AI & Data Science Bootcamp

Dive deep into the world of AI and Data Science with our hands-on, industry-focused bootcamp. Master machine learning, data analytics, and real-world problem solving — while also building cutting-edge Agentic AI systems and powerful automations using n8n.

Rs. 7,499/-

Monthly Rs. 9,000

20% Discount

Enroll Now
Affordable Tech Programs
Affordable Tech Programs

start coding with confidence!

Take the first step towards a brighter future with cutting-edge training from industry leaders

How to use pandas for data analysis in Python

29th Mar 26

Start Date

Data preprocessing techniques in machine learning

Sat-Sun

Class Days

Easy data science interview questions and answers

4 Months

Duration

Free datasets for practicing data science

2:00-04:00 PM

Class Timing

Reserve your seat now

Carefully Curated Curriculum

  • Introduction to Variables
  • Assigning and Reassigning Values
  • Basic Operations with Variables
  • Variable Naming Conventions
  • Practical Examples and Exercises
  • Overview of Data Types (int, float, str, bool)
  • String Operations and Methods
  • Type Conversion
  • Practical Examples and Exercises
  • Common String Manipulation Tasks
  • Conditional Statements (if, elif, else)
  • Logical Operators (and, or, not)
  • Nested Conditionals
  • Practical Examples and Exercises
  • Combining Control Flow with Logical Operators
  • Introduction to Lists
  • List Operations and Methods
  • Using the random Module
  • Practical Examples and Exercises
  • Creating and Modifying Lists
  • Introduction to For Loops
  • Loop Control Statements (break, continue, pass)

  • Dictionary structure & usage

  • Looping through key-value pairs

  • Creating reusable functions

  • Function parameters & returns

  • Working with lists

  • List operations and slicin

  • Course Introduction and Overview
  • Data Collection and Cleaning
  • Handling Missing Data
  • Data Transformation and Scaling
  • Practical Examples and Exercises
  • Introduction and Purpose
  • Mathematical Foundation
  • Practical Implementation
  • Introduction and Purpose
  • Mathematical Foundation
  • Practical Implementation
  • Introduction and Purpose
  • Mathematical Foundation
  • Practical Implementation
  • Introduction to Decision Tree Regression
  • Implementing Decision Tree Regression
  • Introduction to Random Forest Regression
  • Implementing Random Forest Regression
  • Practical Examples and Exercises
  • Model Evaluation Techniques
  • Model Selection Criteria
  • Recap of Regression Models
  • Practical Examples and Exercises
  • Q&A and Discussion
  • Definition and Purpose
  • Mathematical Foundation
  • Real-world Applications
  • Algorithm Explanation
  • Distance Metrics
  • Practical Implementation
  • Algorithm Explanation
  • Distance Metrics
  • Practical Implementation
  • Introduction to Clustering
  • Implementing K-Means Clustering
  • Introduction to Hierarchical Clustering
  • Implementing Hierarchical Clustering
  • Practical Examples and Exercises
  • Algorithm Steps
  • Choosing the Number of Clusters
  • Real-world Applications

  • Introduction to n8n

  • Building AI-powered workflows

  • Connecting APIs

  • Automating intelligent tasks

  • Automated email workflows

  • Trigger-based messaging

  • Personalization logic

  • CRM-style automation

  • Social media automation

  • Scheduled posting

  • AI content workflows

  • Performance tracking

  • What is Generative AI

  • Use cases in industry

  • LLM fundamentals

  • AI ecosystem overview

  • Prompt engineering

  • Structured outputs

  • API integrations

  • Practical AI applications

  • Retrieval-Augmented Generation

  • Vector databases basics

  • Embeddings concept

  • Knowledge-grounded responses

  • Building RAG pipelines

  • Document ingestion

  • Query optimization

  • Production deployment basics

  • Speech-to-text systems

  • Text-to-speech systems

  • Conversational flow design

  • Real-time AI agents

  • Neural network fundamentals

  • Layers and architecture

  • Forward and backward propagation

  • Real-world applications

  • ANN structure

  • Training process

  • Loss functions

  • Model tuning basics

  • ReLU, Sigmoid, Tanh

  • Why activation functions matter

  • Vanishing gradient issue

  • Choosing the right function

  • Image data fundamentals

  • Convolution operation

  • Feature maps

  • Pooling layers

  • Dataset preparation

  • Model compilation

  • Epochs and batch size

  • Performance monitoring

  • Gradient descent variants

  • Adam optimizer

  • Dropout technique

  • Preventing overfitting

  • Introduction to SQL
  • Basic SQL Syntax
  • Writing Simple Queries
  • Practical Examples and Exercises
  • Understanding Databases
  • Advanced SQL Queries
  • Using Aggregate Functions
  • Grouping and Sorting Data
  • Practical Examples and Exercises
  • Working with Multiple Tables
  • Introduction to Joins
  • Implementing Inner Joins
  • Implementing Outer Joins
  • Practical Examples and Exercises
  • Understanding Join Performance
  • Subqueries and Nested Queries
  • Using Subqueries in SELECT Statements
  • Using Subqueries in WHERE Clauses
  • Practical Examples and Exercises
  • Optimizing Subqueries
  • Introduction to PowerBI
  • Data Import and Transformation
  • Building Visualizations and Reports
  • Practical Examples and Exercises
  • Sharing and Publishing Reports

Master These Tools for a Competitive Edge

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Affordable Tech Programs
Affordable Tech Programs
Affordable Tech Programs
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Explore Our Ecosystem

A one-stop destination for all your learning to placement needs

Creating interactive dashboards with Power BI

Tech Blog

Explore our tech blog for in-depth guides on a wide range of programming topics. From beginners to experts, find the knowledge you need to enhance your coding skills!

Real-time data visualization with Tableau
Python code example for data analysis

Internship portal

Experience the real world with our project-based internships, designed to equip you with essential skills. Transform your potential into professional excellence.

Free datasets for practicing data science
Python for data science beginners tutorial

Job Portal

New-age jobs need new-age technology, revamp your CVs to increase your chances of getting hire and apply for exclusive jobs.

Best online courses to learn data science
Decision tree visualization in scikit-learn

Hall of Fame

View our alumni who have excelled & transformed their careers through us.

What is data science and how does it work
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Our alumni work at reputed technology companies and promising startup

Join the ranks of our successful graduates working at top-tier tech companies and startups around the world

Machine learning model architecture diagram

Army will make you confident about your fundamentals

Gain unmatched clarity and mastery in foundational principles to excel in any challenge.

Interactive Python dashboard for data analysis

Syed Abis

Data Scientist

Data science tools for students and beginners
Histogram plot created with Seaborn in Python

Hasnian Ali

Data Scientist

Deep learning vs machine learning in data science
Jupyter Notebook screenshot for Python tutorial

Sara Arshad

Software Engineer

Data science project example using real datasets
Data preprocessing using pandas and NumPy

Sara Arshad

Software Engineer

Python for data science beginners tutorial

Syed Abis

Data Scientist

Python script for machine learning classification

Zainab Arif

Data Scientist

Beginner-friendly Python code snippet
Histogram plot created with Seaborn in Python

Hasnian Ali

Data Scientist

Step-by-step Python data science pipeline

Sara Arshad

Data Scientist

AI workflow using Python libraries

Muhammad Umair

Senior UI/UX Designer

Mishkaat Lodhi

HR Manager

Hamza Abbas

HR Recruiter

Adeel Ejaz

Fahama Ahmed

HR Manager

Usman Khalid

Machine Learning Engineer

Muhammad Owais

AI Lead

Mahnoor Khaliq

Web Developer

Muhammad Mudassir

Data Engineer

Bilal Saeed

Manager Data Analytics

Kashif Raza

Data Analyst

Sharukh Mirza

Data Engineer

Syed Abis

Data Scientist

Python script for machine learning classification

Zainab Arif

Data Scientist

Beginner-friendly Python code snippet
Histogram plot created with Seaborn in Python

Hasnian Ali

Data Scientist

Step-by-step Python data science pipeline

Sara Arshad

Data Scientist

AI workflow using Python libraries

Carefully Curated Curriculum

Everything you need to know about the product and billing.

Most of our courses are designed for beginners, so no prior experience is required. However, some advanced courses may have specific prerequisites, which are listed on the course page.

Course durations vary, but most of our programs range from 4 weeks to 6 months. Check the course details for the exact duration.

Yes, we offer a refund policy if you decide to cancel within the first 7 days of the course start date. Please review our refund policy for more information.

Yes, all our courses come with a certificate of completion, which you can add to your resume or LinkedIn profile.

Absolutely! You will have lifetime access to all course materials, so you can revisit and review them anytime.

We offer both self-paced and live courses to accommodate different learning preferences. Please check the course details to see the format offered.

You’ll have access to a dedicated support team, as well as mentors and peer forums where you can ask questions and share insights.

Yes, we periodically offer discounts, and we have scholarship opportunities available for eligible students. Keep an eye on our promotions page or contact support for more details