Applied Artificial Intelligence & Data Science
Program Structure
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Semester 3 – Core Programming and Data Management
- Relational Databases (RDBMS) using MySQL
- Python Programming & Advanced Python
- Problem Solving & Data Structures using Python
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Semester 4 – Data Analysis
- Exploratory Data Analysis with Pandas
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Semester 5 – Machine Learning
- Machine Learning Fundamentals & Advanced ML
- ML System Design & Deployment (MLOps)
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Semester 6 – Advanced AI
- Deep Learning using TensorFlow
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Semester 7 – NLP and Generative AI
- Natural Language Processing
- Generative AI & Agentic AI
- Experiential Project-Based Learning
Pre-requisites
- Eligibility: 3rd, 4th, 5th, 6th, 7th Semester B. E / B.Tech students
- Basic computer and operating system knowledge
- Logical thinking and problem-solving skills
- No prior programming or AI experience required
Program Outcomes
- Demonstrate proficiency in Python programming, data handling, and database management
- Analyze and visualize complex datasets using Excel and Python-based tools
- Apply supervised and unsupervised machine learning techniques to solve real-world problems
- Design, train, and deploy deep learning models for image, text, and sequence data
- Develop natural language processing and generative AI applications using modern AI frameworks
Project Streams
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Core Programming and Data Visualization
- Student Grading System using Python functions
- Automated Sales Performance Dashboard in Excel
- Customer Segmentation with Grouped Insights
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Machine Learning and Deep Learning
- Credit Risk Analysis using Ensemble
- Multi-Class Image Classification with CNN
- License Plate Detection with OpenCV
Software & Frameworks
- Python, Jupyter Notebook, Anaconda, VS Code
- MySQL · MS Excel
- TensorFlow, Keras, PyTorch, OpenCV
- Streamlit, Gradio, HuggingFace
