Training camps

Training camps 2022 - 2023

*** Training Camp by Amazon AWS ***
Date: July 5th-7th, 2023
Title: High-performance cloud computing
You will learn Cloud Fundamentals, get an introduction to Cloud Architecture, deepen your cloud skills via hands-on labs, and explore cloud careers. The virtual camp will prepare you for official AWS certifications, which you can take once you have completed the Camp!
- Increasing awareness of cloud technologies required to build successful career growth
- Enable capacity-building training and tools to bridge the academic knowledge and skills gap.

Features and benefits:
- Building technical skills and capabilities in the field of cloud computing.
- Obtaining training by AWS Authorized Instructors with teaching and practical experience in the cloud computing field
- Participate in an official AWS Jam, a scenario-based, team-centered event where participants gain practical experience with a wide range of AWS services. AWS Jam scenarios relate to use cases, domains, and services covered in the classroom training course. The event is gamified with teams competing against each other by scoring points for completing specific challenges. Challenges have varying degrees of difficulty and are therefore worth differing amounts of points. A live leaderboard provides updates on scores and progress throughout the event. Clues and guidance can be provided to help teams move through challenges, but cost points.

Participating students are required to attend the following free online courses
- AWS Cloud Practitioner Essentials (
- AWS Well Architected Framework (

Extra content can be found by enrolling in the Cloud Essentials Learning Plan (

*** Training Camp by Dr. Mykhaylo AndriIuka, Google Research ***
Date: September 6th-8th, 2023
Title: Building an image search engine

How could we build an automated system that can find a photograph in a family album or an online photo collection given just a textual description? In this course we will cover fundamental techniques in computer vision and natural language processing that will help us to address this question. The main aim of the course will be to enable students to build their own prototype of the image search engine, and participate in online Kaggle competition organized for the course participants. To aid the students in this mission we will review common methods for representing images and text with neural networks.

Specific techniques that the students will learn:
- image representation with convolutional neural networks (CNNs)
- neural architectures for sequence processing (RNNs and Transformers)
- neural architectures for image captioning
- representing words and sentences with vector embeddings (Word2Vec, GloVe, and BERT)


The course will assume that the students have solid knowledge of Python and numerical computation package NumPy. Knowledge of neural network libraries such as TensorFlow, PyTorch and Jax is highly recommended, but not strictly required. We will provide self-study materials for students to catch-up on these libraries.