In this Part-1 of Mastering Python, you will embark on an in-depth journey into the core concepts of Python programming, focusing on functional programming techniques. This course is designed to provide a strong foundation in Python by covering the following key topics:

1. Variables and Memory References:
   Understand that variables in Python are simply symbols pointing to objects in memory, and how this impacts the way you manage data.

2. Namespaces and Scopes:
   Explore how Python handles variable scope and namespaces, crucial for understanding variable visibility and lifetime.

3. Python's Numeric Types:
   Dive into Python’s rich set of numeric types, including integers, floats, and complex numbers, and their behavior in different contexts.

4. Python Boolean Type:
   Uncover the intricacies of Python’s boolean type and learn why there’s more to a simple or statement than meets the eye.

5. Run-Time vs Compile-Time:
   Delve into the differences between run-time and compile-time, and how these concepts affect function defaults, decorators, module imports, and more.

6. Functions and Lambdas:
   Gain a comprehensive understanding of Python functions, including lambda expressions, and how to leverage them for concise and powerful coding.

7. Functional Programming Techniques:
   Master functional programming techniques in Python, such as map, reduce, filter, and zip, to write clean, efficient, and expressive code.

8. Closures:
   Learn about closures, how they work, and their significance in creating flexible and reusable code.

9. Decorators:
   Explore the world of decorators, powerful tools for modifying the behavior of functions and methods in a clean, readable manner.

10. Imports, Modules, and Packages:
    Understand how to organize and structure your Python projects using modules and packages, and how to effectively manage imports.

11. Tuples as Data Structures:
    Discover the power of tuples as immutable data structures in Python, and when and how to use them effectively.

12. Named Tuples:
    Go beyond regular tuples with named tuples, a readable and convenient way to handle structured data in Python.