ML & GenAI
Learning Lab
Interactive, browser-based playbooks for data scientists, ML engineers, and GenAI practitioners. Use decision trees and visual guides to choose algorithms, metrics, GenAI techniques, and certifications with confidence.
How to Use This Lab
Each module is a small, self-contained playbook. You can drop in for 10–30 minutes, answer a few focused questions, and leave with a concrete decision or checklist.
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01
Pick the question you’re stuck on.
Algorithm, metric, GenAI technique, evaluation, or exam prep.
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02
Walk through a guided decision flow.
Answer simple prompts and follow the branches that match your use case.
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03
Capture the outcome and rationale.
Use the final recommendation as a design note, study aid, or team decision record.
Available Resources
11 modules · Beginner to Advanced + Certification PrepStart with the Beginner module if you're new, then progress through Intermediate and Advanced guides.
Algorithm Selector
Interactive decision tree to find the optimal ML algorithm for your specific problem type and data characteristics.
Feature Engineering Playbook
Interactive decision tree for encoding, scaling, outlier detection, feature creation, and selection across tabular, text, time-series, and image data.
Metric Decision Tree
Navigate the landscape of model evaluation metrics. Choose the right metric for classification, regression, and beyond.
AWS AI Practitioner
Comprehensive study guide with interactive flashcards and quizzes for the AWS Certified AI Practitioner exam.
AWS AI Practitioner Exam
Timed practice exams with 114 questions across all 5 domains, matching the real AIF-C01 exam distribution.
Visual References
Polished diagrams covering confusion matrices, RAG pipelines, and the complete LLM lifecycle from the AIF-C01 curriculum.
AI Opportunity Scorer
PM-perspective decision engine. Evaluate AI opportunities across 6 value dimensions and get a Build, Buy, Experiment, or Kill recommendation.
AI Solution Navigator
Business-focused decision engine covering the full AI landscape. Navigate from problem to solution across Rule-Based, ML, Deep Learning, GenAI, Agents, and OR.
GenAI Technique Selector
Interactive decision tree to choose the right LLM optimization: RAG, Fine-tuning, LoRA, Quantization, and more.
FM Evaluation Metrics
Choose the right metrics for LLM evaluation: Perplexity, ROUGE, BERTScore, RAGAS, LLM-as-Judge, and more.
Suggested Paths
Not sure where to start? These lightweight paths pair the modules into simple journeys.
Path_A · Getting Started
New to ML & GenAI
- 1. GenAI Foundations Navigator
- 2. Algorithm Selector
- 3. Feature Engineering Playbook
- 4. Metric Decision Tree
Path_B · GenAI
GenAI Engineer Track
- 1. GenAI Foundations Navigator
- 2. GenAI Technique Selector
- 3. FM Evaluation Metrics
Path_C · Certification
AWS AI Practitioner Prep
- 1. AWS AI Practitioner Guide
- 2. AWS AI Practitioner Practice Exam
- 3. Visual References
About This Lab
A curated collection of interactive learning tools designed for data scientists and ML engineers. Each resource is built to provide hands-on, practical guidance for real-world machine learning decisions.
Created by Tarek Atwan
What’s new
· AWS AI Practitioner Practice Exam v1.0 · AI Opportunity Scorer v1.0 · AI Solution Navigator v1.0 · Feature Engineering Playbook v1.0 · GenAI Foundations Navigator (Beginner) · GenAI Technique Selector v1.0 · FM Evaluation Metrics v1.0
Upcoming ideas: MLOps readiness checklist, experiment design aide.