Applied AI Study Group

Applied AI Study Group is an advanced 4-week long programme designed for AI enthusiasts and computer engineering students, where we study the materials on IBM’s Applied AI with DeepLearning each week and come together on Saturdays to discuss them with a guide to lead us.

This study group aims to bring together like-minded AI enthusiasts by providing them an opportunity to interact with other participants and community members to collaboratively improve their knowledge and academic prowess on deep learning, and its applications and frameworks.

Furthermore; this study group enables the participants to build models themselves in order to gain hands-on experience. During this course, we will recall the basics of Linear Algebra and Neural Networks, then learn about main DeepLearning frameworks such as Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML to finally use them for building various models. We will use our models to solve real life problems such as anomaly detection in sensor data and stock market forecasting.

Lastly, we will learn about the data storage solutions, real time data processing and distributed computing methods to deploy and scale our projects.

After going through a series of programme assignments offered by the course; we will conclude the sessions by completing final assignments.


- 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)

- Machine Learning: Conceptual knowledge of machine learning ( supervised learning, unsupervised learning, test data, validation, some machine learning algorithms such as linear regression, logistic regression)

- Deep Learning: Theoretical knowledge 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, if you have no background knowledge it may be hard for you to directly jump into the practical aspects.

Have a Python environment i.e. Anaconda ready on your computer before the programme. You will find the instructions here.


It is ended.


Saturday, July 6 Introduction to Deep Learning

Saturday, July 13 Deep Learning Frameworks

Saturday, July 20 Deep Learning Applications

Saturday, July 27 Scaling and Deployment

For more detail:


11:00 - 11:15  Introduction

11:15 - 13:00  Discussion

13:00 - 14:00  Lunch

14:00 - 15:00  Problem solving

15:00 - 15:15  Coffee Break

15:15 - 16:30  Discussion


inzva, Beykoz Kundura.

We are located exactly here = 41.141310, 29.078505



We have a shuttle departing from Kanyon AVM Eczacı Exit at 10 am which stops by Boğaziçi South Entrance at 10.15 am.

You can also take a bus from Kadıköy or Levent, or take a ferry to Beykoz from Yeniköy.

How to get to inzva.


To join this programme, fill in the application form below; and make sure to check out our FAQ page for further information.


See the FAQ here.

Transportation and meals supported by BEV Foundation. All participants have to abide by our CODE OF CONDUCT.



Ahmet Melek is studying Business Management at Bogazici University. He has previously worked on the topics Blockchain, Biometrics and Semantic Web.

He is currently working on generative models, such as GAN or Autoencoder models, to solve various problems in surveillance, the medical sector and consumer applications.

Supported by BEV Foundation; inzva is a non-profit hackerspace, organising study and project groups as well as camps in the fields of AI and Algorithm; and gathering CS students, academics and professionals in Turkey.