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Introduction Our Course
Data Science and Analytics
Data Science and Analytics is the field related to structured and unstructured data by application of various algorithms, preprocessing, and scientific methods for the result of meaningful information. The field can be counted in Artificial Intelligence (AI) and in demand for the past years also, helps in business because companies or organisations can make decisions on the basis of data.
Universities
27
Duration
2 Years
Eligibility
Graduation
What is Data Science and Data Analytics?
Data science indicates all aspects of data processing from the collection to modeling to insights. On the other hand, data analytics mainly relates to statistics, mathematics, and statistical analysis.
Why pursue Data Science and Data Analytics?
Choosing data science means building expertise with positive change. Being a data scientist, you can provide valuable information to the leaders to make confident decisions and much more.
Difference Between Data Science and Data Analytics:
|
Feature |
Data Science |
Data Analytics |
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Coding Language |
The most common language is Python for data science along with the use of other languages such as C++, and Java. |
Knowledge of Python and R Language is an essential element for Data Analytics. |
|
Programming Skills |
Depth knowledge of programming is demanded for data science. |
Basic Programming skills are required for data analytics. |
|
Use of Machine Learning |
Data Science uses machine learning algorithms to get insights. |
Data Analytics does not use machine learning to get the insight of data. |
|
Other Skills |
Data Science considered the use of Data mining activities to get significant insights. |
Hadoop-based analysis is used for getting determinations from raw data. |
|
Scope |
The scope of data science is wide. |
The Scope of data analysis is micro i.e., narrow. |
Why pursue Data Science and Data Analytics?
Businesses generally optimize their operations depending on the data analytics for which organizations need a wide no of professionals for analysis. Data analytics are very high in demand and very fast growing with rapid growth.
What is the scope of Data Science and Data Analytics:
Data science is based on the research field while analytics is based on the practical fields. In data science, You have to research the data, and based on the research you have to come up with new conclusions but In Analytics, you must use the pre-existing data and put them into functional formats.
The scope of data science is at a wide level while data analytics is at a narrow (Limited) level. Data science aims the innovations and explorations and data analytics aims at creating further data from existing data.
Distance Education in Data Analytics:
Data Analytics is commonly a full-time distance programe. The duration of general distance courses is 12 months which is recognized in private and state sectors. Universities, including IIM, IIT, and IGNOU have offered data analytics online courses through distance education.
For more course details you can visit here: https://www.academiccourses.com/courses/data-analytics/distance-learning
Duration of courses in Data Science and Data Analytics:
The duration for a bachelors degree in data science is three years while a master's degree takes two years. The duration for the PG Diploma program for professionals, on the other hand, lasts one year. The duration for Online certification courses is three to six months.
Professionals can gain basic proficiency in data analytics in a minimum of three months, with mastery in approximately three to four years.
Entrance Exams for Data Analytics:
The essential qualifying requirements for admission to Data Analytics:
- Bachelor's Programme: Applicants should have passed their Intermediate and Secondary schooling (10+2) or an equivalent science or commerce test (Math must be preferred).
- Master Program: Admission to the MBA Data Analytics program is specified by entrance tests at the state and national levels.
Entrance exams are mentioned as:
- JEE MAINS & JEE Advanced (To pursue bachelors in data science)
- CUET (Conducted by Christ University)
- CAT
- MAT
- GATE
- NIMSEE (Conducted by NIMS University)
Eligibility for Data Science and Data Analytics:
Candidates should have a Graduation in Science or Engineering with 50% Marks and maths/Statistics/CS/IT as one of the core subjects. Candidates must have 50 - 60% marks in class 10+2 exams & basic knowledge of Statistics, Mathematics, and Programming.
Specializations offered in Data Analytics:
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M.Tech in Data Science
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MBA in Data Analytics |
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MSc (Data Analytics) |
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Courses/Syllabus for Data Science and Data Analytics:
The Data Analytics course syllabus may differ from course to course or university to university but there are a few common data analytics subjects that are listed below:
Data Analytics Course Syllabus |
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Top Companies Hiring Data Analytics Professionals:
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Top Companies Hiring Data Analytics Professionals |
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Career opportunities in Data Science and Data Analytics:
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Career or Job Opportunities after Data Science and Data Analytics |
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