Scaler vs UpGrad – Data Science Course Comparison

Scaler and UpGrad are among the top-notch edtech brand names in the data science course domain. You’re not alone if you’re stuck between these two courses. Thousands of our readers and students have urged us to compare these two organizations and their data science programs. 

We will be reviewing their top-selling Course in data science and will be comparing the basis of the following parameters:

1. Founders: Promoters and Founders social status greatly determine the efficacy and trustworthiness of a course. 

2. Course Duration: For both Scaler and UpGrad, we have selected only the Course with a minimum duration of 6 months. We believe that a minimum of 6 months is required to master a data science career.

3. Mode of Training: In recent years, learners’ dropout rates from online courses have reached 80%. That’s why we have emphasized more on a blended mode of learning that includes live online/classroom classes, pre-recorded sessions, assignments, and industrial training. 

4. Program Fee: When a learner enrols in a course, he not only puts in his personal efforts but also needs to pay a hefty amount of money in the form of a fee. We at Analytics Jobs will emphasize more on a course that guarantees a higher return on investment. This ROI is more crucial if you’re a working professional. Taking time from your professional and family commitments and pursuing these courses takes a lot of toll on you. So, the Course needs to have a properly defined and guaranteed ROI on your hard work and hard-earned money.

5. Course Curriculum: The curriculum is the most crucial part of a data science course or program. The course curriculum needs to be comprehensive. Make a list of all the tools that are required for a data science job from Naukri.com or Indeed.com. Look into a particular course curriculum and see if you’re being taught the skills that are required for a specific data science job. You also need to check the content depth and how much practicality and industry relevancy are being taught to you. Mere theory will not work; exposure to complex problems related to a particular topic will hone your skills that are much needed for a data science job. So, the course curriculum needs to cover both fundamental concepts and advanced techniques in the data science domain. Ask these questions to your counsellor like : tools taught, total number of live sessions and their duration, total hours of pre-recorded content, number of industry projects, capstone projects and various other crucial factors before deciding on a particular course. 

6. Query Resolution: For a working professional, query resolution after enrolling in a data science progrm is crucial. This is very important. Let’s say you are a working professional. Obviously, you will be devoting time to the Course after your working hours. Now, let’s say, you’re going through a particular topic and got stuck. Time is 11 hours in the night. Ask your counsellor this question: Who will help me in this case? Discussion forums should be there, or a mentor should be available to look into your query. The ticketing system for query resolutions also needs to be there with property query resolution turn around time (TAT).

7. Student-Faculty Ratio: Stay aware of the false claims by these institutions. We have seen multiple batches wherein there are more than 500 learners. While deciding on a course comparison between Scaler Academy and UpGrad, ask your counsellor categorically about the following: 

• Total number of learners in your batch. 

• Student-faculty ratio

• Can you switch on your mic during a live class or session?

8. Industry Projects: Keep a close Eye on the number of industry projects in the course content.  An Industry project is a practical transformation of theoretical knowledge you have received in your classes. They are immersive with a real corporate environments wherein learners apply theoretical knowledge to real-world business problems. In data science, an exclusive data set for a particular business or industrial problem is the key. Ensure your Course provides real-world industry large amounts of data sets to work upon in your industrial projects. 

9. Capstone project: To further augment your skills and what you have learned in your classroom, at least 1 capstone project is a must. An Organization should sponsor an ideal Capstone Project. These organizations could be commercial, non-profit, government, or academic. These organizations seek solutions to a particular problem in their organization, seeking recommendations to solve a particular strategic and operational problem statement. Now, based on organization needs, teams need to develop web-based applications that can solve that particular problem statement. A typical Capstone project concludes with a team presentation.

The idea behind the capstone project is to empower students to acquire and analyze data sets to solve real-world problems. A typical capstone project team should have up to five members and a faculty member. If you’re a fresher in the data science domain, most of the questions in your job interview will be based on the Capstone Project only.

10. Internship: Trust us, whatever concepts you learn in your class differs significantly in a real work environment. A small example can vet this. In almost all the courses, you will be working on Jupiter environment. But ask any data science professionals; companies don’t use Jupiter in the workplace. This is where an internship can be the key to learning the concepts while working in a real-life environment. That’s why Analytics JObs always ranks those courses in their list that have added Internships as the core part of their curriculum. 

11. Final Placements: Less than 1% of the workforce takes a course in data science only for UpSkilling. 99% enrol in a data science course either to transition to a higher pay grade or to get their new job. What is your take?

Whatever your motive behind enrolling in a data science course or program, you need to be more concerned about the Course’s last batch placements or career transitions report. Vehemently ask for this report from your counsellor and connect with individuals on LinkedIn who have got jobs or career transitions after completing a particular course. 

12. Analytics Jobs Reviews: Check out the Course reviews on India’s first and only Questions and Answers format discussion forum for course reviews. You will find genuine and up-to-date reviews, ratings and feedback only at Analytics jobs.