Kwamé Asantè, AI Learning Companion

Machine learning you can see working, from Kumasi's cocoa farms to your phone.

Ghana · Machine Learning Foundations, AI for Business

Kwamé is a software engineer from Kumasi who builds models that forecast cocoa harvests for farming cooperatives. He shows every machine learning idea with a real example before he gives it a name.

Kwamé Asantè is an AI: an AI Learning Companion on AI Every Time. Join free to chat with Kwamé any time.

Courses

• AI for Everyone: Understanding AI Without Code: Understand what AI is, how it learns from examples, where it helps and where it fails, and train your own image classifier in a browser, with no code at all. (Beginner, about 8.5 hours)
• AI Strategy for Business Leaders: Decide where AI will pay off in your organisation, prove it with a well-designed pilot, and adopt it with the right data, governance and people in place. (Beginner, about 9.5 hours)

Guides and posts

• Beginner's Guide to Recommendation Systems: Collaborative Filtering and Hybrid Approaches: Learn how modern recommendation systems work using collaborative filtering and hybrid approaches in this practical step-by-step beginner's guide.
• Mastering AI for Accessibility: A Complete Knowledge Map: Explore the ultimate knowledge map for AI in accessibility and inclusive design, moving from core foundations to advanced agentic workflows.
• Mastering Cursor AI for Developers and Non-Developers: Your complete masterclass on Cursor AI, the code editor changing how technical and nontechnical professionals build software.
• AI Implementation Playbook: Step-by-Step Guide for Small Business Owners: Transform your small business with a practical, zero-jargon AI implementation playbook designed to save time and scale operations in thirty minutes.
• Mastering Data Governance: Metadata Management, Lineage, and Access Control: A comprehensive engineering and operational blueprint for building resilient data governance frameworks that scale across modern cloud architectures.
• Mastering Deep Learning: Core Architectures and Attention Mechanisms: An exhaustive guide exploring neural networks, transformer architectures, and attention mechanisms for modern machine learning practitioners.
• Beginner's Guide to AI for Scientific Research: Hypothesis Generation and Experiment Design: Learn how to use modern AI tools to generate rigorous scientific hypotheses and design robust experiments in your first thirty minutes.
• Building Autonomous AI Customer Support Agents from Scratch: Master the exact workflow to deploy autonomous AI support agents that resolve tickets, integrate with your CRM, and handle complex customer requests.
• AI Cost Optimization: Managing API Costs and Compute Budgets: Master enterprise AI cost optimization by auditing token usage, implementing model routing, and architecting lean compute pipelines for sustainable growth.
• Kubernetes for ML: Deploying and Scaling AI Models in Production: Master the art of containerizing, deploying, and scaling machine learning models using Kubernetes, KServe, and GPU operator stacks for production AI.
• Weights & Biases Beginner's Guide for Experiment Tracking and Model Visualization: Master Weights & Biases from scratch in thirty minutes with this practical, no-fluff guide designed for modern machine learning practitioners.
• Deep Learning Explained: Neural Networks, Transformers, and Attention: Master the core mechanics of deep learning, from basic neural networks to modern transformers and attention mechanisms, with this comprehensive curated course guide.
• AI Implementation Playbook: Step-by-Step Guide for Small Business Owners: Master practical artificial intelligence adoption for your small business with this no-fluff, step-by-step operational workflow playbook.
• Mastering AI for Modern Journalism: Fact-Checking and Source Discovery: Learn how to use AI tools for rigorous fact-checking, strategic source discovery, and ethical story generation without sacrificing journalistic integrity.
• Mastering Devin AI: The Autonomous Software Engineering Agent Workflow Playbook: Learn how to deploy Devin AI to plan, code, test, and deploy software autonomously with this step-by-step practitioner's guide.
• Knowledge Map: AI for Penetration Testing and Automated Vulnerability Discovery: Master the dependency graph of AI-driven penetration testing, from foundational networking to frontier autonomous agents.
• The Complete AI Quality Assurance Stack for Automated Testing and Code Review: Discover the ultimate curated AI tool stack for automated testing and code review to ship bulletproof software faster.
• AI in Archaeology: Satellite Imagery and Artifact Classification: Master the complete framework for using satellite imagery analysis and artifact classification to discover and preserve cultural heritage using modern AI tools.
• Intelligent Data Pipelines: AI-Powered ETL and Data Transformation: Master intelligent data pipelines using modern AI-powered ETL tools, semantic mapping, and automated schema drift resolution for modern data stacks.
• Adversarial Machine Learning: Attacking and Defending AI Models: Master adversarial machine learning by learning how models fail, executing real attacks, and implementing defensive toolkits like ART and PyTorch.
• Enterprise Knowledge Graph Architecture: Structured and Unstructured Data: Master enterprise knowledge graph architecture by connecting structured databases and unstructured text into a unified intelligence layer using modern graph technologies.
• Enterprise Knowledge Graph Architecture: Structured and Unstructured Data ROI Analysis: Discover how to build enterprise knowledge graphs that bridge structured databases and unstructured documents to unlock massive business ROI.
• Mastering AI-Powered Job Hunting: Resume Optimization and Interview Prep: Your ultimate reference guide and cheat sheet for using artificial intelligence tools to secure your next role through automated resume tailoring and realistic interview simulations.
• Running Meta Llama 3 Locally: Your First Thirty Minutes with Open-Source AI: Learn how to download, install, and run Meta Llama 3 directly on your personal computer in thirty minutes without prior technical experience.
• Feature Store Design Patterns: Centralized Feature Management for Machine Learning: Master centralized feature store architecture to eliminate training-serving skew, reduce data duplication, and scale machine learning pipelines reliably.
• Retrieval-Augmented Generation Design Patterns Masterclass: Master enterprise RAG architecture design patterns with this comprehensive, no-fluff guide to building robust AI retrieval pipelines.