In this 1.5-hour workshop, globally recognized data visualization instructor and best-selling author Nick Desbarats will deliver a crash course on choosing chart types for showing data over time and for showing the breakdowns of totals. 18 essential chart types will be covered, including very useful but often overlooked ones like step charts, arrow charts, cycle plots, waterfall charts, treemaps and Pareto charts.  This workshop includes a “cheat sheet” package with several groundbreaking chart-type-selection decision trees from Nick’s best-selling books and courses.

Unlock the secrets to confident decision-making based on data and proven methodology. Join us for an insightful hands-on workshop through a powerful 5-Step process named Prime Route. From framing data within the relevant context, to uncovering root causes and employing techniques, such as the "5x WHYs", Matthew will guide you towards making data-informed decisions while respecting your gut!  Bring your laptop if you want to actively participate in the exercises and get the most out of the workshop. A sample dataset is available but if you have data you are familiar with (CSV file, 100MB max) that's even better!

• Brooks 

• Radium

• Skratchville

• Analog AI

• Happtic

• DocAnalyzer

• SlataDoc

• GeoLLM

• Enagramm

We encourage you to meet new people or reconnect with old friends and grab a lunch at one of the nearby cafes.

Despite the increasing deployment of risk assessment algorithms, journalists have struggled to access and test these systems. Last year, a team of journalists managed to access the source code, machine learning model file, and training data of a machine learning welfare fraud algorithm deployed in the Dutch city of Rotterdam. This hands-on workshop will have participants work directly with the Rotterdam algorithm and training data in order to learn how to develop and test hypotheses on risk assessment algorithms. Students and educators are especially encouraged to attend!

Join us to explore how open data can be harnessed for peacebuilding and how Georgian social tech enthusiasts can influence data providers and the government to make their open data more accessible to those committed to building peace.  You don’t need to be a peacebuilding expert — just have an interest in making open data more accessible, open, and functional, and a curiosity about how open data can be utilised in emerging fields.  This session will guide you through the ways open data can be applied to peace initiatives and its intersection with peace tech on a broader scale. Engage in a series of activities designed for activists, providing a platform to voice your ideas on driving more open and accessible policies.  You will gain insights into effective strategies for advocating open data usage, enhancing your ability to contribute to meaningful social change and peacebuilding efforts, alongside taking part in a series of participative activities to have your say.

In this interactive workshop, participants will explore the ethical challenges and responsibilities involved in developing AI systems, with a special focus on gender equality. Through case study analyses and hands-on design sessions, attendees will gain a deep understanding of how AI can perpetuate gender biases and the practical steps that can be taken to mitigate these risks. Participants will engage in meaningful discussions, develop ethical frameworks, and create actionable plans to ensure that AI technologies promote fairness and inclusivity for all genders. Ideally, they will leave with a clear set of strategies to implement ethical AI practices in their work, fostering a more equitable digital future.

At this session, you'll gain practical skills in building and analyzing Bayesian models with Python to detect external effects on time series data.   With over 20 years of experience in data modeling, the instructor will guide participants through a hands-on workshop where you will analyze the effect of external influences on time series data. This workshop will analyze the impact of wars on podcasting activity using a Bayesian approach.  

Bring laptops with Jupyter notebooks; installation instructions will be provided before the workshop. Prerequisites: Familiarity with Python, NumPy, and pandas.

In this presentation, Tbilisi AI Lab will showcase its groundbreaking work in developing Georgian language models tailored for local businesses. Over the past year, we have made significant strides in building neural translation models (NTMs) and small language models specifically designed for SMEs. Our approach addresses the unique challenges of the Georgian language and its impact on AI processing costs, offering more efficient and affordable solutions compared to major AI providers like OpenAI and Anthropic. We will also introduce our Retrieval-Augmented Generation (RAG) model, which enhances customer service capabilities by combining real-time data retrieval with AI-driven responses.  

As part of our commitment to fostering AI talent, we will announce the open-sourcing of our first small language model for educational use in our AI LAB Academy, a 9-month Generative AI course aimed at training the next generation of data engineers and scientists. Additionally, we’ll highlight our partnerships with local data centers, ensuring secure, cost-effective AI infrastructure for Georgian businesses. Join us to explore how we’re pioneering Georgian language AI and empowering businesses with cutting-edge, localized solutions.