Python Programming
Start with clean syntax and core concepts, then climb to object-oriented, data-driven, and production-ready Python.
💡 Skill is the Biggest Asset
Curriculum
Beginner Level
00
Why You Need This Course
Python in AI & Data Science, course goals
01
Getting Started with Python
Python overview, Jupyter Notebooks setup
02
IDEs and Coding Environments
PyCharm, VS Code, Jupyter comparison
03
Basic Syntax & Data Types (Part 1)
Variables, data types, input/output
04
Basic Syntax & Data Types (Part 2)
String manipulation, type casting
05
Conditional Statements
if, elif, else, logical operators
06
Loops in Python
for loops, while loops, loop control
07
Functions and Modules
Function basics, scope, standard libraries
Intermediate Level
00
Why You Need This Course
Python in AI & Data Science, course goals
01
Getting Started with Python
Python overview, Jupyter Notebooks setup
02
IDEs and Coding Environments
PyCharm, VS Code, Jupyter comparison
03
Basic Syntax & Data Types (Part 1)
Variables, data types, input/output
04
Basic Syntax & Data Types (Part 2)
String manipulation, type casting
05
Conditional Statements
if, elif, else, logical operators
06
Loops in Python
for loops, while loops, loop control
07
Functions and Modules
Function basics, scope, standard libraries
08
Lists and Tuples
List operations, comprehensions, tuples
09
Dictionaries and Sets
Key-value pairs, set operations
10
Working with Files
File I/O, CSV handling, data processing
11
Error Handling & Exceptions
try/except blocks, custom exceptions
Expert Level
00
Why You Need This Course
Python in AI & Data Science, course goals
01
Getting Started with Python
Python overview, Jupyter Notebooks setup
02
IDEs and Coding Environments
PyCharm, VS Code, Jupyter comparison
03
Basic Syntax & Data Types (Part 1)
Variables, data types, input/output
04
Basic Syntax & Data Types (Part 2)
String manipulation, type casting
05
Conditional Statements
if, elif, else, logical operators
06
Loops in Python
for loops, while loops, loop control
07
Functions and Modules
Function basics, scope, standard libraries
08
Lists and Tuples
List operations, comprehensions, tuples
09
Dictionaries and Sets
Key-value pairs, set operations
10
Working with Files
File I/O, CSV handling, data processing
11
Error Handling & Exceptions
try/except blocks, custom exceptions
12
NumPy for Mathematical Operations
Arrays, vectorization, matrix operations
13
Data Analysis with pandas
DataFrames, data cleaning, manipulation
14
Data Visualization
matplotlib, seaborn, insight-driven plots
15
Fundamentals of Machine Learning
ML concepts, supervised vs unsupervised
16
Hands-on with scikit-learn
Model implementation, evaluation metrics
17
NLP Basics with Python
Text preprocessing, sentiment analysis
18
APIs and Data Collection
HTTP requests, JSON parsing, automation
19
Building APIs with FastAPI
API development, ML model integration
20
Capstone Project & Future Paths
Final project, advanced topics preview