Pragmatic AI Training

AI Fundamentals

We establish a common frame of reference for AI, explore its history and evolution, introduce key concepts & terminology, share examples and Q&A

George Anadiotis

Data Fundamentals

We introduce different types of data, describe their characteristics and how they're managed, processed, stored & utilized. We share examples and Q&A

George Anadiotis

Data Science and Statistical Analysis

Discover how data transforms into business intelligence through the essential concepts of data science and statistics.

George Anadiotis

Lab: Working with Data in Organizations

We introduce the organization, the no-code environment and the datasets we'll be using throughout the course. We explore and work with the datasets.

George Anadiotis

Exploratory Data Analysis and Visualization

We transform raw data into insights and introduce Univariate, Bivariate and Multivariate analysis, Data Visualization and Hypothesis Testing

George Anadiotis

Lab: Data-Driven Sales Insights

We focus on the sales dataset and explore it using the techniques we introduced: Distributions, Analysis, Visualization, Hypothesis Testing

George Anadiotis

Machine Learning Fundamentals

We introduce the different types of Machine Learning, key Machine Learning concepts and algorithms

George Anadiotis

Lab: Developing a Machine Learning Model for Sales Forecasting

We work on the sales dataset & use it to develop a sales forecasting model. We split the dataset, choose algorithm & features, develop, test, validate

George Anadiotis

Convergence: Day 1 Recap, Reflection and Recreation

We reflect, discuss, and answer questions over dinner and drinks. We keep work conversation within limits, and offer optional group activities

George Anadiotis

Machine Learning Algorithms & Evaluation

We introduce Machine Learning applications, evaluation and performance metrics, and more advanced algorithms

George Anadiotis

Lab: Developing additional ML Models for Sales Forecasting

We continue the work on the sales dataset, using it to develop more models for sales forecasting. We try different algorithms, evaluate & compare

George Anadiotis

Lab: Developing ML Models for Sales Clustering & Classification

We continue the work on the sales dataset, developing models for sales clustering and classification. We try algorithms, evaluate and compare results.

George Anadiotis

Lab: Image Clustering & Classification

We work with the image dataset we introduced previously, and explore ways to extract clusters from it and develop a classifier.

George Anadiotis

Natural Language Processing & Generative AI

We introduce NLP techniques to extract meaning from text, NLP applications, and Large Language Models (LLMs)

George Anadiotis

Lab: Automating Meeting Admin leveraging Speech Recognition

We work with the meeting video and audio dataset we introduced, and explore ways to extract the information we need out of it by turning it to text.

George Anadiotis

Lab: Refining Meeting Admin Automation leveraging GenAI Prompt Engineering

We work with meeting transcripts, using LLMs. We introduce Prompt Engineering techniques & frameworks, the use case and exercise we'll be working on

George Anadiotis

Lab: Scaling up Meeting Admin Automation leveraging RAG & Knowledge Graphs

We go from working with one text file, to working with a collection of text files. We introduce RAG & Knowledge Graphs, use case, tool & exercise

George Anadiotis

Convergence: Day 2 Recap, Reflection and Recreation

We reflect, discuss, and answer questions over dinner and drinks. We keep work conversation within limits, and offer optional group activities

George Anadiotis

Guided tour to Ancient Olympia

George Anadiotis

Local Winery Visit & Lunch

George Anadiotis

Guided Tour to Cricket Hill

George Anadiotis

Guided tour to Platiana Acropolis

George Anadiotis

Convergence: Day 3 Recap, Reflection and Recreation

We reflect, discuss, and answer questions over dinner and drinks. We keep work conversation within limits, and offer optional group activities

George Anadiotis

Local Culture Event

George Anadiotis

Data Governance

We introduce Data Governance practice, roles and responsibilities. We focus on Data Catalogs, and introduce Knowledge Management principles

George Anadiotis

Lab: Governing Data with a Data Catalog

We learn how to work with a Data Catalog. We work in groups, simulating an organizational setting with various stakeholders.

George Anadiotis

Data Modeling & Ontology Design

We introduce the fundamentals of data modeling, focusing on ontology design, and model a knowledge graph of our domain that we'll use.

George Anadiotis

Lab: Problem Solving leveraging Ontology, Advanced RAG & Knowledge Graphs

We use the domain data model we developed to refine our RAG application. Then, we use the application to answer questions and solve problems.

George Anadiotis

AI Integration and Deployment

We review options for AI application development, survey main AI frameworks, cloud-based services, no-code and low-code options

George Anadiotis

Lab: From Model to Application

We develop and deploy a minimal application based on a machine learning model we created in one of the previous labs.

George Anadiotis

AI Ethics

We introduce AI ethics for responsible AI development: bias & fairness, privacy & data protection, social & economic impact, Ethical AI frameworks

George Anadiotis

AI Governance & Regulation

We introduce AI Governance & Regulation, review the regulatory landscape and compliance requirements, governance frameworks & risk management for AI

George Anadiotis

Convergence: Day 4 Recap, Reflection and Recreation

We reflect, discuss, and answer questions over dinner and drinks. We keep work conversation within limits, and offer optional group activities

George Anadiotis

AI & Business Strategy

We introduce a framework for AI strategy development & tools to document & evaluate use cases, learn cost-benefit analysis and evaluate KPIs & ROI

George Anadiotis

Lab: AI Business Strategy Development

We apply the AI strategy development framework & tools we introduced in use cases built around our Organization setting, datasets & model development

George Anadiotis

AI Project Management Fundamentals

We introduce key aspects of managing AI projects: the AI project lifecycle, Buy vs Build decision making, Scoping and planning AI projects

George Anadiotis

Team Management & Budget in AI Projects

We learn what roles are needed in AI project teams and how to manage them, Agile methodologies in AI development, budgeting and resource allocation

George Anadiotis

Lab: Capstone Project - AI Business Strategy Scale-up

We bring everything together, providing additional qualitative & qualitative context for the use cases we introduced & reevaluate initial AI strategy

George Anadiotis

Lab: Capstone Project - AI Project Plan

We choose one use case to develop further, and draft a detailed project plan, budget and resource allocation, and change management plan for it

George Anadiotis

Lab: Capstone Project - Presentations & Feedback

We present findings of the Capstone Project, discuss choices and assumptions, provide feedback and guidance, extrapolate to real-world use cases

George Anadiotis

AI Trends and Future Directions

We introduce emerging trends in AI, discuss the future of AI in society & industry, AI-driven innovation, and share AI learning paths and resources

George Anadiotis

Convergence: Day 5 Recap, Reflection and Recreation

We reflect, discuss, and answer questions over dinner and drinks. We keep work conversation within limits, and offer optional group activities

George Anadiotis

Convergence: Wrap-up, parting thoughts, and check out

We bid each other farewell and reflect on our experience, provide tailored advice and feedback as well as additional resources to explore.

George Anadiotis