Data Science and Artificial Intelligence.pdf

Extracting insights from data using statistics, programming, and domain knowledge.

1. Data Science and
Artificial Intelligence
https://nareshit.com/
Extracting insights from data using statistics,
programming, and domain knowledge.

2. What is Data
Science?

3. Clean Data means:
No missing values
No duplicates
Consistent formats (e.g., date, currency)
Tools: Python, Pandas for cleaning.
Importance of Clean DataGarbage In = Garbage Out” – AI and Data Science need accurate data.

4. What is Artificial Intelligence?
Examples: ChatGPT,
Alexa, Self-driving
cars.
AI vs Data Science →
AI uses data to learn
& make predictions.
Definition : Making
machines think and act
like humans.

5. Attributes (Features): Columns in a
dataset that describe data.
Example: In a Student Dataset → Name,
Age, Marks, Gender.
Target Variable: The column we want to
predict.
Example: Predicting Pass/Fail based on
Marks.
Attributes & Features

6. Python for Data Science
Why Python?
Easy to learn
Large libraries (NumPy, Pandas, Scikit-learn)
Huge community support

Example Code:
import numpy as np
import pandas as pd
https://nareshit.com/

7. NumPy Basics
NumPy = Numerical Python
Used for: Arrays, mathematical operations, linear algebra.
Example Code:
import numpy as np
arr = np.array([1, 2, 3, 4])
print(arr.mean()) # Average

8. Pandas Basics
Pandas = Data manipulation & analysis library.
DataFrames & Series → like Excel in Python.

Example Code:
import pandas as pd
data = pd.DataFrame({
'Name': ['Teja','Ravi'],
'Marks': [85, 90]
})
print(data.describe())

9. https://nareshit.com/
Clean data + attributes → training AI
models.
Example Workflow:
1.Collect Data (student marks dataset).
2.Clean Data (remove missing values).
3.Use Pandas & NumPy for processing.
4.Train AI Model (predict pass/fail).
5.Get Predictions → Insights.
AI + Data Science in
Action

10. Data Science + AI are future-ready skills ??????
Learn Python → NumPy → Pandas → ML → AI.
Career Options: Data Analyst, Data Scientist, AI Engineer.
Tip for Students: Start with small datasets and practice
daily!
Conclusion & Career Path

11. Thank You
Boost your results with AI. 040-23746666 [email protected]
www.reallygreatsite.com

12. Resource Page