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Master AI & Data Science With Industry Experts

Gain practical skills in machine learning, data analysis, and AI technologies through VTU-registered internships. Learn from industry leaders and prepare for high-demand tech roles.

VTU-Recognized Certification
Industry Expert Mentors
Hands-on Projects
Flexible Learning Schedule
Machine Learning
Data Analysis
AI Models
Big Data
AI & Data Science Internship – Curriculum
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AI & Data Science Internship

Master machine learning, deep learning, and data analysis techniques to become a skilled AI professional

15+ Projects
100% Hands-on
VTU Certified

Program Overview

This comprehensive AI & Data Science internship is designed to transform you into a skilled data professional. You’ll gain hands-on experience with machine learning algorithms, deep learning frameworks, statistical analysis, and real-world data projects. The program covers everything from foundational Python programming to advanced neural networks and model deployment.

Industry-Ready Skills

Learn tools and techniques used by data scientists at top companies

Real-World Projects

Build 15+ portfolio projects using actual industry datasets

Expert Mentorship

Get personalized guidance from experienced AI professionals

VTU Certified

Receive certification recognized by VTU and industry partners

Detailed Curriculum

01

Python for Data Science

  • Python fundamentals and advanced concepts
  • NumPy for numerical computing
  • Pandas for data manipulation and analysis
  • Data cleaning and preprocessing techniques
  • Working with different data formats (CSV, JSON, Excel)
  • File handling and database connections
02

Data Visualization & EDA

  • Matplotlib for data visualization
  • Seaborn for statistical graphics
  • Plotly for interactive visualizations
  • Exploratory Data Analysis (EDA) techniques
  • Statistical analysis and hypothesis testing
  • Creating dashboards and reports
03

Machine Learning for Datascience

  • Foundations of Machine Learning for AI
  • Supervised Learning: Regression & Classification
  • Unsupervised Learning: Clustering & Dimensionality Reduction
  • Feature Engineering & Data Preprocessing
  • Model Evaluation Metrics & Validation
  • Cross-validation & Hyperparameter Tuning
  • Handling Imbalanced & Noisy Data
  • Building ML Models using Scikit-learn
04

Deep Learning for AI

  • Neural networks fundamentals and architecture
  • TensorFlow and Keras frameworks
  • Convolutional Neural Networks (CNN) for image processing
  • Recurrent Neural Networks (RNN) and LSTM
  • Transfer learning and pre-trained models
  • Image classification and object detection
  • Natural Language Processing basics
  • PyTorch fundamentals
05

Generative AI and LLMs

  • Introduction to Generative AI and LLM concepts
  • Transformer architecture and self-attention
  • Prompt engineering and optimization
  • Fine-tuning and customizing LLMs
  • Generative models: GPT, Diffusion, GANs & VAEs
  • RAG (Retrieval-Augmented Generation) systems
  • Embeddings, vector databases & AI agents
  • Ethics, safety, hallucination control in LLMs
06

Capstone Project

  • End-to-end project development
  • Problem definition and data collection
  • Model development and optimization
  • Deployment and documentation
  • Presentation and defense
  • VTU format report submission

Tools & Technologies You’ll Master

Python
TensorFlow
PyTorch
Scikit-learn
Pandas
NumPy
Matplotlib
Seaborn
AWS
Git/GitHub
Jupyter
SQL

Industry Projects You’ll Build

Customer Churn Prediction

Build a machine learning model to predict customer churn for a telecom company using classification algorithms and feature engineering.

Python Scikit-learn Pandas

Image Classification System

Develop a deep learning model using CNN to classify images into multiple categories with high accuracy using transfer learning.

TensorFlow Keras CNN

Sentiment Analysis Tool

Create an NLP-based sentiment analysis system to analyze customer reviews and social media posts using RNN and LSTM.

NLP LSTM PyTorch

Sales Forecasting Dashboard

Build a time series forecasting model to predict future sales trends with interactive visualizations and insights.

Time Series Plotly ARIMA

Recommendation Engine

Develop a recommendation system using collaborative filtering to suggest products or content to users based on behavior patterns.

ML Matrix Factorization Python

Healthcare Diagnosis System

Create a medical diagnosis assistant using machine learning to predict diseases based on patient symptoms and medical history.

Deep Learning Classification Healthcare

Ready to Start Your AI Journey?

Join hundreds of students who have transformed their careers with our AI & Data Science internship program

Contact Us: intern@krugna.com | +91 89700 02233

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