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Comprehensive Python Programming Course Content

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Learn Comprehensive Python Programming Course Content

Cohort Based Learning – Only 10 Seats
60+ hours of live virtual training
New Age Curriculum with Gen AI tools
3 Real time projects and capstone project
Certification of completion

Why choose Hirekeyz ?

Curriculum

Industry relevant Curriculum

Training

Job-Ready Training

Projects

Capstone projects & case studies

Flexible

Flexible Learning

Team Working

Tools you will learn

NumPy

Matplotlib

Pandas

Excel

Power BI

AWS

Scikit-learn

SQL

Course Syllabus

Module 1: Introduction to Python (3 Hours)

What is Python and Why Python?
Installing Python and IDEs (PyCharm, VS Code, Jupyter)
Writing and executing your first Python script
Python syntax, keywords, and indentation
Understanding Python’s dynamic typing
Using the REPL (Read-Eval-Print Loop)

Module 2: Variables, Data Types & Operators (3 Hours)

Variables and assignment
Built-in data types: int, float, str, bool
Type conversion and casting
String operations and formatting
Arithmetic, comparison, logical, and assignment operators

Module 3: Control Flow (4 Hours)

Conditional statements (if, elif, else)
Looping structures (for, while)
break, continue, pass statements
List comprehensions

Module 4: Data Structures (6 Hours)

Lists: creation, indexing, slicing, and methods
Tuples and sets: immutability and usage
Dictionaries: key-value pairs and operations
Nested data structures
Iterating through data structures

Module 5: Functions and Modules (5 Hours)

Defining and calling functions
Function arguments: default, keyword, *args, **kwargs
Return values and scope (local vs global)
Lambda functions and map/filter/reduce
Creating and importing modules
Built-in functions and packages (math, random, datetime)

Module 6: File Handling (3 Hours)

Reading from and writing to text files
Working with CSV, JSON files
File pointers and context managers (with statement)

Module 7: Exception Handling (2 Hours)

Types of errors
Try-except blocks
Finally and else
Custom exceptions

Module 8: Object-Oriented Programming (6 Hours)

Classes and objects
Constructors and instance variables
Inheritance and polymorphism
Encapsulation and abstraction
__str__, __repr__, and special methods

Module 9: Advanced Python Concepts (5 Hours)

Decorators and generators
Iterators and iterable protocol
List, set, dict comprehensions
Context managers and with statements
The collections and itertools module

Module 10: Working with Libraries (5 Hours)

Installing packages using pip
NumPy basics for numerical computation
Pandas basics for data manipulation
Matplotlib for basic data visualization
Regex (re module) for pattern matching

Module 11: Web Scraping and APIs (4 Hours)

HTTP requests with requests module
Parsing HTML with BeautifulSoup
Working with APIs and JSON
Project: Scraping job listings / weather data

Module 12: Unit Testing and Debugging (3 Hours)

Writing test cases with unittest and pytest
Debugging using breakpoints and logging
Code quality and linters (flake8, pylint)

Module 13: Working with Databases (3 Hours)

SQLite with sqlite3 module
Basic CRUD operations
Connecting to external DBs (MySQL/PostgreSQL)

Module 14: Final Project (5 Hours)

Build a CLI To-Do List Manager
Create a Personal Expense Tracker using CSV
Develop a Weather Dashboard using API
Data Analysis on Retail Dataset using Pandas
Project planning, design, implementation, and presentation

Program Highlights

Experts

Learn from experts

Courses taught by experienced professors and industry professionals.

Certifications

Certification of Completion

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Gen AI

New Age Curriculum

40+ Hours of learning of new tools, models and projects.

Learning Tools

Interactive Learning Tools

Access to videos, quizzes, and discussions for an engaging learning experience.

Affordable Fees

Affordable Tuition Fees

Access quality education without the high cost of traditional classrooms.

24/7 Access

24/7 Access to Study Material

Get access to recorded videos and assessments.

Who Should Do The Comprehensive Python Programming Course?

Aspiring Analysts
Individuals looking to start a career in data analysis or analytics-related fields.
Career Changers
Professionals from non-technical backgrounds eager to transition into the high-demand field of data analytics.
IT & Engineering Graduates
Students or professionals with technical degrees who want to specialize in data analysis.
Business Professionals
Managers or executives aiming to make data-driven decisions and enhance business outcomes.
Freelancers & Consultants
Professionals who want to offer data analysis as a service to clients.
Upskilling Professionals
Those in adjacent fields like marketing, finance, or operations who want to add data analytics to their skill set.

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