PO1: Graduates will possess a comprehensive skill set in data analysis, including the ability to collect, clean, and analyze data using statistical methods and programming languages.
PO2: Graduates will demonstrate expertise in machine learning techniques, enabling them to develop and deploy predictive models for various applications.
PO3: Graduates will be proficient in utilizing big data technologies, such as Hadoop and Spark, for processing and analyzing large datasets efficiently.
PO4: The program will prepare students to apply data science techniques effectively in diverse domains, addressing industry-specific challenges.
PO5: Graduates will exhibit ethical awareness and responsible practices in data science, considering privacy concerns and societal implications in their work.
PO6: Graduates will develop strong communication skills, both written and oral, and the ability to visually communicate complex data-driven insights through effective data visualization techniques.
PO7: The program will foster critical thinking skills, empowering graduates to approach complex problems systematically and devise innovative solutions using data driven methodologies.
PO8: Graduates will embrace a culture of continuous learning, staying informed about emerging technologies and methodologies in data science, and adapting to industry advancements.
PO9: Graduates will have engaged in hands-on, real-world projects, demonstrating their ability to apply theoretical knowledge to practical scenarios and solving authentic data science problems.
PO10: Graduates will possess skills in designing and conducting both quantitative and qualitative research, contributing to the advancement of knowledge in the field. PSO 12. The program will nurture leadership skills, enabling graduates to make informed, data-driven decisions and contribute to strategic planning within organizations.
| Particular | Course |
|---|---|
| Core Courses | Computer Fundamentals & Python Programming |
| Introduction to Data Science | |
| Data structures using Python | |
| Descriptive Statistics | |
| Exploratory Data Analysis | |
| Statistical Methods for Data Science | |
| Introduction to Machine Learning using Scikit-learn | |
| Data Mining & Warehousing | |
| Generative AI | |
| Time Series and Forecasting | |
| Indian Knowledge System in Data Science | |
| Big Data Analysis | |
| Data Engineering | |
| Computer Vision |
| Particular | Course |
|---|---|
| Vocational Skill Courses | Office Tools |
| Introduction to Web Technologies | |
| Introduction to Research Methodology | |
| Business Analytics using Power BI |
| Particular | Course |
|---|---|
| Skill Enhancement Courses | Data Handling using Microsoft Excel |
| Data Visualization using Tableau | |
| SQL for Data Analysis |
| Particular | Course |
|---|---|
| Minor: Mathematics | Linear Algebra |
| Probability Theory | |
| Numerical Methods | |
| Optimization Techniques | |
| Mathematical Modelling and Simulation |
| Particular | Course |
|---|---|
| Discipline Specific Electives | Domain Specific Analytics (Finance / Healthcare / Marketing) |
| Cloud Computing and Analytics |
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But I must explain to you how all this mistaken idea of denouncing pleasure and praising pain was born and I will give you a complete account of the system, and expound the actual teachings of the great explorer of the truth, the master-builder of human happiness. No one rejects, dislikes, or avoids pleasure itself, because it is pleasure, but because those who do not know how to pursue pleasure rationally encounter consequences that are extremely painful. Nor again is there anyone who loves or pursues or desires to obtain pain of itself, because it is pain, but because occasionally circumstances occur in which toil and pain can procure him some great pleasure. To take a trivial example, which of us ever undertakes laborious physical exercise, except to obtain some advantage from it? But who has any right to find fault with a man who chooses to enjoy a pleasure that has no annoying consequences
