AWS AI Practitioner Flashcards
(78 cards)
Where can I get free AWS AI Practitioner Certification training?
AI Practitioner Practice Exam Questions
What level is the AWS AI Practitioner certification?
Foundational
What are the AWS AI Practitioner Testing specifics?
120 minutes for 85 questions
5 Domains of AI Practitioner Exam
AI & ML (20%)
Generative AI (24%)
Applications of Foundation Models (28%)
Responsible AI (14%)
AI Security Compliance & Governance (14%)
Define AI
Any way a computer can mimic human intelligence
Define ML
AI subset. Identifies patterns within data. Uses patterns to predict new patterns.
Define Deep Learning
ML subset. Neural Networks. Trying to replicate how the brain works.
Define Generative AI
DL subset. Uses DL to generate content.
How is traditional programming different than ML?
Traditional uses human to write the code.
ML uses a learning algorithm to create a model based on its learnings to produce a prediction.
When to use ML vs. Traditional programming
- When you cant code it (too complex to write the code)
- When you cant scale it (e.g. fraud detection, spam, recommendations)
- When you have to adapt/personalize (e.g. book recommendations)
- When you cant track it (data coming in to quickly, e.g. automated driving)
Conditional ML is _______ in its predictions
Deterministic
Generative IA is ________ in its predictions
Non-Deterministic. Can make things up
Why use ML over Gen AI?
Transparency * Interpretability
Explainability & Fairness
Robustness & Consistency
Data Efficiency
Specific Task Performance
3 Machine Learning Types
Supervised, Unsupervised, Reinforcement
What is ML/Supervised Learning
Data is assigned a label. Supervised learning uses the labels and repetition to learn. (E.g. how little kids learn).
Labeled data is put into a ML algorithm which makes a prediction. A human corrects /adjusts the model if the prediction is incorrect.
What is unsupervised learning?
No labeled data. Uses grouping data to predict other relationships. E.g. these type customers bought x so they will likely buy Y
What is ML/Reinforcement learning?
Learns through reinforcement. E.g. Dog training.
Key areas of ML/Supervised Learning
Regression (Numeric e.g. predict house prices), Classification (Binary (a or b class) or Multiclass (can fit into several classes)
Key area of ML/Unsupervised Learning
Grouping/Clustering (Labels unknown or Finds data in Patterns)
Key area of Reinforcement learning
Correct actions rewarded (if agent does x, do y)
ML/Self-Supervised Learning
The basis of Generative AI. Unlabled data has a word removed. The model then predicts the word that was removed. Do this over and over and the prediction becomes accurate.
Label/Target
Dependent variable: what you are attempting to predict
Feature
Independent variable: data that helps you make predictions
Feature Engineering
Data Transformation: process of reshaping data to get more value
