PhD in Data Science

PhD in Data Science

11 mins readComment
Vikram
Vikram Singh
Assistant Manager - Content
Updated on May 24, 2024 18:18 IST

Considering a Ph.D. in data science? This in-depth article explores the ins and outs of pursuing a doctoral degree in this rapidly evolving field, providing valuable insights for aspiring researchers and professionals.

PhD in Data Science

What is a PhD?

A Ph.D., or Doctor of Philosophy, is the second highest academic degree after Post-Doc that can be obtained in most fields. It is research oriented and requires independent original research, followed by a contribution to the particular area of interest. A PhD is a testament to an individual's expertise, dedication, and ability to advance knowledge in their chosen discipline.

What is Data Science?

Data science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. It combines mathematics, statistics, computer science, and domain-specific knowledge to analyze and interpret complex data sets.

Why PhD in Data Science?

  • Specialized Knowledge: Individuals pursuing a PhD in data science delve deep into advanced data analysis techniques, machine learning algorithms, and statistical modeling, gaining a comprehensive understanding of these complex concepts.
  • Research Opportunities: A PhD program allows you to conduct groundbreaking research in big data, artificial intelligence, and data mining, providing avenues to contribute to the advancement of these fields.
  • Career Advancement: A PhD in data science can expand career opportunities, providing paths to leadership roles in industry, academia, and research institutions, and potentially leading to influential positions in the data science field. 
  • Expertise in Data Handling: The demanding curriculum enhances skills in data management, manipulation, and interpretation, which are essential in today's data-driven environment. 
  • Problem-Solving Skills: The program helps individuals develop strong analytical and critical thinking skills, enhancing their ability to address complex data-related challenges effectively and innovatively.

What are the prerequisites/eligibility for PhD in Data Science?

  • A bachelor's or master's degree in a relevant field, such as computer science, statistics, mathematics, or a domain-specific area
  • A solid academic record and relevant research experience
  • Strong quantitative and analytical skills
  • Proficiency in programming languages (e.g., Python, R, SQL)
  • Knowledge of statistical and machine learning techniques
  • Excellent research and communication skills
  • You have to qualify for entrance exams like NET, SET, and GATE (if applying in India). 
    • if you are applying PhD, you have to qualify for GRE/GMAT/TOEFL/IELTS.

Must Do Courses Before Enrolling PhD in Data Science

  1. Coursera
    • Machine Learning by Stanford University
    • Deep Learning Specialization by deeplearning.ai
    • Data Science Specialization by Johns Hopkins University
    • Mathematics for Machine Learning Specialization by Imperial College London
  2. edX
    • Data Science Professional Certificate by IBM
    • Analytics for Data Science Professional Certificate by ColumbiaX
    • Fundamentals of Statistics by MITx
    • Artificial Intelligence (AI) by ColumbiaX
  3. Udacity
    • Machine Learning Engineer Nanodegree
    • Data Scientist Nanodegree
    • Artificial Intelligence Nanodegree
    • Natural Language Processing Nanodegree
  4. Pluralsight
    • Python for Data Science
    • Machine Learning: The Big Picture
    • Linear Algebra for Machine Learning
    • Calculus for Machine Learning
  5. DataCamp
    • Data Scientist with Python Career Track
    • Machine Learning Scientist with Python Career Track
    • Data Engineer with Python Career Track
    • Importing & Cleaning Data in Python
  6. MIT OpenCourseWare
    • Introduction to Computer Science and Programming in Python
    • Mathematics for Computer Science
    • Probabilistic Systems Analysis and Applied Probability
    • Machine Learning
  7. LinkedIn Learning
    • Python for Data Science Essential Training
    • Machine Learning and AI Foundations: Machine Learning
    • Deep Learning: Computer Vision
    • Natural Language Processing Essential Training

How to Choose the Best Ph.D. in Data Science?

  • What are the research areas and specializations offered in the program?
  • What is the faculty expertise, and what are their current research projects?
  • What is the program's curriculum structure, and what courses are required?
  • Are there opportunities for interdisciplinary research and collaboration with other departments or institutions?
  • What kind of research facilities, computing resources, and software tools are available to PhD students?
  • What is the typical time-to-degree completion for the program?
  • What funding opportunities are available, such as teaching assistantships, research assistantships, or fellowships?
  • What is the program's track record in job placements and career outcomes for graduates?
  • Are there opportunities for internships or industry collaborations during the PhD program?
  • What is the program's admission process, and what are the deadlines?
  • What are the prerequisites and minimum requirements for admission?
  • Is there a qualifying or comprehensive exam, and when does it typically occur?
  • What is the process for selecting a dissertation advisor and committee?
  • Are there opportunities for presenting research at conferences or publishing in academic journals?
  • What is the program's overall culture and support system for PhD students?
  • What is the cost of attendance, including tuition, fees, and living expenses?
  • Are there any specific areas of research focus or strengths within the Data Science program?
  • What is the program's approach to balancing coursework and research requirements?
  • Are there opportunities for teaching experience or professional development?
  • What is the program's alumni network, and are there opportunities for networking and mentorship?

Top Colleges Offering PhD in Data Science in India

Indian Institute of Technology (IIT) Kharagpur

  • USP:
    • Pioneering institute in data science research and education
    • Strong focus on interdisciplinary research
    • Cutting-edge computing facilities and resources
    • Collaboration opportunities with industry and research labs
    • Renowned faculty with expertise in various data science domains
  • Course Duration: 3-5 years (full-time)
  • Eligibility: Master's degree in Computer Science, Statistics, Mathematics, or related fields with a minimum CGPA/CPI of 6.5 (on a 10-point scale) or equivalent.
  • Course Fees: Approximately INR 25,000 - 30,000 per semester for Indian students, higher for international students.

Indian Institute of Science (IISc) Bangalore

  • USP:
    • Renowned research-intensive institute
    • Interdisciplinary approach to data science
    • Strong industry collaborations and research opportunities
    • State-of-the-art computing facilities
    • Experienced faculty with diverse research interests
  • Course Duration: 4-6 years (full-time)
  • Eligibility: Master's degree in Computer Science, Statistics, Mathematics, or related fields with a minimum CGPA/CPI of 7.0 (on a 10-point scale) or equivalent.
  • Course Fees: Approximately INR 15,000 - 20,000 per semester for Indian students, higher for international students.

Indian Institute of Technology (IIT) Delhi

  • USP:
    • Interdisciplinary research in data science
    • Emphasis on applications in various domains
    • Collaboration with industry and research organizations
    • Well-equipped computing facilities
    • Experienced faculty with diverse research interests
  • Course Duration: 3-5 years (full-time)
  • Eligibility: Master's degree in Computer Science, Statistics, Mathematics, or related fields with a minimum CGPA/CPI of 7.0 (on a 10-point scale) or equivalent.
  • Course Fees: Approximately INR 25,000 - 30,000 per semester for Indian students, higher for international students.

International Institute of Information Technology (IIIT) Hyderabad

  • USP:
    • Specialized focus on data science and analytics
    • Emphasis on industry-relevant research
    • Collaboration with leading tech companies
    • State-of-the-art computing facilities
    • Experienced faculty with industry and research background
  • Course Duration: 3-5 years (full-time)
  • Eligibility: Master's degree in Computer Science, Statistics, Mathematics, or related fields with a minimum CGPA/CPI of 7.0 (on a 10-point scale) or equivalent.
  • Course Fees: Approximately INR 30,000 - 35,000 per semester for Indian students, higher for international students.

Indian Institute of Technology (IIT) Madras

  • USP:
    • Pioneering institute in data science research and education
    • Strong focus on interdisciplinary research
    • Cutting-edge computing facilities and resources
    • Collaboration opportunities with industry and research labs
    • Renowned faculty with expertise in various data science domains
  • Course Duration: 3-5 years (full-time)
  • Eligibility: Master's degree in Computer Science, Statistics, Mathematics, or related fields with a minimum CGPA/CPI of 7.0 (on a 10-point scale) or equivalent.
  • Course Fees: Approximately INR 25,000 - 30,000 per semester for Indian students, higher for international students.

Indian Institute of Technology (IIT) Bombay

  • USP:
    • Renowned institute with a strong research focus
    • Interdisciplinary approach to data science
    • Collaboration opportunities with industry and research labs
    • Well-equipped computing facilities
    • Experienced faculty with diverse research interests
  • Course Duration: 3-5 years (full-time)
  • Eligibility: Master's degree in Computer Science, Statistics, Mathematics, or related fields with a minimum CGPA/CPI of 7.0 (on a 10-point scale) or equivalent.
  • Course Fees: Approximately INR 25,000 - 30,000 per semester for Indian students, higher for international students.

Indian Statistical Institute (ISI), Kolkata

  • USP:
    • Specialized institute focused on statistics and data science
    • Strong emphasis on theoretical and applied research
    • Collaboration opportunities with industry and research organizations
    • Well-equipped computing facilities
    • Experienced faculty with diverse research interests
  • Course Duration: 3-5 years (full-time)
  • Eligibility: Master's degree in Statistics, Mathematics, Computer Science, or related fields with a minimum CGPA/CPI of 7.0 (on a 10-point scale) or equivalent.
  • Course Fees: Approximately INR 15,000 - 20,000 per semester for Indian students, higher for international students.

Top Colleges Offering PhD in Data Science Abroad

Carnegie Mellon University, USA

  • USP:
    • Pioneering research in machine learning, artificial intelligence, and data science
    • Interdisciplinary approach with collaborations across departments
    • Access to state-of-the-art computing facilities and resources
    • Strong industry partnerships and research opportunities
    • Renowned faculty with expertise in various data science domains
  • Course Duration: 4-6 years
  • Eligibility: Master's degree in a relevant field (e.g., Computer Science, Statistics, Mathematics) with excellent academic records and research potential.
  • Course Fees: Approximately $51,000 per year for tuition and fees.

Massachusetts Institute of Technology (MIT), USA

  • USP:
    • World-class research institution with a strong focus on data science
    • Interdisciplinary programs and collaborations across departments
    • Access to cutting-edge computing facilities and resources
    • Opportunities for industry collaborations and research projects
    • Renowned faculty with diverse research interests in data science
  • Course Duration: 4-6 years
  • Eligibility: Master's degree in a relevant field (e.g., Computer Science, Statistics, Mathematics) with exceptional academic records and research potential.
  • Course Fees: Approximately $53,790 per year for tuition and fees.

University of California, Berkeley, USA

  • USP:
    • Prestigious university with a strong data science program
    • Interdisciplinary approach with collaborations across departments
    • Access to state-of-the-art computing facilities and resources
    • Opportunities for industry collaborations and research projects
    • Renowned faculty with diverse research interests in data science
  • Course Duration: 4-6 years
  • Eligibility: Master's degree in a relevant field (e.g., Computer Science, Statistics, Mathematics) with excellent academic records and research potential.
  • Course Fees: Approximately $14,098 per year for tuition and fees for California residents, higher for non-residents.

University of Oxford, UK

  • USP:
    • Prestigious university with a strong data science program
    • Interdisciplinary approach with collaborations across departments
    • Access to state-of-the-art computing facilities and resources
    • Opportunities for industry collaborations and research projects
    • Renowned faculty with diverse research interests in data science
  • Course Duration: 3-4 years
  • Eligibility: Master's degree in a relevant field (e.g., Computer Science, Statistics, Mathematics) with excellent academic records and research potential.
  • Course Fees: Approximately £27,460 per year for tuition and fees for international students.

National University of Singapore (NUS), Singapore

  • USP:
    • Renowned university with a strong focus on data science and analytics
    • Interdisciplinary approach with collaborations across departments
    • Access to state-of-the-art computing facilities and resources
    • Opportunities for industry collaborations and research projects
    • Renowned faculty with diverse research interests in data science
  • Course Duration: 4-5 years
  • Eligibility: Master's degree in a relevant field (e.g., Computer Science, Statistics, Mathematics) with excellent academic records and research potential.
  • Course Fees: Approximately $18,000 per year for tuition and fees for international students.

Top Colleges Offering PhD in Data Science in Part-Time and Online Mode

Syracuse University, USA (Online)

  • USP:
    • Flexible online format for working professionals
    • Interdisciplinary curriculum covering various data science domains
    • Access to online resources and computing facilities
    • Opportunities for research and industry collaborations
    • Experienced faculty with diverse research interests
  • Course Duration: 3-7 years (part-time)
  • Eligibility: Master's degree in a relevant field (e.g., Computer Science, Statistics, Mathematics) with a minimum GPA of 3.0 or equivalent.
  • Course Fees: Approximately $1,834 per credit hour.

Georgia Institute of Technology, USA (Online)

  • USP:
    • Flexible online format for working professionals
    • Interdisciplinary curriculum with a focus on applications
    • Access to online resources and computing facilities
    • Opportunities for research and industry collaborations
    • Renowned faculty with diverse research interests
  • Course Duration: 4-6 years (part-time)
  • Eligibility: Master's degree in a relevant field (e.g., Computer Science, Statistics, Mathematics) with a minimum GPA of 3.0 or equivalent.
  • Course Fees: Approximately $1,189 per credit hour.

University of Southern California, USA (Part-time)

  • USP:
    • Flexible part-time format for working professionals
    • Interdisciplinary curriculum with a focus on applications
    • Access to on-campus resources and computing facilities
    • Opportunities for research and industry collaborations
    • Renowned faculty with diverse research interests
  • Course Duration: 4-6 years (part-time)
  • Eligibility: Master's degree in a relevant field (e.g., Computer Science, Statistics, Mathematics) with a minimum GPA of 3.0 or equivalent.
  • Course Fees: Approximately $2,193 per unit.

Northcentral University, USA (Online)

  • USP:
    • Flexible online format for working professionals
    • Interdisciplinary curriculum with a focus on applications
    • Access to online resources and computing facilities
    • Opportunities for research and industry collaborations
    • Experienced faculty with diverse research interests
  • Course Duration: 3-7 years (part-time)
  • Eligibility: Master's degree in a relevant field (e.g., Computer Science, Statistics, Mathematics) with a minimum GPA of 3.0 or equivalent.
  • Course Fees: Approximately $1,136 per course

University of Edinburgh, UK (Part-time)

  • USP:
    • Flexible part-time format for working professionals
    • Interdisciplinary curriculum with a focus on applications
    • Access to on-campus resources and computing facilities
    • Opportunities for research and industry collaborations
    • Renowned faculty with diverse research interests
  • Course Duration: 4-6 years (part-time)
  • Eligibility: Master's degree in a relevant field (e.g., Computer Science, Statistics, Mathematics) with excellent academic records and research potential.
  • Course Fees: Approximately £7,200 per year for part-time students.

Career After PhD in Data Science

Research Scientist

  • Work in research labs or organizations (academia, government, or industry)
  • Conduct advanced research in specific areas of data science, such as machine learning, deep learning, natural language processing, computer vision, or domain-specific applications
  • Publish research papers and present findings at conferences
  • Collaborate with other researchers and contribute to the advancement of data science

Research Fellow/Postdoctoral Researcher

  • Conduct advanced research in specialized areas of data science
  • Work on research projects at universities, research institutes, or industry labs
  • Publish research papers and present findings at conferences
  • Collaborate with other researchers and contribute to the advancement of data science

Data Scientist

  • Work in various industries, such as technology, finance, healthcare, retail, or consulting firms
  • Develop and implement data-driven solutions to solve complex business problems
  • Design and build predictive models, algorithms, and machine learning systems
  • Analyze large datasets, uncover insights, and communicate findings to stakeholders

Professor/Lecturer

  • Teach data science courses at universities or colleges
  • Conduct research and publish scholarly articles
  • Supervise and mentor graduate students
  • Contribute to the development of data science curricula and programs

Consultant

  • Provide expert advice and solutions to organizations on data science projects
  • Help businesses leverage data and analytics to gain competitive advantages
  • Develop strategies and roadmaps for implementing data science initiatives
  • Collaborate with cross-functional teams to solve complex data-related challenges
About the Author
author-image
Vikram Singh
Assistant Manager - Content

Vikram has a Postgraduate degree in Applied Mathematics, with a keen interest in Data Science and Machine Learning. He has experience of 2+ years in content creation in Mathematics, Statistics, Data Science, and Mac... Read Full Bio