Data Science Masters Bootcamp

Dive deep into the world of data science with our comprehensive course. Learn advanced techniques, tools, and algorithms to analyze data, gain insights, and make informed decisions. Elevate your skills and embark on a rewarding career in data science.

Rs. 5,999/-

Monthly Rs. 12,000

50% Discount

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start coding with confidence!

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

19th Oct 24

Start Date

Tues/Thurs/Fri

Class Days

2 Months

Duration

8:30-10:30 PM

Class Timing

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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
  • Introduction to While Loops
  • Loop Control Statements (break, continue, pass)
  • Practical Examples and Exercises
  • Nested Loops
  • Defining and Calling Functions
  • Parameters and Arguments
  • Introduction to Karel the Robot
  • Practical Examples and Exercises
  • Using Functions with Karel
  • 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 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
  • Definition and Purpose
  • Mathematical Foundation
  • Real-world Applications
  • 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
  • Agglomerative vs. Divisive
  • Dendrograms
  • Practical Implementation
  •  
  • Introduction to Artificial Neural Networks (ANN)
  • Building ANN Models
  • Training and Evaluating ANN Models
  • Practical Examples and Exercises
  • Advanced Topics in ANN
  • Introduction to Convolutional Neural Networks (CNN)
  • Building CNN Models
  • Training and Evaluating CNN Models
  • Practical Examples and Exercises
  • Advanced Topics in CNN
  • Introduction to Recurrent Neural Networks (RNNs)
  • Training RNNs
  • Implementing RNNs

  • Introduction to Transformer Architecture

  • Applications of Transformers:

  • Implementing Transformers:

  • Basics of NLP:

  • Advanced NLP Techniques:

  • NLP Applications:

  • Introduction to LangChain:

  • Building with LangChain:

  • Advanced LangChain Applications:

  • Introduction to Dimensionality Reduction
  • Implementing Principal Component Analysis (PCA)
  • Implementing Linear Discriminant Analysis (LDA)
  • Practical Examples and Exercises
  • Comparing PCA and LDA
  • Introduction to Model Selection Techniques
  • Implementing Boosting Algorithms (AdaBoost, Gradient Boosting)
  • Practical Examples and Exercises
  • Model Tuning and Optimization
  • Comparing Different Boosting Methods
  • 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

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Internship portal

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

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

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

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

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Syed Abis

Data Scientist

Hasnian Ali

Data Scientist

Sara Arshad

Software Engineer

Sara Arshad

Software Engineer

Syed Abis

Data Scientist

Zainab Arif

Data Scientist

Hasnian Ali

Data Scientist

Sara Arshad

Data Scientist

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