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  • (+91) 8094336633, (+91) 9057015701
  • careers@zeetronnetworks.com
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Data Science with GenAI Training in Jaipur

  • Data Science with Gen AI Training in Jaipur 2026

    Zeetron Network is one of the best Data Science with Gen AI training companies in Jaipur with experienced professionals and a dedicated team. Our Data Science with Gen AI training in Jaipur covers the complete standard module of Data Science and advanced Generative AI topics that are essential for students and professionals to become skilled data scientists, AI specialists, or data analysts for leading companies. Zeetron Networks’ online and offline Data Science with Gen AI training in Jaipur includes Python, basics of R, Statistics, Internal Statistics, Regression, ANOVA, Generative AI, Large Language Models (LLMs), AI-driven analytics, and AI-based predictive modeling. We focus on teaching Python in a way that ensures you gain expert-level skills in Python and Gen AI to be recognized as a professional in the IT sector.

    Zeetron Network is the ideal place for Data Science with Gen AI certification training because we provide Real-Time Expert Trainers, Project-Based Internship, industry-relevant training, an affordable fee structure, flexible learning options, and complete placement assistance for students. We are the only data science internship company in Jaipur that emphasizes industrial learning, Generative AI integration, and quality teaching.

    Learning Data Science with Gen AI will empower you to grow your professional career into multiple related technologies like Machine Learning, Artificial Intelligence, Big Data Hadoop, and Generative AI, enabling you to excel as a data scientist, AI analyst, or AI specialist in Jaipur.

  • Data Science with Gen AI 2026 Learning Outcomes

    • Develop hard skills in Data Science like Python, R Programming, Statistics, Machine Learning, Artificial Intelligence, Tableau, Deep Learning, Neural Networks, TensorFlow, Unix, Git, SQL along with Generative AI, Large Language Models (LLMs), Prompt Engineering, AI Automation, Vector Databases, and Gen AI-based Model Fine-Tuning. Our courses integrate real-world hands-on training with case studies & projects using datasets from companies like Amazon, Facebook, Adobe, Walmart, etc.
    • Work on Real Projects, Build a Portfolio, Attend Interviews and Get Hired. Learn to create AI-driven applications, Gen AI chatbots, AI-powered dashboards, and real-time predictive models using LLMs and Gen AI tools widely used in 2026.
    • Certified Data Science Trainer with years of real-time industry experience. Best faculty with excellent lab infrastructure along with detailed course material. Prepare your CV/Resume to attend interviews and secure a job.
    • We share common interview FAQs, Interview Handling Skills & Real-Time Case Studies including Gen AI interview questions, LLM implementation challenges, and AI product case studies. One-to-one attention by instructors.
    • Start learning Data Science through the promising Julia language and become an efficient data scientist with strong Generative AI expertise for 2026 industry requirements.

Statistics

  • Introduction to Data Science
  • The need for Data Science
  • BigData and Data Science
  • Data Science and machine learning
  • Data Science Life Cycle
  • Data Science Platform
  • Data Science Use Cases
  • Skill Required for Data Science
  • Linear Algebra
  • Vectors
  • Matrices
  • Optimization
  • Theory Of optimization
  • Gradients Descent
  • Descriptive vs. Inferential Statistics
  • Types of data
  • Measures of central tendency and dispersion
  • Hypothesis & inferences
  • Hypothesis Testing
  • Confidence Interval
  • Central Limit Theorem
  • Probability Theory
  • Conditional Probability
  • Data Distribution
  • Binomial Distribution
  • Normal Distribution

 

Python for Data Science

  • Why Python, its Unique Feature and where to use it?
  • Python Environment Setup/shell
  • Installing Anaconda
  • Understanding the Jupyter notebook
  • Python Identifiers, Keywords
  • Discussion about installed modules and packages
  • Python Data Types and Variable
  • Condition and Loops in Python
  • Decorators
  • Python Modules & Packages
  • Python Files and Directories manipulations
  • Use various files and directory functions for OS operations
  • Built-in modules (Library Functions)
  • Numeric and Math’s Module
  • String/List/Dictionaries/Tuple
  • Complex Data structures in Python
  • Python built-in function
  • Python user-defined functions
  • Array Operations
  • Arrays Functions
  • Array Mathematics
  • Array Manipulation
  • Array I/O
  • Importing Files with Numpy
  • Data Frames
  • I/O
  • Selection in DFs
  • Retrieving in DFs
  • Applying Functions
  • Reshaping the DFs - Pivot
  • Combining DFs
  • Merge
  • Join
  • Data Alignment
  • Matrices Operations
  • Create matrices
  • Inverse, Transpose, Trace, Norms, Rank etc
  • Matrices Decomposition
  • Eigenvalues & vectors
  • Basics of Plotting
  • Plots Generation
  • Customization
  • Store Plots

 

Machine Learning

  • Data Exploration
  • Missing Value handling
  • Outliers Handling
  • Feature Engineering
  • Importance of Feature Selection in Machine Learning
  • Filter Methods
  • Wrapper Methods
  • Embedded Methods
  • Introduction to Machine Learning
  • Logistic Regression
  • Naïve Bays Algorithm
  • K-Nearest Neighbor Algorithm
  • Decision Trees (SingleTree)
  • Support Vector Machines
  • Model Ensemble
    • - Bagging
    • - Random Forest
    • - Boosting
    • -Gradient Boosted Trees
  • Model Evaluation and performance
    • - K-Fold Cross-Validation
    • - ROC, AUC, etc...
  • Simple Linear Regression
  • Multiple Linear Regression
  • Decision Tree and Random Forest Regression
  • Similarity Measures
  • Cluster Analysis and Similarity Measures
  • Principal means Clustering
  • HierarComponents Analysis
  • Association Rules Mining & Market Basket Analysis
  • Basics
  • Term Document Matrix
  • TF-IDF
  • Twitter Sentiment Analysis

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