18 mocks pack: 1. Manhattan GRE 6 tests 2. Kaplan 5 3. Princeton 4 4. ETS powerprep plus online 1,

18 mocks pack: 1. Manhattan GRE 6 tests 2. Kaplan 5 3. Princeton 4 4. ETS powerprep plus online 1,2,3 paid ones 5. FREE downloaded Magoosh Videos and Practice sets DM for info and price

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Anyone from queens University Belfast...for business analytics?

#uk #qub #IndianStudent #abroadeducation

Best Schools for Masters in Business Analytics and Management Information Systems

Do you have a hard time distinguishing between Business Analytics and Management Information Systems? Don't know which one to choose? Allow me to provide you with some clarification! What is Business Analytics? Business analytics (BA) is a set of disciplines and technologies that use data analysis, statistical models, and other quantitative methods to solve business problems. It entails an iterative, methodical exploration of an organization's data to drive decision-making, with a focus on statistical analysis. Business analytics takes a data-driven approach to business that employs statistics and data modelling to generate new business insights. This combination of technology and business makes it an excellent choice for anyone interested in programming or working with data. What is Management Information Systems? People, processes and information systems are how organisations do business. Management Information Systems (MIS) is an interdisciplinary major that focuses on how to use technology, people, and processes to improve, transform, and support business operations. It is a discipline that focuses on the management of information and communications technology elements within businesses. MIS professionals contribute significantly to the competitiveness and well-being of the organisations for which they work. They are intelligent, people-oriented, and understand how technological systems are used in the workplace. If you have the right people, data, technology, and business skills, you should consider getting a master's degree in Management Information Systems. Here are some of the best Business Analytics programmes in the United States from top public and private schools- Public Universities: -Arizona State University MS in Business Analytics -University of Maryland College Park MS in Business Analytics -University of Illinois at Chicago MS in Business Analytics -University of Minnesota Twin Cities MS in Business Analytics -UC San Diego MS in Business Analytics -UC Davis MS in Business Analytics -UC Riverside MS in Business Analytics -University of Texas at Dallas MS in Business Analytics -Purdue University MS in Business Analytics and Information Management Private Universities: -Boston University's MS in Business Analytics -Northeastern University MS in Business Analytics -University of Connecticut MS in Business Analytics and Project Management -University of Southern California MS in Business Analytics Here are some of the best MIS programmes in the United States from top public and private schools Public Universities: -UC Berkeley MS in Management Information Systems -University of South Florida MS in Business Analytics and Information Systems -University of Illinois at Urbana Champaign MS in Information Management -Arizona State University MS in Management Information Systems -Texas A& M University MS in Management Information Systems -Georgia State University MS in Information Systems -University of Illinois at Chicago MS in Management Information Systems -University of Texas Dallas MS in Information Technology Management -Rutgers University MS in Information Technology and Analytics -University of Maryland College Park MS in Information Systems -University of Florida MS in Information Systems and Operations Management -University of Arizona MS in Management Information Systems Private Universities: -Syracuse University MS in Information Systems -Northeastern University MS in Information Systems -Carnegie Mellon University MS in Information Systems Management These are a mix of schools that are safe, moderate, and ambitious depending on the applicant's profile. Visit each school's website to see the curriculum in order to find out which school's coursework aligns more with your goals and interests. Additionally, you can look at the admissions page to learn more about the requirements. A great place to start your university search is Yocket's College Finder tool. The tool predicts your chances based on previous applicants. You can get a good idea of your profile and the quality of schools you get as a result. Here's the link: https://yocket.com/college-finder Good luck. #masters #ms #USA #BusinessAnalytics #informationsystems #informationstudies #fall2023 #business #technology #analytics #management #managementinformationsystems

Why having a credit card is important in the USA ?

The advantages of having a credit card are dependent on what your credit scores are in the USA. Credit scores can be anywhere from 300 to 850. As an F1 visa student, the score might range from 680 to 710. A credit score can be considered very good if it is above 740. If your credit score is good : -You will have to pay less interest for loans in the future. -You will have to pay less security deposit while you are renting out an apartment. -You will be given multiple cashback offers if you have a good credit score. A score of 710 and above denotes that you pay your dues on time, you pay your interest on time, and you pay your credit card bill on time. You do not overspend. Spend only 30-40% of the credit limit. To have a credit card, you will need a social security number(SSN). To get an SSN, you will require an authorized work visa. All F1 visa students can work up to 20 hours per week on-campus jobs. To work on campus as well, you will have to have an SSN. SSN is a unique number assigned to each individual which puts you in the USA tax system. As soon as you get a credit card, you will have to build a credit score over a period of at least 6 months. Not all credit cards require an SSN, multiple banks give credit cards to international students based on the i20 and other documents. You have to submit your SSN after you receive it and then these banks can report your credit history. Various credit cards have various benefits like 1% cashback on everything and many more. Companies like NOVA credit lets you use your Indian credit history to apply for a USA credit card. You will have to apply from the USA for a NOVA credit card because it requires a USA address. This will not only help you build a credit history from day 1 itself but also will help you to get various rewards. You can also get gift cards after referring to other people or using other people’s referral codes. If you plan to apply for a USA credit card from India itself, neo banks like zolve credit cards are a good way to go. Many Neo bank credit cards can be availed by using your i20. How are forex cards different? Forex cards are prepaid cards that can be used for cross-country currency exchange. You will have to load a certain amount of money into your forex card. The disadvantage of forex cards is that it does not build your credit. The disadvantage of an international debit card is that every time you use it in a foreign country, you will have to pay a conversion charge every time you swipe your card. In the case of a forex card, the conversion fee is charged only once. A good way to select a credit card for an international student is to check if it has 0% international transaction fees( In case, you need any amount from your home country, you will not be charged extra fees). If you plan to get a credit card, don't forget to set an alarm to pay your dues on time. This way you don't get charged an extra interest. Other factors to consider while selecting a credit card are the APR, rewards, cashback, annual fees, and minimum repayment per amount. Hope this article helps you to understand a little bit more about credit cards and good luck with your study abroad journey!! #creditcards #masters #ms #bachelors #phd #diploma #admissions #applicationprocess #universityselection #studyabroad #tipsandtricks #USA #creditcards

When to apply early and why it could be an added advantage for US universities?

Should you apply early in the 1st month of application acceptance? Know that the admission committee has to fill a particular quota of seats every year. From my observation, in the 1st month of application acceptance, the admission committee tends to be lenient. The number of applicants you are competing with at this time is generally less. A lot of universities will start your evaluation as soon as you complete the application process but they might give the application decisions later. The available grants for scholarships/funding also tend to not have been given out in the 1st month of application acceptance and hence your chances of getting a scholarship also remain higher. Applying early will not only show initiatives from the the student’s side but also prove that you have taken efforts to apply early. When not to apply early? If your recommenders are going to send the LORs after 15-20 days then wait to submit the application because the application won't go into admission review unless all parts of the application are submitted. You can use this time to improve your profile. Don’t apply early if your profile is going to be improving in the next few weeks or 1 month like a promotion that may be coming up or if your research paper is to be published. The factors that affect your chances (from highest to lowest weightage) for a tech degree are- Bachelor's CGPA/percentage, GRE, TOEFL score, Projects accomplished(profile of a student for the degree, competitions won if any, research work if any. Make your profile fit for a particular field like AI, cloud, security or any other field that you might be interested in. Let's say for instance you are interested in AI. 1. Start with python, learn Github (very important), upload your projects on github. A lot of people just upload the projects to GitHub and leave them. Do not do this. Make a front end for it and publish using GitHub pages or any other publishing tool. Have a github documentation. 3-4 published documented projects are better to show than 6-7 non-documented projects. 2. Compete in Kaggle competitions as much as possible. 3. Andrew Neg's AI Coursera certifications are good to gain knowledge, University of Washington AI specialization, Stanford ML, deep learning specialization by ‘deeplearning.ai’. It is not necessary to complete all of these. But it's good to have them on your resume and would help you gain knowledge in the fields of AI. Udemy has a few good courses also but I don't remember them. Start with Udemy and then move on to Coursera. 4. Write an AI research paper in a reputed institution like IEEE or Springer. Give paper conferences in IIT level institutions or better in the virtual conferences held in the USA via skype. USA universities look for research work in the profiles of applicants. 5. Complete at least 1 internship in the AI field in the summer. You will have to search for an internship at least 6 to 9 months early to avoid the competition. 6. For your final year project, an industry AI/ML project is better than an in-house project. You will get to solve real-world challenges. 7. Try to get as good grades as possible in data science, AI, and ML subjects. This will not only help you to get an admit in the AI field degree but also help you to get a TA or RA in the same field. You can follow similar steps for the fields you might be interested in. Lastly, applying early for your master's degree would be best. But if your profile is expected to be improved drastically in a month or 2, then waiting is also a good decision. DO NOT WAIT till December. You will face problems like lagging, document uploading problems, and slow email replies from the universities that would take more time. Applying early, in the 1st week of application acceptance, will not only increase your chances of getting funding but also increase the chances of getting an admit. Universities tend to be lenient at the start of application acceptance and not so much as you approach near the deadline. Hope it helps !!! Good luck !! #masters #applicationprocess #ProfileBuilding

18 mocks pack: 1. Manhattan GRE 6 tests 2. Kaplan 5 3. Princeton 4 4. ETS powerprep plus online 1,

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