Basic Python Course

Who is it for?

• Psychologists and health professionals who want to use Python to organize, analyze, and present data.
• Students or curious people who want to start without complications.
• Those looking to solve real tasks with clear steps and guidance.

What do you get?

• Simple explanations and step-by-step examples.
• Practice files and email support.
• Flexible mode: 1-on-1 or group, according to your needs.

Syllabus

1. Python for Psychologists and Non-Programmers
   What? How? When? Why? of Python · Advantages · Disadvantages
2. Why use JupyterLab?
   What is JupyterLab?
3. Module 1: Using Anaconda
   Installation · Downloading Anaconda Individual App · Creating your Environment · Anaconda Commands
4. Module 2: Variable Types
   Differences between types
5. Module 3: Arithmetic Operators
   Operators · String concatenation · String multiplication · Numpy PI number · Type conversion
6. Module 4: What is a List in Python?
   Lists
7. Module 5: Applications in a list
   FOR loop in action · len() · type()
8. Module 6: What is the difference?
   Operator reference · Responding well · Customizing feedback · What has been declared?
9. Module 7: Relational Operators
   Equal, greater, and less than · What does each return?
10. Module 8: Strings (str)
    What the heck are strings? · Useful methods
11. Module 9: List Manipulation
    Applying previous functions
12. If we understood everything above...
    Paths and data directories
13. Module 10: range()
14. Module 11: set()
    What on earth is set()?
15. Module 12: eval()
    What does eval() do?
16. Integration of what was seen
    “Pythonic Power”: What does each print print? (ref. FOR in action)
17. Module 13: lambda Expression
    Helpful and anonymous Lambda · Using it to our advantage
18. Quick look at Pandas #1
    Creating a database with Pandas
19. Module 14: def Statement
    What the heck is def? · Relation with lambda and operators
20. Module 15: map() and filter()
    What are they and how to apply them?
21. Quick look at Pandas #2
    Using everything seen
22. Module 16: enumerate()
    Aha, enumerate what?
23. Module 17: Tuples
    What is a tuple? · Find the tuple
24. Module 18: Dictionaries
    What is a dictionary?
25. Quick look at Pandas #3
    “I have the Power”
26. Module 19: for Loop
    What is a for loop? · Write it
27. Module 20: if Conditional
    What is it? · Write it · Guided practice
28. Module 21: while Loop
    Basic usage
29. Module 22: Closing
    Integrating everything seen
30. Pandas for Psychologists and Non-Programmers
    What is Pandas? · Why use Numpy? · Introduction to DataSets
31. To Structure
    DataFrame · Series · How to create a pd.Series?
32. “Cycling” categories
    pd.Series.unique() · Lambda to filter strings · The for also does its thing
33. Element selection: if, def, lambda, for
    What the heck is .iloc and .loc? · Differences · Replacing what DOES NOT work with NaNs
34. Data Handling
    pd.concat() · pd.merge()
35. Basic Statistics
    Descriptive statistics functions

Python-Pandas for Psychologists and Non-Programmers.
This course is designed for you to learn Python to your advantage and be able to analyze any database you have. If you are tired of relying on Excel macros or suffering incompatibilities, here you will see how to use Python from scratch to create and manipulate your data. In the end, you will have that feeling of power —like automating even the toast process (✌)— and organizing your data to analyze them whenever you want.

Enrollment

Price: USD $40 per student

You can take it individually or join a group. After your payment, I will write to you by email to coordinate schedules and access to materials.

After payment, you will be redirected to gracias2.html and receive an email with access and next steps.