The aims to equip students with the knowledge and skills needed to succeed in an increasingly datadriven world.
The department focuses on the development of intelligent systems and data-centric technologies through a curriculum that combines the principles of computer science, artificial intelligence, statistics, and big data analytics.
The program is designed to enable students to understand and apply AI and data science tools in solving real-world problems across a variety of domains such as healthcare, finance, education, retail, agriculture, and cybersecurity. With the rapid growth of data across industries, professionals in this field are in high demand globally.
VISION
To be a center of excellence in Artificial Intelligence and Data Science, fostering innovation, ethical practices, and societal impact.
MISSION
- M1: To promote innovation, critical thinking, and problem- solving using cutting-edge AI technologies.
- M2: To nurture ethically responsible and socially aware professionals capable of addressing real-world challenges through intelligent solutions.
- M3: To collaborate with industry and academia to bridge the gap between theoretical knowledge and practical applications.
Program Educational Objectives (PEOs)
- Apply fundamental knowledge of artificial intelligence, machine learning, mathematics, and computing to develop intelligent systems and solve real-world problems.
- Pursue successful careers in industry, research, by continuously upgrading their technical skills and adapting to emerging technologies.
- Exhibit professionalism, ethical behavior, teamwork, and leadership while addressing societal needs through responsible AI practices
Program Specific Outcomes (PSOs)
- Design, develop, and deploy intelligent systems using core concepts of artificial intelligence, machine learning, deep learning, and data analytics to solve complex real-world problems.
- Demonstrate proficiency in modern programming languages, AI/ML frameworks, and cloud platforms for building scalable and efficient intelligent applications.
Data Science Skills
Math & Stats : Probability, linear algebra, and hypothesis testing.
Data Wrangling: Cleaning messy data with Pandas and NumPy.
Database Management: Querying structural systems with SQL.
Visualization: Presenting discoveries via PowerBI or Matplotlib.
Artificial Intelligence Skills
Deep Learning : Building multi-layered neural networks.
Natural Language Processing (NLP) : Teaching systems to read and write text.
Computer Vision : Enabling machines to process visual data.
MLOps : Deploying and monitoring active AI models in production.
BASIC ELIGIBILITY
10, +2 Pass with minimum 50-60% aggregate.
INDUSTRIES HIRING FOR BOTH FIELDS:
- Healthcare (AI for diagnosis, DS for patient data)
- FinTech (AI for fraud detection, DS for credit scoring)
- Retail & eCommerce (AI for recommendation, DS for behavior analysis)
- Cybersecurity, Logistics, Energy, Gaming, EdTech
MAJOR SUBJECTS IN AI AND DATA SCIENCE
- Foundation Programming: Python for Data Science, C/C++
- BasicsMaths & Stats: Linear Algebra, Calculus, Probability, Statistics-I
- Core CS: Data Structures, Database Management Systems (DBMS)
- AI Basics: Introduction to AI, Principles of AI
- Statistics: Statistical Inference, Statistics-II, Regression Analysis
- Machine Learning: ML Algorithms, Supervised & Unsupervised Learning
- Data Handling: Data Mining, Data Warehousing, R Programming
- Core CS: Design & Analysis of Algorithms, Operating Systems
- NoSQL Databases NLP: Natural Language Processing
LAB KNOWLEDGE:
Python lab, ML lab, SQL lab, Deep Learning lab, Project labKey, Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Power BI, Tableau, Git, AWS/Azure basics.
JOBS
1. ENTRY LEVEL
Job Role | What You Do | Avg Salary Fresher |
Data Analyst | Clean data, make dashboards, Excel/SQL reports | 3.5 - 6 LPA |
Business Intelligence Analyst | Power BI/Tableau dashboards for business teams | 4 - 7 LPA |
ML Associate / Junior ML Engineer | Basic ML models, data labeling, model testing | 5 - 8 LPA |
Data Engineer Trainee | Trainee Build data pipelines, manage databases | 4.5 - 8 LPA |
AI/Python Developer | Code chatbots, automation scripts using Python | 4 - 7 LPA |
2. ONCE EXPERIENCED
Job Role | What You Do | Avg Salary Fresher |
Data Scientist | Build prediction models, stats, A/B testing | 8 - 18 LPA |
MachineLearning Engineer | Deploy ML models to production, MLOps | 10 - 22 LPA |
AI Engineer | Work on NLP, Computer Vision, LLMs, GenAI | 12 - 25 LPA |
Big Data Engineer | Handle Hadoop/Spark, large-scale data systems | 10 - 20 LPA |
Data Analytics | Consultant Solve business problems using data for clients | 9 - 16 LPA |