Python for OSINT - Leveraging AI and Machine Learning

The Python for OSINT course from CyberNest Labs is genuinely cutting-edge in the world of Open Source Intelligence, emphasising AI and machine learning technologies, including computer vision, generative audio, image, video, and local LLMs for coding and debugging. Our course will teach you Python and integrates a full environment setup with version control through GitHub, culminating in a full-day application-building exercise that you can take-away, with support from your trainers. 

Environment Setup and Python Basics

• Setting Up the Environment: Installing Python, setting up virtual environments and understanding dependencies.

• Version Control: Introduction to Git, creating and managing GitHub repositories, branching and merging.

• Python Basics: Variables, data types, basic operations, control structures, and functional programming.

Data Handling and Manipulation

• Data Structures: Lists, dictionaries, sets, tuples.

• Libraries for Data Manipulation: Introduction to Pandas, Requests, BeautifulSoup.

• Data Importing/Exporting: Working with CSV, JSON, and Excel files among others.

AI-Enabled Data Analysis and Visualisation

• Statistical Analysis: Basics with NumPy.

• Data Visualisation: Introduction to Matplotlib and Seaborn.

• Exploratory Data Analysis: Using Pandas to summarise datasets.

• Applying LLMs: Using LLMs for sentiment analysis, text summarisation, question-answering & analytical insights.

Database Management

• SQL Basics: Understanding SQL and databases.

• Integrating Python with SQL: Using libraries like SQLAlchemy.

• NoSQL Databases: Basics of MongoDB and integration with Python.

Web Scraping and Data Gathering

• Introduction to Web Scraping: Using BeautifulSoup and Scrapy.

• API Interactions: Accessing data through APIs with Requests.

• Automating Data Collection: Scheduled scraping with Python and automated web-wide alerting with Google Alerts.

AI and Machine Learning for OSINT

• Advanced Statistical Techniques: Regression analysis, hypothesis testing.

• Machine Learning Basics: Using scikit-learn for predictive modelling.

• Natural Language Processing: Practical use with Large Language Models.

• Using Local LLMs: Employing LLMs for coding and debugging.

Computer Vision and Generative AI

• Introduction to Computer Vision: Basics and applications.

• Using Open Source Models: Modifying neural networks from Hugging Face for computer vision tasks.

• Generative AI: Creating generative audio, image, and video content.

• Tools for Enhancement: Using MidJourney, Krea & Gimp for image enhancement.

Advanced OSINT Techniques

• OSINT Techniques: Automate gathering data from public sources.

• Social Media Analysis: Using Python to process & enrich OSINT and social media data.

• Practical Tools: Implementing StreetClip and other advanced OSINT tools.

Application Development and Automation

• Automating OSINT Processes: Writing scripts to automate OSINT tasks.

• Developing OSINT Tools: Building tools for specific OSINT applications.

• Integration with AI Tools: Enhancing OSINT tools with AI and machine learning capabilities.

Capstone Project and Professional Development

• Capstone Project: A full-day project that integrates topics covered, applied to a real-world OSINT scenario.

• Project Management: Using GitHub for version control and collaboration.

• Presentation Skills: Delivering findings to an audience & explaining technical topics.

• Professional Development: Writing clean, maintainable code, exploring career paths in OSINT and AI.

Course Highlights

• Constant Hands-On Exercises and Mini-Projects: Ensuring practical application of concepts.

• Support Materials: Cheat sheets, best practices, tips and tricks, and further reading resources.

• Interactive Learning: Incorporating Jupyter Notebooks and cloud-based platforms for coding and collaboration.

• Food, Drinks, Video-Games & Networking: Courses with CyberNest Labs are an immersive experience involving professional networking events and external speakers. 

• Cutting-Edge Tools and Techniques: Utilising the latest AI tools and open-source neural networks for practical OSINT applications.

• Real-World Examples and Case Studies: Providing context and relevance to the skills being taught.

This structure aims to provide a robust learning experience, equipping delegates with both the technical skills and practical knowledge needed for modern OSINT practice using advanced AI and machine learning technologies.