Applied AI Study Group #10
We are excited to announce Applied AI Study Group #10!
If you are eager to learn how Artificial Intelligence applies to real-world scenarios, understand its business implications, explore models in computer vision and natural language processing, gain hands-on experience, and connect with an AI-enthusiast community, you're in the right place!
Applied AI Study Group is designed to get the skills needed to apply AI models in real-world scenarios, which will allow us to demonstrate our work and its practical applications, and discuss the most up-to-date arguments.
Starting from April 11, we will meet online for 7 weeks. Additionally, we will have 5 online lab sessions on weekdays to get our hands dirty.
Watch our webinar for the 7th batch to learn more about us!
APPLICATION PERIOD
The application period consists of two parts;
1- First, you need to fill out the application form until March 24: APPLY
We will announce the first stage results on February 14, until 23:59.
2- The second stage will be an online interview, which may include follow-up questions based on your responses to the technical questions. You will receive a detailed email about the interview after you pass the first stage.
We will inform you about the second stage results by April 9, until 23.59
The first session will be on April 11, 10 pm
Note that the sessions will be held in Turkish.
Discover the previous Applied AI Study Group's journey in our report.
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.
SCHEDULE
Kick-off and Machine Learning in Business
Week 1: April 11
Week 2: April 18
Introduction, meeting and kick-off!
Ece Özen İldem Beyza Nur Şenol
ML in Business Guide Lab Sessions Guide
In these weeks, we explore how Machine Learning can bring value to businesses. Throughout the section, we will discuss various topics related to ML engineering and its practical applications in the industry.
Natural Language Processing
Week 3: April 25
Week 4: May 2
NLP Guide Lab Session Guide
We will focus on the recent research and practical developments in Natural Language Processing (NLP) spanning the years from 2015 to 2024. Furthermore, we will explore other relevant topics including distillation and quantization for deployment, ethical considerations about large language models (LLMs), dialog models, efficient transformers, and language models for search, among others.
Advanced Computer Vision
Week 5: May 9
Week 6: May 16
Gürkan Soykan Berkin Deniz Kahya
Computer Vision Guide Lab Session Guide
In this week, we will focus on advanced computer vision topics, including diffusion models, visual transformers, multimodal approaches, and practical advice. Through notebook sessions and demos, this part aims to provide a comprehensive understanding of advanced computer vision techniques.
Models in Action: Discussion on Specific Use Cases & Wrap-up
Week 7: May 23
Program Lead
& Moderator
This week, we’ll explore how the models we’ve covered throughout the course can be applied to diverse fields such as bioinformatics, drug design, and fintech, as well as how AI is utilized across various industries. Our community members will join us to discuss their respective domains, share how they apply machine learning to their projects, and talk about their journeys.
Lastly, we will have our graduation ceremony!
Curious about what each session will cover? Explore the detailed syllabus here.
COMMUNITY FEEDBACK
“The Applied AI program organized by inzva is an enjoyable and highly productive initiative where you can meet many individuals from both the industry and academia who share a similar journey.
The program covers a wide range of topics, from classical machine learning concepts to NLP (Natural Language Processing) and computer vision. It not only provides theoretical knowledge and coding skills but also offers the opportunity to hear firsthand how these concepts manifest in real-world scenarios. Moreover, one of the most valuable aspects of the program is the chance to connect with people who share similar interests and concerns.
I believe that being part of such a community in such a vast industry is truly invaluable. ”
FREQUENTLY ASKED QUESTIONS
Please check out the Frequently Asked Questions here.
For further questions, you can reach us at ai@inzva.com
PROGRAM OUTCOMES
Learn from more experienced guides and peers in the field of computer science,
Acquire a state-of-the-art, domain-specific training,
Learn about recent models that have changed our daily lives like LLMs,
Hold discussions about different ways to approach a problem,
Become familiar with the ML in Business and the use cases,
Meet like-minded students,
Experience peer-to-peer learning with our guides,
Certificate of participation issued by inzva.
EXPECTATIONS
Successfully answering the technical question during your application,
Attending all classes (this is mandatory in order to graduate),
Completing the weekly assignments and delivering them by the deadline,
Being an active participant who is an enthusiast of all things AI-related,
Following the rules of our community: Code of Conduct
Please note that failure to meet these requirements without a good reason will result in your disqualification from the program and future inzva AI programs.
TECHNICAL REQUIREMENTS
Programming experience: The course is taught in Python. We assume you have basic programming skills (understanding of for loops, if/else statements, and data structures such as lists and dictionaries).
Mathematics: Basic linear algebra (matrix-vector operations and notation)
Machine Learning: Conceptual knowledge of machine learning (supervised learning, unsupervised learning, test data, validation, and some machine learning algorithms such as linear regression, and logistic regression)
Deep Learning: Theoretical knowledge is required on the deep learning concepts. The objective of this study group is to give the participants practical knowledge and hands-on programming experience with deep learning algorithms and frameworks. Theoretical aspects of deep learning algorithms will be only quickly summarized in the study group. Therefore, it may be hard for you to jump directly into the practical aspects if you do not have any background knowledge. Having attended inzva Deep Learning Study Group before is a big plus.
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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