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Eligibility Criteria for Data Science Courses

  • A bachelor's degree in computer science, IT, statistics, or STEM (science, technology, engineering, and mathematics)
  • A minimum of 50% marks in 10th and 12th grades is necessary
  • Understanding of programming languages such as Python, R, and SQL
  • Understanding of mathematical and statistical concepts such as linear algebra, calculus, and probability theory
  • Possession of soft skills such as problem-solving, critical thinking, and time management
  • Passion for working with data and the curiosity to uncover insights

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Eligibility Criteria For Different Data Science Courses

Check out the comprehensive guide on the eligibility criteria for various data science courses offered by Great Learning.

Data Science Courses Eligibility Criteria

Great Learning offers several top data science certificate courses to suit various needs and skill levels. The eligibility criteria for these courses may vary depending on the specific program and its requirements.

 

Here is detailed information on the eligibility criteria for each course to help aspiring data scientists meet the requirements and succeed in their careers:

 

Course Name

University

Eligibility Criteria

PG Program in Data Science and Business Analytics

The University of Texas at Austin (UT Austin) McCombs School of Business

A bachelor's degree in computer science, IT, statistics, STEM (science, technology, engineering, and mathematics), or any other related field

PG Program in Data Science and Business Analytics (Classroom)

Great Lakes Executive Learning

A bachelor's degree in computer science, IT, statistics, STEM (science, technology, engineering, and mathematics), or any other related field

Data Science and Machine Learning

Massachusetts Institute of Technology Institute for Data, Systems, and Society (MIT IDSS)

Data scientists, data analysts, and working professionals who want to extract

actionable insights from massive volumes of data

 

Early career professionals and senior managers, such as technical managers, BI analysts, IT practitioners, management consultants, and business managers

 

Those with some academic/professional background in statistics/applied mathematics. Nevertheless, participants without this experience will need to put in extra effort and will receive assistance from Great Learning

PG in Data Science (Online)

Great Lakes Executive Learning

Bachelor’s degree and a minimum grade point average of 60% in 10th and 12th grades

 

Final semester students, graduate students, and working professionals with 0-3 years of experience

 

Best candidates for the course: A degree in engineering, commerce, sciences, statistics, mathematics, economics, and other related fields

PG in Data Science (Bootcamp)

Great Lakes Executive Learning

Bachelor’s degree and a minimum grade point average of 60% in 10th and 12th grades

 

Final semester students, graduate students, and working professionals with 0-3 years of experience

 

Best candidates for the course: A degree in engineering, commerce, sciences, statistics, mathematics, economics, and other related fields

MS in Data Science (Online)

Northwestern University

A 4-year U.S. bachelor’s degree or equivalent

 

For students with a 3-year bachelor’s degree:

> Students who didn’t complete their degree in the U.S.: Their transcript evaluation must state that their degree is equivalent to a 4 year U.S. bachelor’s degree

> Students who completed their degree in the U.S.: They must possess a 4-year bachelor’s degree

 

The medium of instruction for the candidate’s bachelor’s degree must be English. If not, they would need to give an English language proficiency test like IELTS/TOEFL

Master of Data Science - 24 Months

Deakin University

Deakin’s minimum English language requirement

 

Minimum 3-year bachelor’s degree in a related discipline

 

Minimum 3-year bachelor’s degree in any discipline with at least 2 years of professional experience

Master of Data Science - 12 Months

Deakin University

Deakin’s minimum English language requirement

 

Minimum 3-year bachelor’s degree in a related discipline

 

Minimum 3-year bachelor’s degree in any discipline with at least 2 years of professional experience

 

Candidates must have completed either PGP-DSBA or PGP-AIML offered by UT Austin and Great Learning

 

Data Science Prerequisites
 

  • Basic knowledge of mathematics: Linear algebra, calculus, & Probability

  • Proficiency in programming: Python/R & SQL

  • Familiarity with statistics: Hypothesis testing & regression analysis

  • Understanding of machine learning concepts and algorithms

  • Knowledge of big data technologies: Hadoop & Spark

  • Experience with data visualization tools: Tableau & Matplotlib

 

Who Should Learn Data Science?
 

  • IT/Software Professionals

  • Business Professionals

  • Engineers & Scientists

  • Entrepreneurs

  • Undergraduate/Graduate Students

  • Data Enthusiasts
     

Data Science Qualifications
 

To excel in a data science course and pursue a career in this cutting-edge field, several key qualifications are highly valued:

 

  • Academic Qualifications

A bachelor's or master's degree in a relevant field, such as computer science, mathematics, statistics, science, technology, or engineering, provides a strong foundation in quantitative analysis, programming, and data management. These skills are essential for success in the data science discipline.

 

  • Practical Experience

Hands-on experience with data analysis methods and programming languages is also highly valued. It includes proficiency in popular programming languages like Python, R, and SQL and experience working with various data analysis processes like data cleaning and data visualization. Having practical experience with real-world data problems is vital for building valuable skills.

 

  • Industry-Specific Knowledge

Industry-specific knowledge is also essential, depending on the area of data science you are interested in. For instance, if you are interested in data science for finance, a background in finance and accounting may be beneficial. Understanding your chosen industry's specific challenges and opportunities will help you apply data science techniques more effectively.

Frequently asked questions

What is the data science course eligibility at Great Learning?


At Great Learning, the eligibility for data science often requires the prospective learner to have a Bachelor's degree in a related field like STEM (science, technology, engineering, and mathematics), statistics, economics, computer science, or IT. However, it can vary depending on the complexity and level of the specific course.

Do I need a background in technology for eligibility to learn data science at Great Learning?


Not necessarily. While having knowledge of technology can be beneficial, the core eligibility for data science involves having an analytical mindset and a willingness to learn. Many of the courses provide the foundational knowledge necessary for a successful career in data science.

What's the eligibility for a data analyst course at Great Learning?

 

The data analyst course eligibility usually requires a Bachelor's degree and some basic knowledge of statistical concepts. However, the data analyst course from Great Learning is designed to be comprehensive and accessible, even for beginners with minimal prior knowledge.

 

Is there any specific eligibility criteria for data science courses at Great Learning?

The eligibility criteria for a data science course at Great Learning typically include a Bachelor's degree in a relevant field and a basic understanding of mathematical concepts. However, the requirements vary between programs, and we recommend checking the specific course page for accurate details.

 

What are the age criteria included in the data science eligibility?


Great Learning doesn't set any age restrictions for its courses. The eligibility for a data science course is mainly based on educational background and a desire to learn.

Do I need to know programming languages to be eligible for the data science course?


While knowledge of programming languages such as Python or R can be beneficial, it is not a strict eligibility criterion for our data science courses. Many of the programs include modules that teach these languages from the basics.

Is work experience part of the data science course eligibility criteria at Great Learning?


Some advanced data science courses may require a few years of work experience but are not necessary for all the programs. Great Learning has a range of programs suitable for both freshers and experienced professionals.

Can I take a data science course if I am from a non-technical background? What's the eligibility for data science in this case?


Yes, you certainly can. At Great Learning, we believe in making education accessible. So, even from a non-technical background, your eligibility for data science is not affected as long as you have a passion for learning and problem-solving.

What are the prerequisites for eligibility to learn data science at Great Learning?


The essential eligibility criteria for a data science course at Great Learning typically include a Bachelor's degree and a solid understanding of mathematical concepts. However, prerequisites can vary between programs, and many require no prior knowledge.

Are international students eligible for the data science courses offered by Great Learning?


Yes, Great Learning welcomes students from all over the world. There are no specific geographical restrictions that affect the eligibility for a data science course with Great Learning.