Become a Future-Ready

Full Stack Data Scientist

in 5 Months!

Master Data Science, Generative AI, and Agentic AI – with placement support.


Why This Course is Built for the Future of Tech

  • Learn from Scratch

    Master Python, Machine Learning, Deep Learning, and Generative AI from the basics.

  • Real-World Projects

    Work on hands-on projects using real industry datasets to build practical skills.

  • Career Readiness

    Get help with resume building, mock interviews, and career mentorship to land your dream job.

Comprehensive Curriculum That Covers Everything

  • Introduction to Data Science
  • Python Basics
  • Python – Data Types & Utilities
  • Set
  • Tuple
  • Dictionary and Dictionary comprehension
  • Functions
  • Packages
  • Map Reduce
  • OOPs
  • Class & Object
  • Methods
  • Python DECORATOR
  • Polymorphism
  • Python – Production Level
  • Pickling & Unpickling
  • Pandas
  • Numpy
  • Matplotlib
  • Seaborn
  • Scipy
  • Statsmodels
  • Set Theory
  • Combinatorics
  • Probability
  • Distributions
  • Linear Algebra
  • Euclidean Distance & Manhattan Distance
  • Calculus
  • Indices & Logarithms
  • Introduction
  • Types of Data
  • Measures of Central Tendency
  • Descriptive statistic Measures of symmetry
  • Measurement of Spread
  • Measures of variability
  • Levels of Data Measurement
  • Variable
  • Frequency Distribution Table
  • Types of Variables
  • Frequency Distribution Table
  • Correlation, Regression & Collinearity
  • Others
  • Bias and Variance in ML
  • Entropy in ML
  • Information Gain
  • Surprise in ML
  • Loss Function & Cost Function
  • Inferential Statistics
  • Introduction
  • Keys
  • Constraints
  • CRUD Operations
  • SQL Languages
  • SQL Commands
  • SQL Clause
  • Operators
  • Wild Cards
  • Aggregate Functions
  • SQL Joins
  • EDA
  • Data Visualisation
  • ML Introduction
  • Important Element of Machine Learning
  • Multiclass Classification
  • Data Processing
  • Regression
  • Evaluation Metrics for Regression
  • Classification
  • Clustering
  • Introduction
  • K-Means Clustering
  • Hierarchical Clustering
  • Agglomerative clustering
  • DBSCAN Clustering
  • Association Rules
  • Recommendation Engines
  • Time Series & Forecasting
  • Model Selection & Evaluation
  • Over Fitting & Under Fitting
  • Others
  • ML Pipeline
  • ML Model Deployment in Flask
  • Introduction
  • Basic Report Design
  • Visual Sync, Grouping
  • Hierarchies, Filters
  • Power Query
  • DAX Functions
  • Functional English
    • Grammar: Tenses, Articles, Voice, Prepositions
    • Sentence Construction
  • Soft Skills
    • JAM (Just a Minute), GD (Group Discussion)
    • Resume Writing, Email Etiquette
    • HR Interview Preparation (Mock Interviews)
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Why Naresh IT?

Comprehensive Curriculum

Master web development with a full-stack curriculum covering front-end, back-end, databases, and more.

Hands-On Projects

Apply skills to real-world projects for practical experience and enhanced learning.

Expert Instructors

Learn from industry experts for insights and guidance in full-stack development.

Certification upon Completion

Receive a recognized certification validating your full-stack development skills.

Job Placement Assistance

Access job placement assistance for career support and employer connections.

24/7 Support

Access round-the-clock support for immediate assistance, ensuring a seamless learning journey.

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Frequently Asked Questions

Yes. This course is beginner-friendly and covers basics before diving into advanced topics.

Yes. You'll receive a verifiable course completion certificate + Gen AI specialization badge.

You’ll get resume help, mock interviews, job alerts, and referral-based opportunities through our partner network.

Yes. You’ll build projects similar to what top AI startups and MNCs are working on right now.

Request Call Back

Have further queries? Contact us!

Request a Callback. An expert from the admissions office will call you in the next 24 working hours. You can also reach out to us at [email protected] or +91-8179191999

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