Computer Educator

# Artificial Intelligence Course in Karachi

• Data Science Play Ground
• What is Machine Learning.
• First Image CLassifier.
• Data Science and Machine Learning Cheat Sheet
• Recommender Systemt using K nearst Means
• Data Science vs Machine Learning vs Artificial Intelligence
• Sumarizing it all
• AI Project Framework
• STep-1 Problem Defination
• Step-2 Data
• Step-3 Evaluation.
• Step-4 Features
• Step-5 Modelling.
• Step-5 Data Validation
• Step-6 Course Correction
• Tools needed for AI Project
• What is Programming Language
• Python Interpreter and First Code
• Python 3 vs Python 2
• Formula to Learn Coding
• Data Types and Basic Arithmatic
• Basic Arithmetic Part-2
• Rule of Programming
• Mathematical Operators and Order of Precedence
• Variables and their BIG No No
• Statement vs Expression
• Augmented Assignment Operator
• String Data Type
• String Concatenation
• type Conversion
• String Formatting
• Indexing
• Immutability
• Built in Function and Methods
• Boolean Data Type
• Exercise
• Data Structor and Lists
• Lists continued
• Matrix from Lists
• List Methods
• Lists Methods 2
• creating Lists Programatically
• Dictionary
• Dic key is Un Changeable
• Most Used Methods on Dictionaries
• Tuple Data Types
• Sets data Types
• Intro to Process of Coding-Conditionals
• if else Statement
• AND OR keywords
• Boolean result of Different values
• Logical Operators
• Identity Operator
• for loop and Iterables
• Nested For loop
• Exercise for loop
• Range Function
• While Loop
• Continue Break Pass Keywords
• Exercise Draw a Shape
• Functions
• Why of Functions
• Parameter vs Argument
• Default Parameters
• Return Keyword
• Doc String
• Good Programming Practices
• args and kwargs
• Exercise
• Scope of a Function
• Scope Rules-1
• Scope Rules-2
• GLobal vs nonlocal Keywords
• Programming Best Practices-2
• Special Functions map
• Special Functions Filter.
• Special Functions Zip
• Special Functions reduce
• List Comprehension Case-1,2 and 3
• Sets and Dictionary Comprehension
• Python Modules
• Python packages
• Tools for Data Science Environment
• Who is Mr. Conda
• Setting Up Machine Learning Project
• Blue Print of Machine Learning Project
• Installing conda
• Installing tools
• Starting Jupyter Notebook
• Installing for MacOS and Linux
• Walkthrough of Jupyter notebook 1
• Walkthrough of Jupyternotebook 2
• Summing it Up
• Tools needed
• Pandas and What we Will cover
• Data Frames
• How to Import Data
• Describing Data
• Data Selection
• Data Selection 2
• Changing Data
• Manipulating Data
• What Actually ML Model is
• Intro to Sklearn
• Step-1 Getting Data Ready Split Data
• Step-2 Choosing ML model
• Step-3 Fit Model
• Step-4 Evaluate Model
• Step-5 Improve Model
• Step-6 Save Model.
• What we are going to Do
• Step-1 Getting Data Split Data
• Step-1 Getting Data Ready Converting Part-1
• Getting Data Ready Converting Part-2
• Getting Data Anatomy of Conversion
• Getting Data Second Method of Conversion
• Getting Data Missing Values.
• Getting Data Missing Values method 2
• Choosing Machine Learning Model
• Using map to choose model
• Step-2 How to Choose Better model
• Choosing Model for Classification problem
• Fit the Model
• Running Prediction
• Step-3 predict_proba method
• Step-3 Running Prediction on Regression Problem
• Step-4 Evaluating Machine Learning Model Default Scoring
• Step-4 WHat is Cross Validation
• Step-4 Accuracy (Classification Model)
• Step-4 Area Under the Curve Part-1
• Step-4 Area Under the Curve Part-2.
• Step-4 Area Under the Curve Part-3 Plotting
• Confusion Matrix Calculate
• Step-4 Confusion Matrix Plot
• Step-4 Classification Report Important concepts
• Step-4 Classification Report Fully Explained
• Step-4 R2 for Regression Problems
• Step-4 Mean Absolute Error for Regression Problems
• Step-4 Mean Square Error for Regression Problems
• Step-4 Scoring parameters for Classification
• Step-4 Scoring parameters for Regression
• Step-4 Evaluation using Functions Classification
• Step-4 Evaluation using Functions Regression
• Step-5 Improving Model by Hyper parameters
• Step-5 Improving Model by Hyperparameters manually
• Step-5 Evaluation Metrics in One Function
• Step-5 Hyperparameters Comparison
• Tunning Hyperparameters using RSCV
• Tunning Hyperparameters using RSCV Part-2
• Tunning Hyperparameters using GSCV
• Results Comparison
• Save Load Model with Pickle Method-1
• Save Load Model with joblib Method-2

## Introduction

Welcome to our comprehensive guide on artificial intelligence (AI) courses in Karachi. In this article, we delve into the exciting world of AI and how it is transforming industries and driving innovation. Whether you are a tech enthusiast, a student, or a professional looking to upgrade your skills, this guide will provide you with valuable insights into the best AI courses available in Karachi.

## The Rise of Artificial Intelligence

Artificial Intelligence has become a game-changer in today’s digital landscape. It encompasses the development of intelligent machines that can simulate human intelligence, enabling them to perform tasks that typically require human intervention. From voice assistants to self-driving cars, AI has permeated various sectors, revolutionizing the way we live and work.

## Why Choose Karachi for AI Education?

Karachi, the bustling metropolis of Pakistan, has emerged as a hub for technology and innovation. With its vibrant tech community and numerous educational institutions, the city provides a conducive environment for individuals seeking to pursue AI courses. Karachi’s thriving IT industry and access to cutting-edge research make it an ideal destination to embark on your AI education journey.

## Top AI Courses in Karachi

This course focuses on teaching advanced machine learning techniques, including neural networks, deep learning, and natural language processing. By understanding these concepts, you’ll be equipped with the skills to develop intelligent algorithms and models.

##### Data Science with Python:

This course introduces you to the fundamentals of data science using Python. You’ll learn how to analyze complex datasets, extract valuable insights, and make data-driven decisions using Python libraries such as NumPy, Pandas, and Matplotlib.

##### Computer Vision and Image Recognition:

This course explores the field of computer vision, where you’ll learn how to develop algorithms that can interpret and analyze visual data. From object detection to facial recognition, this course empowers you to build cutting-edge applications in the field of computer vision.

##### Ethics in AI:

As AI continues to evolve, ethical considerations become crucial. This course delves into the ethical implications of AI and guides you on how to develop AI systems that are fair, transparent, and unbiased.

This course is tailored for professionals and business leaders who want to understand how AI can impact their organizations. You’ll gain insights into AI strategy, implementation, and its potential for driving business growth and innovation.

## Benefits of Pursuing an AI Course in Karachi

By enrolling in an AI course in Karachi, you unlock a world of opportunities and advantages. Here are some of the key benefits:

AI skills are in high demand across industries. By acquiring expertise in AI, you enhance your employability and open doors to exciting job prospects in fields such as data science, machine learning, and AI development.

##### Industry-Relevant Curriculum:

The AI courses in Karachi are designed to equip you with the skills that align with industry requirements. You’ll learn the latest tools, techniques, and frameworks used in the field, ensuring you stay ahead in this rapidly evolving domain.

##### Networking Opportunities:

Karachi’s tech community offers ample networking opportunities. By joining an AI course, you’ll connect with like-minded individuals, industry professionals, and potential mentors, fostering valuable relationships that can propel your career forward.

##### Practical Experience:

Many AI courses in Karachi provide hands-on projects and real-world case studies, allowing you to apply your knowledge in practical scenarios. This practical experienceenhances your understanding of AI concepts and prepares you to tackle real-world challenges.