Intermediate Python Deep Dive: Write Better Python and Build Better Systems – Certificate of Completion

Real Python Cohort-Based Course

VERIFIED
Certificate of Achievement

Real Python Cohort-Based Course

This is to certify that

Akhilesh M

has successfully completed

Intermediate Python Deep Dive: Write Better Python and Build Better Systems

a course of study offered by Real Python (realpython.com), an online learning platform and expert community for Python software developers.

Completion Date: May 14, 2025

Verification ID: 9ea7745d-e908-4a0f-9a09-3251291e0d0d

Course Description

Skill level: intermediate

This is an interactive, cohort-based Python course. This intermediate-level course focuses on Python’s core principles, starting with the object model and moving through advanced iteration techniques, special methods, and data structures. Course is led by an experienced Real Python instructor

Day 1 - Monday (Week 1)

1. Welcome From Your Instructor

2. Course Kick-Off Meeting

3. The Course Forum

4. A Review of Object-Oriented Programming

5. What is Object-Oriented Programming (OOP)?

6. Classes in Python

7. Class and Instance Attributes

8. Adding Attributes to a Python Class

9. Adding Methods to a Python Class

10. Exercise: Practice Writing a Class

Day 2 - Tuesday (Week 1)

1. Exercise: Jake's Stall at The Market

2. An Object's Identity, Type, and Value

3. Variables and How They're Linked to Objects in Python

4. Variable Assignment

5. Object References

6. Object Value vs Object Identity

7. Small Integer Caching

8. Identity: Recap

9. Optional: Watch the Remaining Lessons in the Variables Course

10. Python '!=' Is Not 'is not': Comparing Objects in Python

11. End of Day 2

Day 3 - Wednesday (Week 1)

1. Live session

Day 4 - Thursday (Week 1)

1. Introducing Inheritance

2. How Do You Inherit from Another Class?

3. OOP Inheritance

4. Inheritance Example

5. Inheritance and Composition

6. Exercise: Revisiting Jake, The Market Seller

Day 5 - Friday (Week 1)

1. Creating and Initializing Objects

2. Using Python Class Constructors (Overview)

3. Introducing the Instantiation Process

4. Exploring the Instantiation Process

5. Initializing Objects With .__init__()

6. Creating Objects With .__new__()

7. Providing Custom Object Creators

8. Subclassing Immutable Built-in Types

9. Returning Instances of a Different Class

10. Allowing Only a Single Instance in Your Class

11. Partially Emulating collections.namedtuple

12. Using Python Class Constructors (Summary)

13. Live Instructor Q&A Today

14. Weekend Fun Activity (Optional)

Day 6 - Monday (Week 2)

1. Using Special Methods to Explore Python's Core Topics

2. When to Use .__repr__() vs .__str__() in Python (Overview)

3. Displaying Object Information

4. Understanding Responses From Literals

5. Delving Into Strings

6. Calling Non-Functions

7. Customizing Objects

8. When to Use .__repr__() vs .__str__() in Python (Summary)

9. Exercise: Adding String Representations to Product and Sandwich

Day 7 - Tuesday (Week 2)

1. How Operators Are Linked to Special Methods

2. Supporting Operator Overloading in Custom Classes

3. Implementing Custom Sequences and Mappings

4. What Does a Data Structure Contain?

5. Shallow vs Deep Copying of Python Objects

6. End of Day 7

Day 8 - Wednesday (Week 2)

1. Live Session

Day 9 - Thursday (Week 2)

1. A Short Intro to Data Classes

2. Using Data Classes in Python (Overview)

3. Comparison to Standard Classes

4. Alternatives to Standard Classes

5. Basic Data Classes

6. More Flexible Data Classes

7. Advanced Default Values

8. Data Classes for Representation

9. Data Classes for Comparison

10. Immutable Data Classes

11. Inheritance and Subclassing

12. Optimization of Data Classes

13. Using Data Classes in Python (Summary)

14. Exercise: Creating a Recipe Data Class

Day 10 - Friday (Week 2)

1. The Iterator Protocol and Pythonic Looping

2. Efficient Iterations With Python Iterators and Iterables (Overview)

3. Getting Started

4. Understanding Iterator Objects

5. Transforming and Generating Data

6. Iterators and Iterables in Python: Run Efficient Iterations

7. Exercise: Making a Custom Iterable

8. Live Instructor Q&A Today

9. Weekend Fun Activity (Optional)

Day 11 - Monday (Week 3)

1. Pythonic Looping

2. Understanding Python List Comprehensions (Overview)

3. How to Create Lists in Python

4. How to Supercharge Your Comprehensions

5. When Not to Use a List Comprehension in Python

6. Understanding Python List Comprehensions (Summary)

7. Revisiting the Iterator Protocol

Day 12 - Tuesday (Week 3)

1. More Pythonic Looping Using zip() and enumerate()

2. Parallel Iteration With Python's zip() Function (Overview)

3. The zip() Function

4. Python Versions

5. Traversing Iterables

6. Applications

7. Parallel Iteration With Python's zip() Function (Summary)

8. Looping With Python enumerate() (Overview)

9. Iterating Without enumerate()

10. Using enumerate()

11. Understanding enumerate()

12. Building my_enum()

13. Working With my_enum()

14. Looping With Python enumerate() (Summary)

15. Exercise: Let's Make Sure You're Comfortable With zip() and enumerate()

Day 13 - Wednesday (Week 3)

Day 14 - Thursday (Week 3)

1. Generators, Generator Expressions, and Generator Functions

2. Iterating With Generators

3. Exploring Iterator Specifics

4. Going Deeper on the Iterator Protocol

5. Efficient Iterations With Python Iterators and Iterables (Summary)

6. Python Generators 101 (Overview)

7. Understanding Generators

8. Using Advanced Generator Methods

9. Creating Data Pipelines With Generators

10. Python Generators 101 (Summary)

11. [Optional] How to Use Generators and yield in Python

12. Exercise: Generators

Day 15 - Friday (Week 3)

1. How Groups of Special Methods Define Data Structure Categories

2. Python Sequences: A Comprehensive Guide

3. Python Mappings: A Comprehensive Guide

4. Live Instructor Q&A Today

5. Weekend Fun Activity (Optional)

Day 16 - Monday (Week 4)

1. Focus on Functions

2. [Optional] Review Function Basics: Defining and Calling Python Functions

3. [Optional] Functions in Python

4. [Optional] Why Use Functions?

5. [Optional] Function Calls and Definitions

6. Positional Arguments

7. Keyword Arguments

8. Positional and Keyword Arguments

9. Exercise: Positional and Keyword Arguments

Day 17 - Tuesday (Week 4)

1. Introducing Default Arguments

2. Default Parameters

3. Mutable Default Parameter Values

4. Default Parameters and Default Parameters with Mutable Values

Day 18 - Wednesday (Week 4)

Day 19 - Thursday (Week 4)

1. Pass-By-Reference, Pass-By-Value, and Pass-By-Assignment

2. Pass-By-Value vs Pass-By-Reference in C++

3. Pass-By-Value vs Pass-By-Reference in Python

4. Passing Mutable Objects and Side Effects

5. Argument Passing Summary

Day 20 - Friday (Week 4)

1. Introducing args and kwargs

2. Python args and kwargs: Demystified

3. Python args and kwargs Demystified: The Video Course

4. Using the Python args Variable in Function Definitions

5. Using the Python kwargs Variable in Function Definitions

6. Ordering Arguments in a Function

7. Unpacking With the Asterisk Operators

8. Python args and kwargs: Demystified (Summary)

9. Keyword-Only and Positional-Only Arguments

10. Keyword-Only Arguments

11. Bare Variable Argument Parameter

12. Positional-Only Arguments

13. Live Instructor Q&A Today

Day 21 - Monday (Week 5)

1. Scoping Rules, Closures, and Decorators

2. Python Scope & the LEGB Rule: Resolving Names in Your Code

Day 22 - Tuesday (Week 5)

2. Python Closures: Common Use Cases and Examples

3. Exploring Scopes and Closures in Python: Code Conversation

4. Debugging the outer() Function

5. Stepping Through inner_returned()

6. Inspecting Dunder Objects

7. Recapping Scopes and Closures

Day 23 - Wednesday (Week 5)

Day 24 - Thursday (Week 5)

2. Decorators Course Introduction and Overview

3. An Example Function

4. Functions as First-Class Objects in Python

5. Inner Functions

6. Returning Functions From Functions

7. Section 1 Review

8. Overview of Section 2 on Decorators

9. Simple Decorators

10. Syntactic Sugar

11. Reusing Decorators

12. Decorating Functions With Arguments

13. Returning Values From Decorated Functions

14. Who Are You, Really?

15. Section 2 Review

16. Overview of Section 3 with Real-World Examples

17. Timing Functions With Decorators

18. Debugging Code With Decorators

19. Slowing Down Code With Decorators

20. Registering Plugins With Decorators

21. Decorators 101 Recap and Review

22. Exercise: Controlling the Eager Turtles

Day 25 - Friday (Week 5)

2. Live Instructor Q&A Today

Day 26 - Monday (Week 6)

1. Data Types and Data Structures

2. Differences Between Python's Mutable and Immutable Types (Overview)

3. Understanding Mutable vs Immutable Types

4. Learning the Difference Between a Variable Name and the Object

5. Looking at Immutable Built-in Data Types: Numbers & Booleans

6. Seeing More Immutable Built-in Data Types: Strings & Tuples

7. Switching to Mutable Built-in Data Types: Lists

8. Exploring Mutable Built-in Data Types: Dictionaries & Sets

9. Avoiding Mutability-Related Gotchas: Aliasing & Mutating Arguments

10. Avoiding Further Gotchas: Mutable Default Arguments & Copying Objects

11. Differences Between Python's Mutable and Immutable Types (Summary)

12. Exercise: Mutable and Immutable Types

Day 27 - Tuesday (Week 6)

1. Tuples, Sets, and Frozen Sets

2. Lists and Tuples in Python: Overview

3. Lists: Ordered & Arbitrary

4. Indexing and Slicing

5. Operators and Built-In Functions

7. Lists: Mutable & Dynamic

8. List Methods

9. List Methods With Return Values

10. Defining Tuples

11. Tuple Assignment, Packing, and Unpacking

12. Lists and Tuples in Python: Conclusion

13. Sets in Python (Overview)

14. What Is a Set?

15. Immutable vs. Hashable

16. Defining a Set in Python

17. Length, Membership, and Iteration

18. Union, Intersection, and Difference

19. Disjoint, Subset, and Superset

20. Add, Remove, Discard, Pop, and Clear

21. Different Update Methods

22. Augmented Assignment (Sets)

23. Frozen Sets

24. Augmented Assignment (Frozen Sets)

26. Set Speed Test

27. Sets in Python (Summary)

Day 28 - Wednesday (Week 6)

Day 29 - Thursday (Week 6)

1. The collections Module

2. Python's collections: A Buffet of Specialized Data Types

3. Exercise: Collecting Your Thoughts About collections

Day 30 - Friday (Week 6)

1. Writing Clean, Pythonic Code With namedtuple (Overview)

2. Using namedtuple

3. Providing Optional Factory Arguments

4. Understanding namedtuple Class Utilities

5. Writing Cleaner Code

6. Comparing Data Structures

7. Extending namedtuple Classes

8. Writing Clean, Pythonic Code With namedtuple (Summary)

9. Choosing a Data Structure

10. Live Instructor Q&A today

Days 31 - 40 (Weeks 7 and 8)

1. Welcome to the Final Two Weeks: Recipe Management Application Project

2. Setting Out the Project Requirements

Extra: SOLID Principles

1. Design and Guidance: OOP in Python (Overview)

2. The Decision to Use Classes

3. Single Responsibility

5. Liskov Substitution

6. Interface Segregation

7. Dependency Inversion

8. SOLID Principles

View Course Details »

Certificate of Completion

This person’s account is verified and was created on Feb. 16, 2021. Real Python certifies their completion of the Intermediate Python Deep Dive: Write Better Python and Build Better Systems course on May 14, 2025.

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