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Python Courses in Lahore 2025

Master in Python skills with Sphere comprehensive training programs. Industry-expert instructors, hands-on projects, virtual internships, lms portals, and career support in Lahore, Pakistan

Rs 30,000/-

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Course Detail

Are you a student or aspiring developer in Lahore searching for a future-ready tech course that combines Python Programming with cutting-edge Artificial Intelligence skills?
Sphere’s Python & AI Development Course is designed to equip you with both core programming expertise and advanced AI development knowledge.

You’ll start by mastering Python programming—covering syntax, data structures, OOP, file handling, libraries (NumPy, Pandas, Matplotlib), automation, and web development with Flask/Django. From there, you’ll dive deep into data science, machine learning, and AI, gaining practical exposure to real-world applications.

Throughout the course, you’ll explore:

  • Core AI Foundations – AI domains, history, applications, and ethics
  • Machine Learning & Deep Learning – Regression, Classification, Clustering, Neural Networks, CNNs, and NLP pipelines
  • Data Science Tools – NumPy, Pandas, Matplotlib, Seaborn for data cleaning, visualization, and analysis
  • Python for Automation – APIs, web scraping, scripting, and workflow automation
  • AI Frameworks & Libraries – TensorFlow, PyTorch, Scikit-learn, and emerging technologies like Transformers and Reinforcement Learning
  • End-to-End Projects – Sentiment analysis, image classification, chatbots, and recommendation systems

Hands-on Experience:
Go beyond theory with capstone projects and internship integration, where you’ll apply your skills on real-world AI tasks. Build a professional portfolio featuring Python apps, ML models, and AI-powered solutions—showcasing your readiness for industry roles.

Whether your goal is to become a Python Developer, Data Scientist, AI Engineer, or Automation Specialist, this comprehensive program gives you the skills, tools, and project experience to launch your tech career with confidence.

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Course Flow or Roadmap

Kickstart your career with the Python & AI Development Course in Lahore at Sphere.
This course delivers hands-on experience and comprehensive knowledge of Python programming, data science tools, and AI-powered solutions. Whether you’re a beginner or looking to upskill, our expert instructors ensure industry-ready training over a 1-year duration.

The course is designed to help you master Python foundations while also leveraging the latest AI technologies to build smart, scalable, and intelligent applications.

Course Curriculum Overview

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    Python Foundations

    Learn Python syntax, data types, variables, operators, control flow, loops, and functions. Build a solid base in programming.

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    Data Structures & File Handling

    Work with lists, tuples, dictionaries, sets, and file I/O operations. Explore CSV, JSON, and external libraries like Pandas for data handling.

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    Object-Oriented Programming (OOP)

    Master classes, objects, inheritance, polymorphism, and encapsulation. Understand how to build scalable applications with OOP.

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    Python Libraries & Web Development

    Use NumPy, Pandas, and Matplotlib for computation, data manipulation, and visualization. Get introduced to Flask and Django for building web applications.

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    AI & Automation Integration

    Explore Machine Learning and AI frameworks like TensorFlow, PyTorch, LangChain, CrewAI, and Ollama. Learn workflow automation with n8n and build intelligent AI agents.

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    Capstone Projects & Portfolio

    Work on real-world projects—ranging from e-commerce systems to AI-driven applications—and graduate with a professional portfolio that demonstrates your skills.

Course Duration & Mode

Duration: 6 Months
Modes: Physical  
Sessions: Twice a Week

Comprehensive Course Modules

Introduction to Python Programming

  • What is Python? Overview and History 

  • Installing Python and Setting Up the Development Environment (IDE, Anaconda, Jupyter, Notebooks) 

  • Python Syntax and Structure 

  • Writing Your First Python Program 

  • Understanding Python’s Interpreted Nature 

  • Data Types: Integers, Floats, Strings, Booleans 

  • Variables, Constants, and Constants 

  • Operators in Python: Arithmetic, Comparison, and Logical 
  • Control Structures: Conditional Statements (if, else, elif) 
  • Loops in Python: for, while, and nested loops 
  • Working with Functions: Defining and Calling Functions 
  • Function Arguments and Return Values 
  • Introduction to Exception Handling (try, except, finally)
  • Lists: Creating, Modifying, and Accessing List Elements 
  • Tuples: Creating and Accessing Immutable Sequences 
  • Dictionaries: Key-Value Pairs, Adding, Modifying, and Deleting Items 
  • Sets: Working with Unique Collections 
  • Understanding List Comprehensions and Set Operations 
  • Introduction to Data Structures from the Standard Library (e.g., collections module)
  • Reading Files (Text, CSV, JSON) in Python 
  • Writing Data to Files: Handling File Writing Modes 
  • Understanding File Handling Best Practices 
  • Working with CSV and JSON Formats 
  • Introduction to External Libraries for File Parsing (e.g., CSV, JSON, and Pandas)
  • Introduction to OOP Concepts: Classes and Objects 
  • Defining Classes and Creating Objects 
  • Instance Variables and Methods 
  • Constructors and the __init__ Method 
  • Inheritance and Method Overriding 
  • Polymorphism and Encapsulation 
  • Python’s Special Methods (e.g., __str__, __repr__, __len__)
  • Importing Standard Libraries and Third-Party Modules 
  • Introduction to Pip: Installing and Managing Packages 
  • Popular Python Libraries for Different Domains:  
  • NumPy (for numerical computation) 
  • Pandas (for data manipulation and analysis) 
  • Matplotlib (for data visualization) 
  • Creating Custom Modules and Organizing Code
  • Web Frameworks Overview: Flask and Django 
  • Introduction to Flask: Building Simple Web Applications 
  • Working with Routes, Templates, and Forms in Flask 
  • Introduction to Django: Setting Up a Django Project 
  • Building and Handling Static and Dynamic Pages 
  • Handling HTTP Requests and Responses in Python Web Apps
  • Introduction to Data Science and Python’s Role 
  • Using NumPy for Data Manipulation and Computation 
  • Pandas for Data Analysis: DataFrames and Series 
  • Data Visualization with Matplotlib and Seaborn 
  • Handling Missing Data and Data Cleaning Techniques 
  • Introduction to Machine Learning with Scikit-Learn
  • Writing Python Scripts for Task Automation 
  • Automating File Operations (File Renaming, Sorting, etc.) 
  • Web Scraping  
  • Working with APIs: Sending Requests and Handling Responses 
  • Automating Emails and Reports 
  • Introduction to Task Scheduling with Cron (Linux) or Task Scheduler (Windows)
Optional
Advanced Python Concepts
  • Advanced Functions: Lambda Functions, Map, Filter, Reduce 
  • Decorators and Generators in Python 
  • Multithreading and Multiprocessing for Concurrency 
  • Memory Management and Performance Optimization in Python 
  • Introduction to Python’s Asynchronous Programming  

Module 11: Final Project & Certification 

  • Hands-on Project: Building a Python Application (e.g., Web Scraper, Data Analysis Tool, 

or Simple Web App) 

  • Code Review and Peer Collaboration 
  • Best Practices for Code Documentation and Commenting 
  • Final Evaluation and Course Completion Certification
Introduction to AI
  • What is AI? Definitions, history, real-world applications
  • AI domains: Perception, Reasoning, Learning, NLP, Robotics
  • Ethical considerations: Bias, privacy, fairness, responsible AI
    – Based on FAJ Academy content
  • Python basics: syntax, data types, control flow, functions, OOP
  • Data handling: NumPy, Pandas, Matplotlib
    – Inspired by UET AI-Trains details
Machine Learning Fundamentals
  • Supervised, Unsupervised, Reinforcement Learning introductions
  • Key algorithms: Regression, Classification, Clustering
  • Model evaluation: accuracy, precision, recall, F1-score
    – Reflecting Upskill Intern curriculum
  • Neural networks: architectures, activation functions, forward/backpropagation
  • Hands-on: Build and train a basic neural network in Python
    – Also from Upskill Intern outline
Computer Vision
  • CNN basics, convolution and pooling layers
  • Build a simple image classifier (e.g., digit recognition)
  • Text preprocessing, tokenization, NLP pipelines
  • Mini project: Sentiment analysis or text classification
    – Both modules are standard in Pakistani AI programs (e.g. IDEO College)
  • Basics of RL: MDPs, Q-learning fundamentals
  • Overview: Transformers, language models, ethics, explainability
    – Inspired by WELC’s curriculum coverage
  • Final mini-project: e.g., chatbot, recommendation system, or image classifier
  • Deliverables: Code, report/README, and demo presentation
  • Focus on end-to-end workflow: data → model → evaluation → documentation

Through collaboration with industry or partner firms, participants undertake:

  • Supervised internship (2–3 weeks): Apply skills on a real-world AI task
  • Guidance: Mentor check-ins, weekly updates, feedback cycles
  • Deliverables: Project code, documentation, internship report/presentation
    – Modeled after features like mentorship, portfolio creation, and industry integration seen in AI Institute of Pakistan programs
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