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We all know that data science is a hot topic and worth pursuing in long term, large businesses use data science to increase revenue while small businesses use data science to scale up. So data science is a must need for any business, and that technology is changing rapidly. But our traditional schooling systems haven’t identified the importance of data science yet, so normal schooling might not be sufficient to be a market-ready data scientist. This is where MOOC(Massive Online Open Courses) and distant education programs come into play.
There are thousands of online courses made on this topic and almost all of them are oversubscribed, even the worst ones taught by novice data scientists are oversubscribed. Since there is a sea of different courses available it will be tremendously difficult to find the right course for you.
Here in this article let’s compare the pros and cons of two famous online programs for data science, they are the Great Lakes PGP in Data Science And Engineering and The Master Of Applied Data Science by the University of Michigan School of Information. As an addon, we will also discuss how to select the best data science course and the things that should be considered while enrolling for a data science online course. So that you can save your money by avoiding an accidental enrolment in a wrong or bad course, as a token of gratitude we request you to kindly share this article with your friends so that they can also learn these beautiful skills.
If you are a beginner in data science our blogs will help you acquire more knowledge. we have written blogs on best courses on data science, best books to learn data science, the difference between data science and machine learning, etc. do check them here.
Which Is Better Great Lakes Or UMSI?
Well, the question that we are going to answer is highly subjective and will vary from person to person but here we will analyze the curriculum, fee structure, and other key points like details on the instructor, .etc so that after reading this article completely you can come to your own conclusion.
Great Lakes PG Program In Data Science And Business Analytics
Great lakes institute of management in collaboration with the University of Texas at Austin. They offer two post-graduate programs one in which data science and business analytics are taught and in the other data science engineering is taught.
The program uniquely combines a comprehensive curriculum, covering the most widely-used tools
and techniques in the industry, with a hands-on learning approach. A structured learning journey
keeps you on track throughout as you achieve your weekly learning milestones with your mentor
and benefit from their rich professional experience.
Master Of Applied Data Science At University Of Munich School Of Information
The University of Michigan School of Information is offering a fully online master’s program in applied data science. They teach comprehensive applied data science at the intersection of people and technology. They provide critical insight into data collection, computation, and analytics, then teach you how to present the information and solutions you find. You’ll develop hands-on skills using a multidisciplinary approach embedded in information, computer science, and statistics.
Basic Details About The Three PG Programs In Data Science
|PG Program In Data Science And Business Analytics By Great Lakes||PG Program In Data Science Engineering By Great Lakes||Master Of Applied Data Science By UMSI|
|Course Duration||6months||9months||The program can be completed in 1 to 3 years depending on how many credits take per month. For Part-time candidates who learn while working the course duration will be 2 years to 3 years, while for full-time students the course can be completed in 1 year.|
|Mode Of Teaching||Online Pre-Recorded Videos + Interactive Mentored Learning||Live Online Classes Twice A Week + Online Lab Session On Weekends||The program uses both synchronous and asynchronous instruction with weekly synchronous sessions using a virtual classroom|
|Time Commitment||5-7 Hours A Week (Highly Dependent)||8hrs/week(4hrs for live sessions + 4hrs for lab sessions on weekends)||Full Time-6hrs Daily & Part Time-5-10 hrs Weekly|
|Hands On Projects||YES(8 Numbers)||YES(Numbers Unspecified, Applicants can take up a 4-week application-based hands-on capstone project to apply their learning to real-life business problems.)||YES(3 Numbers)|
|Number Of Modules||12||3||33|
|Skill That Will Be Taught||Python, SQL, Tableau, Predictive Modeling, Data Mining, And Machine Learning||Computational skill for big data, python, data visualization using multiple methods, Analytic techniques like machine learning, network analysis, natural language processing, experiment design and analysis, causal inference, etc, Data science application in a context like a search and recommender systems, social media analytics, learning analytics, etc.||Math Methods for Data Science, Data Science Ethics, Data Manipulation, SQL And Databases, Efficient Data Processing, Big Data: Scalable Data Processing, Visual Exploration of Data, Communicating Data Science Results, Data Mining, Supervised and Unsupervised learning, Database Architecture, Deep learning, and many more.|
|Type Of Candidates Who Enroll For This Course||The Majority Of The Learners Are Employees With 5-12 Years Of Experience||The Majority Of The Learners Are Students And Employees With 0-5 Years Of Experience||The Majority Of The Learners Are Employees Who Are Looking For A Career Upgrade.|
|Fees||Fees USD 3500 (Flexible Fee Structure For More Details Visit)||Fees USD 4500 (Flexible Fee Structure For More Details Visit)||USD $31,688 + fees (in-state); $42,262 + fees (out-of-state)|
|Remarks||Self Paced Course||Placement Assistance||Career Development, Scholarships & Financial Aids|
|Faculty Details||Dr. Kumar Muthuraman|
Faculty Director, Center for Research and
Analytics, McCombs School of Business, The
University of Texas at Austin. H. Timothy (Tim)
Harkins Centennial Professor. MS & Ph.D.
Dr. Dan Mitchell
Assistant Professor, McCombs School of Business
Ph.D., The University of Texas at Austin.
Dr. Abhinanda Sarkar
Academic Director, Great Learning
Ph.D., Stanford University
Industry Expert in Visualization
MBA, Whitman School of Management
Industry Expert in Visualization
MBA, Monash University
|DR. NARAYANA DARAPANENI|
Professor, Artificial Intelligence & Machine Learning, Great Learning
Ph.D (Pierre & Marie Curie University, Paris)
DR. MUDIT KULSHRESHTA
Professor, Great Lakes Institute of Management
MR. R VIVEKANAND
Operations Director, Wilson Consulting Private Limited
MBA (Monash University)
MR. GURUMOORTHY PATTABIRAMAN
Faculty, Data Science & Machine Learning, Great Learning
M.Sc (Madras School of Economics)
DR. SRABASHI BASU
Professor, Business Analytics, Great Lakes Institute of Management
Ph.D. (Penn State University)
|Paul Resnick. |
Michael D Cohen Collegiate Professor of Information, Associate Dean for Research and Faculty Affairs, and Professor of Information.
Assistant Professor of Information, School of Information
Lecturer III in Information, School of Information
*There Are Many Other Qualified Faculties But Since The Number Of Modules Are High And All Modules Are Covered By Individual Faculties It Is Impossible To List Them All. How Ever You Can Always Refer To UMSI Official Website Directory To Read About All The Faculties HERE
For more information on great lakes courses and procedure for application click here.
For more information on UMSI courses and procedure for application click here
How To Select The Best Online Course To Learn Data Science?
As we have already discussed market is flooded with data science courses, So spent some time doing some research on what you are going to learn and make sure that everything that you learn from the course is fundamentally true and is updated with current technology, reviews by other users will help you here. Since this involves your time and money make sure that it will completely be worth it for you.
Following are the key points that should be kept in mind when you enroll for a course
Be Sure About What You Want To Learn
As we all know data science is an interdisciplinary field where maths science business and communication coincides. Within data science itself, there are many categorizations like business analyst, machine learning engineer, data architect, data engineer, .etc. There are individual courses for each and every one of them make sure that you are learning what you want to learn.
Understand And Be Honest With Skills That You Have Now
Analyze and spent time to understand your strengths and weakness, validate your skillset and improve your existing skill. When You get into the race it’s mandatory that you should have a mindset to learn new things daily. For you to be industry-ready make sure that your skills are sharp and up to date with the market needs.
Before you become a data analyst be a self analyst first.
Do The Research About The Online Course That You Are Going To Enroll
After doing the first and second steps that I mentioned above you can now open your laptop and search for data science online courses and tons of search results will be shown within a matter of microseconds. Use your mental filters and search engine filters to find out the courses that teach what you are looking for.
Make sure that you are seeing only what you want to see. Web results are prone to paid ads and SEO works are wise to select only what you need.
Possible things that you can do while doing research about the course are as follows
Who Is Teaching You?
Who teaches you is the monumental question that you need to find an answer to first. The quality of the course solely depends on who presents it, so make sure to do thorough research here. Make sure that the instructor is qualified enough to teach the topic. Do some research on his career, previous courses, and their feedbacks, years of experience in the field, years of experience in teaching, social media profiles, funnels, etc.
Read The Alumni Reviews Before Enrolling
Alumni reviews are very helpful but sometimes it will be showing fake reviews or paid reviews which are inorganic and are done by cunning corporates to improve SEO. It’s better to stay away from these types of courses. Use filters to find good reviews. Not all courses are 100% perfect so read the reviews and understand the pros and cons of that course.
Make Sure That You Learn Updated syllabus
Do some research to know about the current situation of your target market. Make sure that the course curriculum is designed to meet those market needs and timely update is done by the same instructor on new and emerging technologies. Since almost all online courses are having lifetime validity and this area of technology is undergoing rapid changes this step is so vital.
Real-Life Examples And Hands-On Experiments
Make sure that the instructor has included enough real-life examples and hands-on teachings so that the classes will be more easily understandable and the idea of the tutor will be easily conveyed to the student.
Here we have seen the differences between two major online Master’s courses offered by renowned universities in the world. We have discussed their fee structure, curriculum, and faculty details. As we have seen it is impossible to say one is better than the other since both are handling different domains in data science. All that they have in common is both are courses that can be pursues only after graduation.
Since your choices are subjected to many factors like budget, accessibility, placements, etc take a wise decision by considering the points that we have discussed here and your individual logic. Also, let us know what you decide through the comment section of the article.