PROGRAM OUTCOME (PO)
PO1: Apply the data science principles, tools and techniques to model and analyze various real world business problems, and suggest a suitable solution by communicating relevant findings and effectively presenting results using appropriate data visualization techniques.
PO2: Identify, formulate, research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
PO3: Understand the recent developments and applications of big data analytics in social and web media firms for prediction and recommendation.
PO4: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
PO5: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
PO6: Recognize various issues in everyday business; apply data science to understand and make well-reasoned, data-driven management decisions.
PO7: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
Curriculum & Syllabus
CURRICULUM & SYLLABUS
MINIMUM CREDITS TO BE EARNED: 140
|Code No.||Course||Hours/Week||Maximum Marks|
|LANG||Tamil I/ Hindi / French||5||0||0||5||40||60||100|
|CORE||Programming in C||4||1||0||5||40||60||100|
|CORE||Mathematics - I||4||0||0||4||40||60||100|
|CORE||Programming in C Lab||0||0||4||2||40||60||100|
|CORE||MS Office Lab||0||0||4||2||40||60||100|
|Program||Eligibility||Criteria for Merit|
|B.C.A Data Science - II Shift||Pass in (10+2) or equivalent with Maths / Computer Science / Business Maths / Statistics / Computer Applications / Information Practice|
Lateral Entry: Pass in Diploma in Computer Science / ECE / Information Technology / Computer Technology
|Merit - based on percentage of marks secured in the qualifying examination.|
- Applications Architect
- Business Intelligence Developer
- Data Architect
- Data Analyst
- Data Scientist
- Data Engineer
- Enterprise Architect
- Infrastructure Architect
- Machine Learning Scientist
- Maching Learning Engineer
| Tuition Fee 2023 - 2024 (Per Sem) ||Other Fee (Per Sem)||Total Fee (Per Sem)
| 55,000 || 6,500 || 61,500