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AI & Data
Science

From data wrangling to deep learning — build real-world AI models using cutting edge frameworks and OpenAI APIs.

16 weeksIntermediateLive Projects
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Program HighlightsWhat You'll Experience
Live instructor-led sessions
1-on-1 mentorship
Real-world projects
Career guidance

Key Responsibilities

Clean, normalize, and pre-process massive datasets for model training
Optimize existing algorithms to improve predictive accuracy and speed
Develop REST endpoints to securely serve machine learning models
Design dashboards to visualize training metrics and data drift

Technologies You'll Master

Python
Python
NumPy
NumPy
Pandas
Pandas
Scikit-learn
Scikit-learn
TensorFlow
TensorFlow
PyTorch
PyTorch
Jupyter Notebook
Jupyter Notebook
OpenAI APIs
OpenAI APIs

Learning Outcomes

Demonstrate practical implementation of AI and Data Science concepts
Develop end-to-end solutions using structured workflows
Gain experience in real-world datasets and problem-solving
Build professional portfolios aligned with industry expectations
Acquire exposure to deployment and cloud-based environments
Project Allocation Framework

Real-World Project Execution

As part of the AI & Data Science Internship Program, project-based learning serves as a critical component in enabling students to translate theoretical knowledge into practical application. The following project allocation framework has been designed to provide structured exposure across varying complexity levels, ensuring progressive skill development.

Learning Stages

  • Set 1 & Set 2: Foundational (Basic Level)
  • Set 3 & Set 4: Intermediate (Medium Level)
  • Set 5: Advanced (Industry-Level Capstone)

Implementation Guidelines

  • Problem Definition and Requirement Analysis
  • Data Collection and Preprocessing
  • Exploratory Data Analysis and Feature Engineering
  • Model Development and Evaluation
  • Optimization and Validation
  • Deployment (where applicable)
  • Documentation and Presentation
  • Projects in advanced stages must include cloud deployment using AWS or Microsoft Azure, ensuring real-world exposure.

Expected Outcomes

  • Demonstrate practical implementation of AI and Data Science concepts
  • Develop end-to-end solutions using structured workflows
  • Gain experience in real-world datasets and problem-solving
  • Build professional portfolios aligned with industry expectations
  • Acquire exposure to deployment and cloud-based environments
Project Catalogue
Foundational Level (Basic – Level 1)

Project Set 1

This set focuses on fundamental data handling, visualization, and introductory analysis.

1
Student Performance Analysis System
2
Sales Data Visualization Dashboard
3
Weather Data Analysis and Trend Identification
4
Basic Movie Recommendation System (Popularity-Based)
5
COVID-19 Data Analysis and Visualization
6
E-Commerce Product Analysis Dashboard
7
IPL Dataset Exploratory Data Analysis
8
Simple Loan Data Analysis System
9
Customer Demographics Analysis Tool
10
Food Delivery Data Insights System
11
Traffic Data Analysis and Visualization
12
Basic Stock Market Trend Visualization Tool

1-on-1 Mentorship

Get personalized guidance from industry experts. Regular code reviews, career advice, and technical support throughout your internship.

Certificate

Earn an industry-recognized certificate upon successful completion. Boost your resume and stand out to potential employers.

Outcomes That Matter

Real Results for
Real Students
Real Results for
Real Students
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