Introduction to Artificial Intelligence

AI is transforming every industry. Understand the fundamentals and explore career opportunities.

What is Artificial Intelligence?

AI enables machines to mimic human intelligence.

Types of AI

Narrow AI

• Designed for specific tasks
• Examples: Siri, chess engines
• Current state of AI

General AI

• Human-level intelligence
• Can perform any intellectual task
• Still theoretical

Machine Learning

ML is a subset of AI:

python
# Simple ML example with scikit-learn
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier

# Load data
iris = load_iris()
X_train, X_test, y_train, y_test = train_test_split(
    iris.data, iris.target, test_size=0.2
)

# Train model
model = RandomForestClassifier()
model.fit(X_train, y_train)

# Evaluate
accuracy = model.score(X_test, y_test)
print(f"Accuracy: {accuracy:.2%}")

Deep Learning

Neural networks with multiple layers:

• Image recognition
• Natural language processing
• Speech recognition

AI Applications

1. Healthcare: Disease diagnosis, drug discovery
2. Finance: Fraud detection, algorithmic trading
3. Transportation: Self-driving cars
4. Entertainment: Recommendation systems
5. Education: Personalized learning

Ethical Considerations

• Bias in AI systems
• Privacy concerns
• Job displacement
• Decision-making transparency

Career Path

1. Learn Python and mathematics
2. Study ML algorithms
3. Work on projects
4. Get certified
5. Build portfolio