Module 1 — Python Fundamentals
• Introduction to Python
• Why Python is important in AI and software development
• Installing Python
• Python interpreter & execution
• VS Code / PyCharm
• Python syntax
• Comments
• Variables
• Constants & naming conventions
• Data types: int, float, str, bool, None
• Type checking — type()
• Type conversion
• Input and output
• Operators: Arithmetic, Assignment, Comparison, Logical, Identity, Membership, Bitwise
Module 2 — Control Flow
• if
• if-else
• if-elif-else
• Nested conditions
• for loops
• while loops
• break
• continue
• pass
• range()
• Nested loops
• Conditional expressions
Module 3 — Python Data Structures
• List — Creating lists, Indexing, Slicing, Adding/removing, Updating, Sorting, List methods, List comprehension
• Tuple — Creating tuples, Tuple unpacking, Immutable data
• Set — Unique values, Set operations, Membership, Set comprehension
• Dictionary — Key/value, Accessing values, Adding/updating, Removing, Dictionary methods, Nested
dictionaries, Dictionary comprehension
Module 4 — Functions
• Creating functions
• Parameters
• Arguments
• Return values
• Default arguments
• Keyword arguments
• *args
• **kwargs
• Scope
• Local/global variables
• Lambda functions
• map()
• filter()
• reduce()
• Recursion
• Docstrings
• Type hints
Module 5 — Strings & Text Processing
Very important for AI and LLM applications
• String indexing
• String slicing
• String methods
• Formatting
• f-strings
• Regular expressions
• Searching text
• Replacing text
• Splitting/joining
• Cleaning text
• Parsing text
• Unicode
• Basic NLP concepts
Module 6 — Files & Data Handling
• Reading files
• Writing files
• with open()
• TXT files
• CSV
• JSON
• XML basics
• File paths
• Directories
• pathlib
• File upload/download
• Handling large files
Module 7 — Exception Handling
• Errors vs exceptions
• try
• except
• else
• finally
• raise
• Custom exceptions
• Error logging
• Defensive programming
Module 8 — Object-Oriented Programming
Students should understand OOP, but not spend months on complicated OOP theory.
• Classes
• Objects
• Constructors
• Instance variables
• Methods
• Class variables
• Class methods
• Static methods
• Encapsulation
• Inheritance
• Method overriding
• Polymorphism
• Abstract classes
• Properties
• Magic/dunder methods
• Dataclasses
Module 9 — Modules, Packages & Environments
Very important for professional development.
• Modules
• import
• from ... import
Module 10 — Modern Python Features
• List/dict/set comprehensions
• Iterators
• Generators
• yield
• Decorators
• Context managers
• enumerate()
• zip()
• any()
• all()
• sorted()
• dataclasses
• Type hints
• match-case
• Structural pattern matching
• async / await
Module 14 — Data Analysis
Now Python starts becoming extremely useful for AI.
• NumPy — Arrays, Dimensions, Indexing, Slicing, Vector operations, Mathematical operations, Broadcasting
• Pandas — Series, DataFrame, Reading CSV, Reading Excel, Filtering, Sorting, Grouping, Aggregation, Missing
data, Merging, Cleaning data, Exporting data
• Visualization — Matplotlib, Seaborn basics, Plotly basics
Module 25 — Git & GitHub
Mandatory for professional students.
• Git
• Repository
• Commit
• Branch
• Merge
• Pull
• Push
• Pull request