and come prepared each Saturday, actively engaging in discussions. After 12 weeks, we will provide the course materials for your continued self-improvement!
WHAT'S NEW?
This batch, we will invite participants to our class on Google Classroom and share the brand-new materials and announcements on this platform. Between modules, you will have two assignments to complete via GitHub Classroom. Finally, in order to graduate, we will ask you to improve your skills by participating in one of the specified Kaggle challenges in groups. Additionally, we are planning weekday meetups, career meetups, and in-person events!
APPLICATION PERIOD
Application period is over, thank you for your interest!
July 27 - August 16, until 23.59
The results will be announced on August 27, until 23.59.
SCHEDULE and TOPICS
You can access the weekly schedule here. Please note that there may be changes to the program.
Module 01: Introduction to Neural Networks and Deep Learning
Week 1: Introduction to Neural Networks
Week 2: Hyperparameter Tuning and Regularization
Week 3: Optimization Algorithms
Module 02: Neural Network Architectures and Common Tasks in Deep Learning
Week 4-5: Convolutional Neural Networks with Common Tasks: Image Classification, Object Detection, Image Segmentation
Week 6-7: Recurrent Neural Networks with Common Tasks: Forecasting for Time Series
Week 8-9: Transformers with Common Tasks: Neural Machine Translation, Image Classification
Module 03: Trend Topics in Deep Learning: Generative Models and LLM's
Week 10: Generative Models (VAEs, Diffusion Models)
Week 11: Introduction to Large Language Models (LLMs)
Week 12: Graduation Project: Kaggle Challenges
Graduation Day: November 30!
Note: BEV Foundation (inzva) reserves the right to change or modify any of the conduct, design, and rules of the program at any time and in their sole discretion.
OUR GUIDES & CONTRIBUTORS
Our guides and contributors are all proud graduates of Deep Learning Study Group. This year, in leadership of our AI Team member Sarper Yurtseven, they have giveback their knowledge with a shared mission to enhance this study group. Berfin Duman, Berkin Deniz Kahya, Bike Sönmez, Emir Faruk Erman, Gürkan Soykan, İrem Zırhlıoğlu, Şafak Bilici, Sarper Yurtseven, Simge Şenyüz, Şilan Fidan Vural, and Tarık Can Özden have developed a wonderful new curriculum and materials to ensure an exceptional learning experience.
COMMUNITY FEEDBACK
Deep Learning Study Group 8 gave me an opportunity to combine peer learning with industry knowledge. Program schedule and following up regularly taught me to be a well-disciplined person. Pre-lesson and post-lesson assignments always kept my attention in this area. Especially, thanks for the guides and their enthusiastic efforts to teach us. Their energy and motivation were unbelievable. Our deep learning journey with them has taught me the fundamentals and how to properly maintain a deep learning project. Besides these, I had a chance to enlarge my network by meeting new people in this area. I am so glad to be a part of inzva family and look forward to joining your other programs as soon as possible.
In the Deep Learning Study Group, we obtained valuable knowledge on fundamentals of deep learning theory and discovered the practical uses of the current studies. We got the chance to test ourselves on these topics with a series of homeworks. Also, by practicing the notebooks, we gained hands-on coding experience. The program is well organized and progressive, live sessions were very interactive and guides were enthusiastic. In the sessions, as a group, we exchanged ideas on various Deep Learning topics such as Convolutional Neural Networks (CNNs), Natural Language Processing (NLP) and Network optimization and regularization techniques. When you graduate from Deep Learning Study Group you will not only become a capable deep learning practitioner, but also meet great people sharing common interests with you. I am glad to be a part of the inzva family!
OUTCOMES
Experience for the first time the brand new curriculum curated by the experienced team of the inzva community, all of whom have graduated from this program.
Acquire state-of-the-art, domain-specific training.
Gain experience on competing in Kaggle challenges.
Learn from experienced guides and peers in the field of computer science.
Join discussions about different ways to approach a problem.
Opportunity to meet like-minded students and professionals, through online meetings and face-to-face events.
Join the private channel for the program on inzva’s Discord server and become a part of inzva AI community after the graduation.
EXPECTATIONS
Successfully answering the application form questions.
Consistent attendance to the weekly lectures (at least %80).
Studying the materials before the class and being an active listener and attending the discussions is essential for your learning journey.
Being responsive to emails and announcements.
Completing assignments and quizzes by the deadline.
Attending and submitting to Kaggle challenges.
Following the rules of our community.
Please note that failure to meet these requirements will result in your disqualification from the program.
TECHNICAL REQUIREMENTS
Programming experience: The course is taught in Python. We assume you have basic programming skills (understanding of for loops, if/else statements, data structures such as lists and dictionaries).
Mathematics: Basic linear algebra (matrix-vector operations and notation), calculus and probability theory.
Machine Learning: Conceptual knowledge of machine learning (supervised learning, unsupervised learning, test data, validation, some machine learning algorithms such as linear regression, logistic regression).
Please have a Python environment (i.e. Anaconda) ready on your computer before coming to the program. You will find the instructions here.
FREQUENTLY ASKED QUESTIONS
Please check out the Frequently Asked Questions here.
For further questions, you can reach us at ai@inzva.com.
All participants have to abide by our CODE OF CONDUCT and LETTER OF CONSENT.
A BEV Foundation project inzva is a non-profit hacker community organizing study and project groups as well as camps in the fields of AI and Algorithm; and gathering CS students, academics, and professionals in Turkey.
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