Combining computer science concepts with data analysis methods is the main goal of Computer Science integrated Data Science. Core disciplines covered in the curriculum include big data technology, machine learning, databases, algorithms, and programming. To handle challenging challenges, students gain the ability to organize, evaluate, and comprehend huge datasets. The program places a strong emphasis on practical skills through data science application projects and internships. Graduates can work in a variety of businesses as machine learning engineers, data scientists, data analysts, and in related areas.
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| Sl. No. | Professional Opportunity | Description |
|---|---|---|
| 1 | Data Scientist | Explore big data sets to find patterns and insights that help make smarter decisions. |
| 2 | Data Analyst | Analyze data and create easy-to-understand reports that show trends and business performance. |
| 3 | Machine Learning Engineer | Build models that can predict outcomes and make systems smarter and more efficient. |
| 4 | Business Intelligence (BI) Developer | Create tools and dashboards that help businesses make informed decisions based on data. |
| 5 | Data Engineer | Set up and maintain data pipelines to keep data organized and ready for analysis. |
| 6 | Quantitative Analyst | Use math and stats to analyze financial data and help make investment decisions. |
| 7 | Data Science Consultant | Offer expert advice on using data to help businesses make better decisions. |
| 8 | Artificial Intelligence (AI) Specialist | Develop AI solutions that make systems more efficient and add new capabilities. |
| 9 | Big Data Engineer | Manage large-scale data systems to ensure data is accurate and scalable. |
| 10 | Data Visualization Specialist | Design visuals that make complex data easy to understand at a glance. |
| Educational Level | Eligibility Criteria |
Preferred Stream | Minimum Marks |
|---|---|---|---|
| Diploma | Passed 10 or equivalent examination from a recognized board or university | Science (PCM) | 50% in class 10 th |
| Bachelor’s | Passed 10+2 or equivalent examination from a recognized board or university | Science (PCM) | 50%-60% aggregate marks in class 12 th |
| Master’s | Bachelor’s in Engineering or Technology from a recognized university |
Engineering | 50%-60% aggregate marks in Bachelor’s degree |
| Doctoral | Master’s in Engineering or Technology from a recognized university | Engineering | 50%-55% aggregate marks in Master’s degree |
| NIRF Ranking. | Leading Institutes | City |
|---|---|---|
| 1 | Indian Institute of Technology Madras | Chennai |
| 2 | Indian Institute of Technology Delhi | New Delhi |
| 3 | Indian Institute of Technology Bombay | Mumbai |
| 4 | Indian Institute of Technology Kanpur | Kanpur |
| 5 | Indian Institute of Technology Roorkee | Roorkee |
| 6 | Indian Institute of Technology Kharagpur | Kharagpur |
| 7 | Indian Institute of Technology Guwahati | Guwahati |
| 8 | Indian Institute of Technology Hyderabad | Hyderabad |
| 9 | National Institute of Technology Tiruchirappalli | Tiruchirappalli |
| 10 | Jadavpur University | Kolkata |
| Sl. No | Entrance Exam | Conducting Body |
|---|---|---|
| 1 | Joint Entrance Examination (JEE) Main | National Testing Agency (NTA) |
| 2 | Joint Entrance Examination (JEE) Advanced | Indian Institutes of Technology (IITs) |
| 3 | Birla Institute of Technology and Science Admission Test (BITSAT) | Birla Institute of Technology and Science (BITS), Pilani |
| 4 | Vellore Institute of Technology Engineering Entrance Examination (VITEEE) | Vellore Institute of Technology (VIT) |
| 5 | SRM Joint Engineering Entrance Examination (SRMJEEE) | SRM Institute of Science and Technology |
| 6 | Manipal Entrance Test (MET) | Manipal Academy of Higher Education (MAHE) |
| 7 | Amrita Entrance Examination Engineering (AEEE) | Amrita Vishwa Vidyapeetham |
| 8 | KIITEE (Kalinga Institute of Industrial Technology Entrance Exam) | Kalinga Institute of Industrial Technology (KIIT) |
| 9 | Consortium of Medical, Engineering and Dental Colleges of Karnataka Under Graduate Entrance Test (COMEDK UGET) | COMEDK |
| 10 | West Bengal Joint Entrance Examination (WBJEE) | West Bengal Joint Entrance Examinations Board (WBJEEB) |
- Data analysis: To examine huge datasets, glean insights, and facilitate data-driven decision-making, apply statistical techniques and machine learning algorithms.
- Model Development: To solve complicated issues and enhance business procedures, develop, put into practice, and optimize predictive models and algorithms.
- Data management: It involves organizing and preparing data while guaranteeing its security, integrity, and quality across a range of platforms and instruments.
- Cooperation: Assist cross-functional teams in incorporating data solutions into goods and services, and disseminating research results via reports and graphics.
| PROS | CONS |
|---|---|
| A robust labor market is witnessing an increase in the need for data scientists throughout a range of businesses. | The curriculum is difficult and demands a solid background in programming, statistics, and mathematics. |
| Attractive compensation packages and competitive beginning salary. | This constantly changing subject needs ongoing education and adjustment to new instruments and methods. |
| Skills that are useful in a variety of industries, including technology, e-commerce, healthcare, and finance. | Solving complicated and unstructured issues is a cognitively taxing task that requires problem-solving skills. |
| Possibilities to participate in creative initiatives and work on cutting-edge technology. | As the profession becomes more and more well-known, there is fierce competition for jobs, necessitating exceptional training and expertise. |