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Python with AI – I
Session 4
Logistics
• Please paste your repl link for this session in the google sheet
• Be prepared to share your screen
• A repl link with questions to all exercises we will do today in the
class will be provided
Course Curriculum
Session
Number
What is covered
1 Python basics – conditionals and loops
2 Python packages – pandas dataframes
3 Data structures in python – lists, arrays, dictionaries
4 Create and manipulate datasets in python
5 REST API and Github
6 Connecting two or more AIs in an Application
7 Data Visualization
8 Final Projects
Operators in python - Recap
Operator Syntax Description
Sum + Adds two numbers (or) strings
Subtraction - Only numbers
Product * Product of numbers, repetition of strings
Division / Division between numbers
Modulo % Remainder of division between two
numbers
Power ** Power of one number over another
Conditionals - Recap
• The if statement
Conditional Description
== Equal
!= Not Equal
> Greater than
< Less than
>= Greater than or equal to
<= Less than or equal to
Loops - Recap
• The for loop is of the following form.
• The range indicates the number of times a statement will be
implemented.
• There is a colon value to indicate the start of for loop.
• The code below is executed many times. The number of times it gets
executed depends on the values specified in range.
• Note that the code below the for statement is indented.
Lists- Recap
• A list holds ordered collection of items.
• And item can be a string or a number
Dictionaries - Recap
• A dictionary consists of two things (a) keys (b) values
• Use strings to represent keys
• Values can be anything
Dictionaries - Recap
• Print a value in a dictionary
• Delete a value in a dictionary
• Print all keys of a dictionary
• Add values to a dictionary
Functions in python
• Re-usable pieces of code
Functions accept parameters
• How would you call this function?
Call a function that accepts parameters
• How would you call this function?
Functions return values
• How would you call this function?
How would you call this function
• How would you call this function?
Functions can accept and return multiple
values
• How would you call this function?
Functions can accept and return multiple
values
• How would you call this function?
Exercise
Modules in python
• Use multiple functions written by others
Modules in python
• Use multiple functions written by others
• Popular packages: numpy, pandas
• How do you tell python to use these packages?
Modules in python
• Use multiple functions written by others
• Popular packages: numpy, pandas
• How do you tell python to use these packages?
Numpy package - arrays
• Example of an array
Numpy package - arrays
• Example of a 2D array
Can all lists be converted to numpy arrays?
Why should I use a numpy array?
• Arrays are more convenient – How?
Create random numbers
Create random numbers
• Generate random integers
• Generate random numbers
http://aiclub.world

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Pa1 session 4_slides

  • 1. Python with AI – I Session 4
  • 2. Logistics • Please paste your repl link for this session in the google sheet • Be prepared to share your screen • A repl link with questions to all exercises we will do today in the class will be provided
  • 3. Course Curriculum Session Number What is covered 1 Python basics – conditionals and loops 2 Python packages – pandas dataframes 3 Data structures in python – lists, arrays, dictionaries 4 Create and manipulate datasets in python 5 REST API and Github 6 Connecting two or more AIs in an Application 7 Data Visualization 8 Final Projects
  • 4. Operators in python - Recap Operator Syntax Description Sum + Adds two numbers (or) strings Subtraction - Only numbers Product * Product of numbers, repetition of strings Division / Division between numbers Modulo % Remainder of division between two numbers Power ** Power of one number over another
  • 5. Conditionals - Recap • The if statement Conditional Description == Equal != Not Equal > Greater than < Less than >= Greater than or equal to <= Less than or equal to
  • 6. Loops - Recap • The for loop is of the following form. • The range indicates the number of times a statement will be implemented. • There is a colon value to indicate the start of for loop. • The code below is executed many times. The number of times it gets executed depends on the values specified in range. • Note that the code below the for statement is indented.
  • 7. Lists- Recap • A list holds ordered collection of items. • And item can be a string or a number
  • 8. Dictionaries - Recap • A dictionary consists of two things (a) keys (b) values • Use strings to represent keys • Values can be anything
  • 9. Dictionaries - Recap • Print a value in a dictionary • Delete a value in a dictionary • Print all keys of a dictionary • Add values to a dictionary
  • 10. Functions in python • Re-usable pieces of code
  • 11. Functions accept parameters • How would you call this function?
  • 12. Call a function that accepts parameters • How would you call this function?
  • 13. Functions return values • How would you call this function?
  • 14. How would you call this function • How would you call this function?
  • 15. Functions can accept and return multiple values • How would you call this function?
  • 16. Functions can accept and return multiple values • How would you call this function?
  • 18. Modules in python • Use multiple functions written by others
  • 19. Modules in python • Use multiple functions written by others • Popular packages: numpy, pandas • How do you tell python to use these packages?
  • 20. Modules in python • Use multiple functions written by others • Popular packages: numpy, pandas • How do you tell python to use these packages?
  • 21. Numpy package - arrays • Example of an array
  • 22. Numpy package - arrays • Example of a 2D array
  • 23. Can all lists be converted to numpy arrays?
  • 24. Why should I use a numpy array? • Arrays are more convenient – How?
  • 26. Create random numbers • Generate random integers • Generate random numbers