Question 1

Can i do major in datascience with mechanical degree with 7.26cgpa?

Accepted Answer

A person with a mechanical degree and a 7.26 CGPA (Grade Point Average) may be able to pursue a graduate degree in data science, but it would depend on the specific requirements and admissions policies of the universities or institutions in question.

Many graduate programs in data science require a strong academic background in math, statistics, and computer science, which may be more closely aligned with a traditional computer science or electrical engineering degree. Additionally, a certain level of experience and skill in programming and data analysis is also often required.

There are many universities and institutions around the world that offer graduate programs in data science, including universities in the following countries:

United States: MIT, Stanford University, University of California, Berkeley, Harvard University, Carnegie Mellon University, among others.
United Kingdom: University of Cambridge, Imperial College London, University of Oxford, among others.
Germany: the Technical University of Munich, Ludwig Maximilian University of Munich, among others
France: Sorbonne University, École Normale Supérieure Paris-Saclay, among others
Australia: Monash University, University of Melbourne, and University of Sydney, among others

These are just a few examples of the many universities around the world that offer graduate programs in data science, and there are many other options available depending on your location and interests. Keep in mind that this is not a comprehensive list and the availability of the program and specific requirements may vary in different Universities.

If you have any other questions feel free to leave a comment below.

Question 2

What is the difference between MS in business analytics, MS in MIS, and MS in Data Analytics, I am currently targeting the USA as my study location?

Accepted Answer

Some of the major differences between MS in business analytics, MS in MIS, and MS in Data Analytics are:-

MIS and related are conventional IT degrees, whereas BA/BI/BD levels are established on facts and/or analytics. Therefore, if you want to have greater flexibility in your IT career, I would advise going the MIS route.
If desired and possible, you can choose data/analytics selective guides (or even, specialization, if supplied at the institutions that you consider) to be "closer" to the currently warm large statistics/analytics trend.
An additional doable benefit of an MIS diploma is IMHO its higher suitability for managerial positions if you are interested in that. As for your work (TCS), I'm sorry that I can't comment on that, as I'm now not intently familiar with the Indian IT market.

Hope this works for you!

Share your profile to get evaluated which is best for you!

Question 3

What are the top career options for data analytics and data science?

Accepted Answer

Data analytics and data science are often considered as one, but there is a difference. Data science is a vast career, and data analytics is a subset of data science. A large number of people today are inclining toward data analytics and data science careers. Well, there are various reasons for this inclination, such as :

This is a field where there is a high average salary of individuals.
The industry is growing at a fast pace, and there is a huge demand for skilled personnel.
There is a lot of room for advancement in a career in this field.
So let’s now discuss the various job roles. As I have mentioned that data analytics and data science are two different fields, here are the top two career options for each of them separately.

Career options in data analytics:

Data analyst: This is the most common job role in the field of data analytics. But it does not mean that this does not have a wide career scope. We have already discussed that this field industry is facing a huge shortage of skilled individuals. The role of a data analyst is to analyze huge chunks of data and maintain databases.
Business Intelligence Analyst: Every moment, there is a huge momentum in the market, competitors, customers, anything that may take a huge turn at any moment, and that will have a huge impact on the business and its future. Therefore it is important for a business to analyze these shifts and turns in the market and make correct decisions accordingly. This is where the role of a Business Analyst comes to play. They analyze the shifts in market trends so that management can make appropriate decisions timely.

Career options in data science:

Data Engineer: This role is within the field of data science so this field will require more technical skills, and the problems will be more complex. The role of a data analyst requires maintenance of databases, the responsibilities of a data engineer are one step ahead. They are also responsible for updating those databases and data structures.
Project Manager: Project managers work with a team of data analysts and track their team's efficiency and progress. Project managers also maintain coordination with the data analysts and data scientists to maximize productivity and deliver the best results.

Question 4

What is the difference between Columbia's MS in Data Science and Columbia's MS in CS with the machine learning track?

Accepted Answer

First of all, Columbia's MS in Data Science and Computer Science are both excellent programs. But I do want to suggest you know it with some elements. You see, even with MS computer science with the machine learning track, it offers way too many options. So, you can choose from numerous courses under the MS computer science with machine learning. Whereas MS in data science is more of statistics and analytics. In a way you kind of stick with it, which by the way is not a bad thing.

This option delivers to more individuals who are interested in the field. You may not know how many students change their career paths while in their masters. In this case MS in CS with a machine learning track is far more viable.

Now, this may seem a bit technical, but important if you want to figure out the difference. The MS in data science does consist of computer systems and operations, machine learning etc. But it's far more directional. The course options for MS in data science will be more focused on data science principles. Of-course it goes for MS CS with machine learning as well. However, MS CS machine learning track will offer a wider CS learning.

As complicated as it seems, it's just a matter of limit on availability in both programs. You can either go for a rather more universal opinion or a directional one. Simple right? And if your career modules are already set, just go for the required elective options keeping the subject approach in mind.

Question 5

Best 5 colleges in UK for MS data science or data analytics?

Accepted Answer

Data Science is a rapidly growing field that has achieved vital importance in today's data-driven world. It has become a requirement for businesses to keep a close eye on the data churned out of their respective fields to grow their businesses. This, in turn, has increased the need for data scientists worldwide. Owing to its popularity, several universities in the UK have started teaching the subject. Some of the best universities for Data Science in the UK cater to students' demands by providing them with various comprehensive courses.

Best Universities for Data Science
University of Oxford
King's College London
University of Manchester
University of Bristol

Eligibility Criteria

A minimum of a 2.1 honors degree (60-70% score) with computer science as a major subject
IELTS score: Between 6.5-7.0 overall with no less than 6.0-6.5 in all components.

Documents Required for the Admission Process.

Academic transcripts as proof of your academic achievements
Explanation of English Proficiency scores
Proof of funds as evidence to pay for the tuition fees and monthly living costs for the first year
Resume
Two academic reference letters
SAT scores
ACT scores
Statement of Purpose (SOP) for studying in the UK.

Question 6

What's the difference between data analytics and data science?Which country is best for masters?

Accepted Answer

Two of the most sought-after, well-paying careers in 2021 are data analysts and data scientists. These positions were ranked first for rising demand across industries in the World Economic Forum's Future of Jobs Report 2020, followed by big data and AI professionals.

Data analysts often use tools like SQL, R or Python programming languages, data visualization software, and statistical analysis to work with structured data to address real-world business issues. Typical tasks for a data analyst could be:

Identifying informational needs in collaboration with organizational executives.
Obtaining information from both primary and secondary sources.
Data organization and cleaning up for analysis.
Examining data sets to find patterns and trends that can be transformed into knowledge that can be used.
Making clear presentations of findings to help decision-makers use data to their advantage.

When dealing with the unknown, data scientists frequently use more sophisticated data approaches to generate future predictions. They might develop techniques for predictive modeling that can handle both structured and unstructured data, or they might automate their machine learning algorithms. This position is typically viewed as an improved version of a data analyst. Typical daily chores could include:

Gathering, purifying, and processing unprocessed data
Using machine learning algorithms and predictive models to harvest large data sets
Creating instruments and procedures to track and evaluate data accuracy
Building dashboards, reports, and tools for data visualization
Programming the collection and processing of data in an automated manner

The best Nations for Data Science and Data Analytic education are:

United States

The University of California at #4
Carnegie Mellon University at #53
Massachusetts Institute of Technology at #1
Stanford University at #3
The University of Washington at #85

United Kingdom

The University of Edinburgh at #16
The University of Warwick at #61
Imperial College London at #7
The University of Manchester at #27
The University of Southampton at #77

Australia

The University of Melbourne at #37
Monash University at #58
The University of Sydney at #38
RMIT University at #206
UNSW Sydney at #43

Germany

Technische Universität München at #159
The Ludwig Maximilian University of Munich at #64
The University of Mannheim at #423
Technical University Dortmund at #801
Leuphana University of Lüneburg at #1000

Canada

The University of Waterloo at #149
The University of British Columbia at #46
Ryerson University at #801-1000
The University of Toronto at #26
Carleton University at #601-650

Basically, data science and and data analytics are much connected but are not same. In simplest words, data science is a subset of data science that mainly deals with analytics. Its a specialization in data science. If you are in the process of selecting one of these for higher studies let me know. Maybe I can somehow be of help.

Bachelor's Degree	Need a bachelor's degree in data science, mathematics, statistics or a related field
GPA	Most universities require a GPA of at least 3.0 on a 4.0 scale, which is like getting scoring around 80% overall

GRE	GRE scores with a minimum of 130 in verbal, 140 in quantitative, and 2.5 in writing analysis. (Overall 280 - 320)
Language Proficiency Tests	International applicants generally need to prove their English skills by taking standardized tests. They usually have to achieve certain minimum scores. IELTS: 6.0 - 7.0 TOEFL: 80 - 90

Course	Description
Statistics for Data Science	Learn how to make sense of data through numbers. It's all about using statistics to find patterns and answer questions.
Machine Learning	This is where you teach computers to learn on their own from data. It's like training a robot to make smart decisions.
Data Mining	Dive into large sets of data to find the hidden treasures. It's like being a detective but for Dat
Data Visualization	Learn to turn data into visual stories that people can understand. It's about making complex info look simple and clear
Database Management	Get the skills to organize and manage data in databases. It's like setting up a super-organized digital filing system.

Course	Description
Big Data Analytics	Learn how to deal with really, really big sets of data and get insights from them. It's like data science but for giant datasets
Deep Learning	Dive deeper into machine learning with complex models. Think of it as teaching a computer to think and learn like a human brain.
Business Intelligence	Use data to make smart business decisions. It's about using data to figure out how to make a company more successful.
Data Ethics and Privacy	Learn about the right and wrong ways to use data, especially how to keep people's information safe and private.
Natural Language Processing	Teach computers to understand human language. It's like helping a robot read and understand books or conversations.

Job Roles	Average Salary
Machine Learning Engineer	$1,65,072 per year
Data Scientist	$1,54,755 per year
Big Data Developer	$1,67,097 per year
Database Administrator	$100,891.35 Per year
Analytics Engineer	$118,766 per year

Masters in Data Science in USA

Table of Contents

Table of Contents

Master of Science in Data Science

Eligibility Requirements

Academic Qualifications:

Standardized Test Scores:

Additional Requirements:

Application Process and Requirements

Data Science Curriculum and Skills Required

Core Courses

Elective Courses

Soft Skills Development

Financial Aid and Scholarships

University Scholarships

Research Assistantships

Fellowships

External Scholarships

On-Campus Employment

Loans

Career Opportunities

Here are some career options you can explore:

Machine Learning Engineer

Data Scientist

Big Data Developer

Database Administrator

Analytics Engineer