Master Python Development in Jodhpur - Beginner Syllabus
Python Programming Course in Jodhpur
This Beginners Python Programming course introduces the fundamentals of coding in a easy and feasible way. Learners will explore core topics like datatypes, variables, conditional statements, loops, functions, and error handling. No prior programming experience is required—just curiosity and desire to learn. By the end of the course, students will be able to write basic Python programs and build a continuous framework for advanced topics in coding, data analysis, or web development.
Why Python?
Python is one of the world’s most popular programming languages thanks to its readability, vast ecosystem of libraries, and applicability across domains — from web services and APIs to data science, machine learning, automation, and DevOps. Its gentle learning curve and strong community support make it ideal for rapid prototyping and production systems alike.
Course Highlights
- Beginner Friendly: Start from basics like syntax and variables.
- Practical Tools: IDL, V S Code, PyCharm, Jupyter, virtual environments.
- Core Concepts: Conditional statement, control flow, functions.
- File & Error Handling: File I/O, exceptions, and robust code.
- Hands-on Projects: Small projects, scripts, and basic projects.
Who Should Join?
- Beginners with no coding experience who want to start learning programming.
- Students interested in building a foundation for computer science or data science.
- Professionals from non-IT fields looking to automate tasks or enhance career opportunities.
- Aspiring web developers who want to understand programming basics before diving deeper.
- Data enthusiasts who want to explore data analysis, visualization, or machine learning.
- Entrepreneurs and business owners seeking to use Python for problem-solving or process automation.
Join the Python Revolution Today
Begin your journey now — Python empowers you to work across industries, from web to automation. This course gives you basic knowledge & skills, projects, and career guidance to succeed.
- History and Origins of Python — creator, development timeline, and philosophy (PEP 20).
- Features and Applications of Python — readability, libraries, use-cases (web, automation, data, scripting).
- Setting up Python Environment — installing Python (official installer / Anaconda), choosing IDEs (PyCharm, VS Code, Jupyter), and verifying installation.
- Running Your First Python Program — scripts, REPL, and running .py files from terminal/IDE.
- Python Syntax — indentation rules, block structure, and comments (#, multi-line).
- Variables and Data Types — int, float, string, boolean; naming conventions and dynamic typing.
- Type Casting in Python — int(), float(), str(), bool(), and safe conversions.
- Input/Output — using
input() and print(), formatted strings (f-strings).
- Arithmetic Operators —
+, -, /, %, *, // (floor division).
- Comparison Operators —
==, !=, >, <, >=, <=.
- Logical Operators —
and, or, not.
- Assignment Operators —
=, +=, -=, *=, /=, etc.
- Bitwise Operators —
&, |, ^, ~, <<, >> (basic examples)
- Identity Operators —
is, is not (object identity vs equality).
- Membership Operators —
in, not in for sequences and collections.
- Conditional Statements —
if, elif, else and nested conditions.
- Loops in Python
for loops — iterating over ranges, lists, strings.while loops — loop conditions and loop variables.
- Loop Control Statements —
break, continue, pass and their use-cases.
- Defining Functions —
def, function naming, docstrings and scope.
- Arguments and Parameters — positional and keyword parameters.
- Default, Keyword & Arbitrary Arguments — default args,
args and *kwargs.
- Return Statement — returning values, multiple returns, None.
- Lambda Functions — small anonymous functions and simple examples.
- Lists — creating, accessing, modifying, slicing, common list methods.
- Tuples — immutability, packing & unpacking.
- Dictionaries — key-value access, methods (.get, .items, .keys, .values), iteration.
- Sets — unique items, set operations (union, intersection, difference) and methods.
- Reading from a File —
open(), .read(), .readline(), context managers (with).
- Writing to a File — write, append, and proper resource handling.
- File Modes —
r, w, a, rb, wb, and text vs binary modes.
- Handling File Exceptions — catching I/O errors and safe file operations.
- Errors in Python — syntax vs runtime errors and common exception types.
- Try / Except / Finally — structured exception handling and cleanup.
- Raising Exceptions —
raise for error signaling.
- Custom Exceptions — creating and using user-defined exception classes.
