One account
Many possibilites
Data science is a postgraduate degree program that prepares students for the position of handling statistics, learning machines, data mining, analytics, and processing of massive data. The general time frame that students take to complete the degree of Ph.D. in Data Science is generally between four and six years if the candidate is studying full-time.
In order to lay the adequate foundation, students are provided with advanced mathematical and statistical knowledge, computer science and domain areas. It focuses on research techniques, quantitative methods, algorithms, data analysis tools, and practical use. The final years are spent in developing an original thesis under the guidance of a faculty member based on research that contirbutes fresh knowledge.
| Feature | Description |
|---|---|
| Full Form | Doctor of Philosophy (Data Science) |
| Duration | 3-5 years (full-time), Can be longer for part-time |
| Course Level | Doctoral Level |
| Eligibility | Master's degree in Computer Science, Statistics, Mathematics, or a related field with a strong foundation in statistics, programming, and data analysis, and minimum marks (usually 55%) |
| Top Colleges (India) | Indian Institutes of Technology (IITs) - Delhi, Bombay, Kanpur, Kharagpur, Madras, Indian Institute of Science (IISc) Bangalore, Indian Statistical Institute (ISI) Kolkata, Delhi |
1. Possessing a sound knowledge in Computer science/Statistics/Mathematics/Economics/any other quantitative field with Masters degree having minimum 60% marks or equivalent CGPA from any recognized university.
2. Have passed entrance tests such as GATE/NET or have potential for research as evidenced by any published material or letters of recommendation, etc.
3. A strong understanding of the mathematical prerequisites including probability and statistics, linear algebra, calculus, and solid programming skills coupled with good quantitative problem-solving skills.
4. Relevant work experience through projects/ internships etc. in the areas of data science and machine learning will be preferred.
5. Proper communication and interpersonal skills especially when working in a large team that cuts across various disciplines.
6. A strong desire to know the latest innovations in the data science field and use them to address existing challenges.
| Subject | Important Topics |
|---|---|
| Foundations of Data Science | Machine Learning Fundamentals, Statistics for Data Science, Database Management Systems, Big Data Processing & Analytics |
| Advanced Machine Learning | Deep Learning Techniques (Convolutional Neural Networks, Recurrent Neural Networks), Probabilistic Graphical Models, Reinforcement Learning |
| Data Analysis & Visualization | Data Preprocessing & Feature Engineering, Statistical Modeling & Inference, Time Series Analysis, Data Visualization Techniques |
| Scientific Computing | High-Performance Computing for Data Science, Parallel and Distributed Computing, Cloud Computing for Data Science |
| Specialization | Job Titles | Average Salary (INR) |
|---|---|---|
| Machine Learning | Machine Learning Engineer, Research Scientist (Machine Learning), Artificial Intelligence Researcher | 12-18 Lakhs |
| Deep Learning | Deep Learning Engineer, Computer Vision Scientist, Natural Language Processing Engineer | 14-20 Lakhs |
| Data Engineering | Big Data Architect, Data Warehouse Architect, Cloud Data Engineer | 12-18 Lakhs |
| Data Analytics | Data Analyst (Advanced), Business Intelligence Analyst, Data Scientist (with strong analytical skills) | 10-16 Lakhs |
| Artificial Intelligence | AI Researcher, Robotics Scientist, Human-Computer Interaction Specialist | 15-20 Lakhs |
| Data Visualization | Data Visualization Specialist, Information Designer, Business Intelligence Specialist (with visualization focus) | 10-14 Lakhs |
| Optimization & Decision Making | Operations Research Analyst, Management Scientist, Quantitative Analyst | 12-16 Lakhs |
