Python Programming – From Basics to Real-World

Duration: 4 Months | Daily: 2 Hours | Sunday: Off

  • Module 1: Introduction to Python
    Learn Python’s background, installation, and environment setup.

  • Module 2: Syntax, Variables & Data Types
    Understand variables, numbers, strings, lists, tuples, and dictionaries.

  • Module 3: Control Structures
    Write decision-making and looping programs with if, for, and while.

  • Module 4: Functions & Modules
    Create reusable functions and use built-in and custom modules.

  • Module 5: File Handling
    Learn to read, write, and manage text, CSV, and JSON files.

  • Module 6: Error & Exception Handling
    Handle runtime errors using try, except, and finally.

  • Module 7: Object-Oriented Programming (OOP)
    Understand classes, objects, inheritance, and encapsulation.

  • Module 8: Working with Libraries
    Explore essential libraries like math, os, and datetime.

  • Module 9: Mini Projects
    Develop small applications such as a calculator, quiz app, or file organizer.

  • Module 10: Real-World Project
    Build a complete Python application and deploy it locally.

Python for Data Science & Machine Learning

Duration: 6 Months | Daily: 2 Hours | Sunday: Off

  • Module 1: Introduction to Data Science
    Learn the concepts and workflow of data science projects.

  • Module 2: Python Libraries for Data Handling
    Master NumPy and Pandas for data manipulation and analysis.

  • Module 3: Data Visualization
    Use Matplotlib and Seaborn to create insightful graphs and charts.

  • Module 4: Exploratory Data Analysis (EDA)
    Clean and prepare datasets for machine learning models.

  • Module 5: Statistics & Probability for Data Science
    Learn statistical measures, distributions, and hypothesis testing.

  • Module 6: Machine Learning Basics
    Introduction to supervised and unsupervised learning with Scikit-learn.

  • Module 7: Regression & Classification Models
    Build predictive models using linear regression and decision trees.

  • Module 8: Clustering & Dimensionality Reduction
    Work on k-means clustering and PCA.

  • Module 9: Model Evaluation & Optimization
    Learn about cross-validation and hyperparameter tuning.

  • Module 10: Real-World Data Project
    Complete a hands-on project using a public dataset.

Python for Cybersecurity

Duration: 6 Months | Daily: 2 Hours | Sunday: Off

  • Module 1: Introduction to Cybersecurity Concepts
    Understand cyber threats, attacks, and Python’s role in defense.

  • Module 2: Python Basics for Security Professionals
    Learn Python syntax, libraries, and setup tailored for security tasks.

  • Module 3: Working with Files and Logs
    Automate file operations and analyze log files for unusual activity.

  • Module 4: Network Scanning & Enumeration
    Use Python to scan ports and collect information about hosts.

  • Module 5: Packet Sniffing & Analysis
    Implement network sniffers using Scapy to monitor traffic.

  • Module 6: Password Cracking & Hashing
    Understand encryption, hashing, and brute-force automation ethically.

  • Module 7: Web Security Testing
    Automate vulnerability detection for common web attacks.

  • Module 8: Secure Coding & Defense Automation
    Write scripts to detect, block, and report threats automatically.

  • Module 9: Cybersecurity Project
    Create a mini tool like a log analyzer or network scanner.

Python Django Web Development

Duration: 6 Months | Daily: 2 Hours | Sunday: Off

  • Module 1: Introduction to Django Framework
    Learn how Django simplifies backend web development.

  • Module 2: Django Project Setup
    Install Django, create a new project, and explore its structure.

  • Module 3: Models, Views & Templates (MVT Architecture)
    Understand the Django MVT framework for dynamic web pages.

  • Module 4: Working with Databases
    Use Django ORM to create and manage SQL databases.

  • Module 5: Forms & User Input Handling
    Create and validate forms securely.

  • Module 6: Authentication & User Management
    Add login, signup, and admin functionality.

  • Module 7: Static & Media Files
    Handle images, CSS, and JS files effectively.

  • Module 8: Django REST Framework (DRF)
    Build APIs for web and mobile apps.

  • Module 9: Deployment on Cloud
    Deploy your Django site to platforms like Heroku or PythonAnywhere.

  • Module 10: Capstone Project
    Build a complete web app such as a blog, e-commerce, or portfolio.

Python with Streamlit for AI Applications

Duration: 4 Months | Daily: 2 Hours | Sunday: Off

  • Module 1: Introduction to Streamlit
    Learn how Streamlit turns Python scripts into interactive web apps.

  • Module 2: Streamlit Basics
    Create simple dashboards using widgets, charts, and data frames.

  • Module 3: Integrating Python AI Models
    Connect AI/ML models built in TensorFlow or Scikit-learn with Streamlit.

  • Module 4: Data Visualization
    Create real-time visualizations for predictions and analysis.

  • Module 5: Custom UI Design
    Use Streamlit themes and layouts to design user-friendly dashboards.

  • Module 6: File Uploads & API Integration
    Add file inputs and connect with external APIs.

  • Module 7: Deploying Streamlit Apps
    Host apps on Streamlit Cloud or other servers.

  • Module 8: AI Dashboard Project
    Build an AI-based web app (like sentiment analysis or image detection).

Python for Automation & Scripting

Duration: 4 Months | Daily: 2 Hours | Sunday: Off

  • Module 1: Introduction to Automation
    Learn how automation saves time and reduces repetitive work.

  • Module 2: Working with the OS Module
    Automate file management, renaming, and system tasks.

  • Module 3: Web Scraping
    Use BeautifulSoup and Selenium to extract data from websites.

  • Module 4: Excel & PDF Automation
    Work with openpyxl, pandas, and PyPDF2 for report generation.

  • Module 5: Email & Messaging Automation
    Send automatic emails and WhatsApp messages using Python scripts.

  • Module 6: Task Scheduling
    Automate scripts using schedulers like Task Scheduler or CRON.

  • Module 7: GUI Automation
    Control applications with PyAutoGUI for clicks and typing.

  • Module 8: Real-World Projects
    Build an auto-file organizer, scraper bot, or report generator.

Python for Networking & Ethical Hacking

Duration: 6 Months | Daily: 2 Hours | Sunday: Off

  • Module 1: Networking Fundamentals
    Understand IPs, ports, and protocols used in computer networks.

  • Module 2: Python Networking Libraries
    Work with socket, ipaddress, and scapy for network communication.

  • Module 3: Network Scanning
    Build port and subnet scanners to detect live systems.

  • Module 4: Packet Analysis & Sniffing
    Capture and analyze network packets using Python scripts.

  • Module 5: Building Network Tools
    Create your own ping tool, port scanner, or network monitor.

  • Module 6: Ethical Hacking Automation
    Automate vulnerability scanning and information gathering.

  • Module 7: Wireless Network Hacking (Ethical)
    Learn about Wi-Fi security, encryption, and penetration testing ethics.

  • Module 8: Cyber Defense Scripts
    Develop detection and alerting scripts for suspicious activities.

  • Module 9: Capstone Project
    Create a full Python-based network security toolkit.

Python with Data Science – Professional Training

Duration: 6 Months | Daily: 2 Hours | Sunday: Off

  • Module 1: Introduction to Data Science & Python
    Understand what data science is, where it’s used, and how Python powers modern analytics. Set up your Python environment using Anaconda and Jupyter Notebook.

  • Module 2: Python Programming Fundamentals
    Learn syntax, variables, loops, functions, and data structures (lists, tuples, sets, and dictionaries). Practice clean and efficient coding for data tasks.

  • Module 3: Working with Data Using NumPy
    Master NumPy arrays, indexing, slicing, mathematical operations, and data manipulation techniques.

  • Module 4: Data Analysis with Pandas
    Learn how to clean, filter, merge, group, and summarize large datasets efficiently using Pandas.

  • Module 5: Data Visualization with Matplotlib & Seaborn
    Create charts, histograms, heatmaps, and trend visuals to represent insights clearly.

  • Module 6: Data Cleaning & Preprocessing
    Handle missing values, duplicates, and inconsistent data. Learn techniques like normalization and encoding for machine learning readiness.

  • Module 7: Exploratory Data Analysis (EDA)
    Explore datasets using statistical summaries and visualizations to identify patterns, trends, and anomalies.

  • Module 8: Statistics & Probability for Data Science
    Learn key concepts including mean, median, variance, distributions, and hypothesis testing for data interpretation.

  • Module 9: Introduction to Machine Learning with Scikit-learn
    Build predictive models using regression, classification, and clustering algorithms. Understand model training, testing, and evaluation.

  • Module 10: Feature Engineering & Model Optimization
    Improve model accuracy with scaling, encoding, feature selection, and hyperparameter tuning.

  • Module 11: Working with Real-World Datasets
    Analyze public datasets from Kaggle or UCI Repository and practice end-to-end data workflows.

  • Module 12: Introduction to AI & Deep Learning (Overview)
    Understand the basics of neural networks, TensorFlow, and how deep learning connects with data science.

  • Module 13: Data Science Tools & Libraries
    Explore essential tools like Jupyter, Google Colab, and libraries such as SciPy and Statsmodels.

  • Module 14: Project: Data-Driven Decision Making
    Work on a practical project involving real business data — from analysis to prediction and presentation.

  • Module 15: Capstone Project & Portfolio
    Create and present a full professional data science project with documentation, code, and insights.

  • Module 16: Freelancing & Career Preparation
    Learn how to offer data analysis and visualization services on freelancing platforms, write proposals, and manage clients professionally.

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