DAY 1

09:00 -

13: 00

Workshop 1: Introduction to AI for strategic decision-making covers machine learning, deep learning, generative AI, real-world use cases (Zambian academics), AI readiness assessment, and AI adoption roadmap.

Presentation , Case studies, interactive Q&A

Clear understanding of AI's potential; checklist for initiating AI projects

14:00 -

8: 00

Workshop 2: Building an AI-Ready Organisation Focuses on integrating AI into workflows, identifying use cases selecting technologies, and managing change. Includes group activity to draft an AI implementation plan

Interactive workshop, Group exercises, case study Discussions.

Draft AI implementation plan; Insights into overcoming common adoption challenges

DAY 2

09:00 - 13:00

Workshop 3: Introduction to python for Machine Learning Introduces basics of python programming and fundamental packages for AI model implementation.

Lecture, Live coding, Demo, Hands-on Lab

Fundamental understanding of python programming languages.

14: 00 - 18:00

Workshop 4: Introduction to Machine Learning: Classification, Regression and Clustering Introduces core machine learning techniques (logistic regression, decision trees, SVMs) wit hands-on exercises using python and scikit-learn.

Lecture,Live coding Demo, Hands-on Lab

Basics of implementation of machine learning models

DAY 3

09:00 -

13: 00

Workshop 5A: Introduction to computer Vision Focuses on image classification, object detection, using Python, OpenCV, and pre-trained models (YOLO11) for basic image recognition. Discussions on facial recognition and defect detection.

Lecture, Live Coding Demo, Hands-on Lab

Participants will develop a basic image recognition system and understand computer vision applications

09: 00 -

13: 00

Workshop 5B: Introduction to Audio Processing

Introduces audio processing techniques, focusing on speech recognition and audio classification.

Lecture, Live Coding Demo, Hands-on Lab

Participants will develop a basic audio classification system and understand audio processing applications.

14:00 - 18:00

Workshop 5C: Introduction to Deep Learning

Introduces neural networks, solving classification and regression problems using neural networks, with hands-on exercises using Python and Keras.

Lecture, Live Coding Demo, Hands-on Lab

Basics of implementation of deep learning models

14:00 - 18:00

Workshop 6: Text Analysis with Natural Language Processing (NLP) Explores NLP techniques like sentiment analysis and text classification, using Python libraries (NLTK, spaCy) with hands-on sentiment analysis model building.

Lecture, Live Coding Demo, Hands-on Lab

Participants will create a text analysis model and gain skills in NLP applications

DAY 4

09:00 -

13: 00

Workshop 7A: Introduction to Retrieval-Augmented Generation (RAG)

Introduces RAG, combining retrieval and generation for context-aware responses, using Python and Vector databases (ChromaDB) to build a simple RAG system.

Lecture, Live Coding Demo, Hands-on Lab

Participants will develop a RAG system and understand its applications in knowledge-intensive tasks

09: 00 - 13:00

Workshop 7B: Deploying Large Language Models Locally

Focuses on deploying LLMs on local infrastructure, addressing resource constraints and data privacy.

Lecture, Live Coding Demo, Hands-on Lab

Participants will deploy a lightweight LLM locally and learn strategies for managing resource-intensive models in constrained environments.

09:00 - 13:00

Workshop 7D: AI for Cybersecurity Operations: Penetration Testing, Threat Detection, and Automation

Explores AI in offensive and defensive cybersecurity, including penetration testing, vulnerability assessments, phishing detection, and automated reporting. Includes practical labs simulating AI tools in SOC environments.

Presentation, Tool Demonstrations, Hands-on Labs, Interactive Discussion

Practical knowledge of AI-enhanced red and blue teaming; Ability to automate parts of security assessments and reporting; Exposure to integrating AI into cybersecurity workflows.

14:00 - 18:00

Workshop 7C: Deploying Artificial Intelligence Models

Focuses on deploying AI models as scalable APIs and creating accessible end-user interfaces, using Flask for web services and Gradio for interactive UIs.

Lecture, Live Coding Demo, Hands-on Lab

Participants will deploy an AI model as a Flask API and create a Gradio-based user interface, enabling practical model integration.

14:00 - 18:00

Workshop 7E: Securing AI Systems: Attacks on AI and the OWASP ATLAS Framework

Explores threats to AI models (adversarial machine learning, model extraction, prompt injection) and introduces the OWASP Top 10 for LLM Applications (ATLAS). Includes labs simulating attacks and defenses.

Presentation, Attack Demos, Hands-on Labs, Group Exercise

Identify and exploit AI model vulnerabilities; Apply ATLAS to assess AI/LLM risks; Gain actionable strategies to secure AI systems and pipelines.