About Coursera
Before reviewing Coursera Data Science program, let us talk about the history of Coursera. Professors of computer science at Stanford University, Daphne Koller, and Andrew Ng, founded Coursera in 2012. In the fall of 2011, Ng and Koller began making their Stanford courses available online. Shortly after, they departed Stanford to found Coursera. The first colleges to offer content on the platform were Princeton, Stanford, the University of Michigan, and the University of Pennsylvania. Coursera works with universities & other organizations to offer online courses, certifications, and degrees in a variety of subjects. In 2021 it was estimated that about 150 universities offered more than 4,000 courses through Coursera.
The Headquarters of Coursera are in California, United States. Coursera provided 104 on-demand courses as of May 2015. Additionally, they offer small, 2-3 hour guided tasks that students can complete at home. The certification that you get after completing the courses is valid all across the globe.
Now let’s talk about Coursera Data Science Specialization Track and its most sought-after features.
Here are some of the key features of the Coursera Data Science course:
- On completion of the course, you’ll be awarded a certificate.
- The course is completely online.
- You can make your schedule according to your convenience.
- The course is taught in English with subtitles in various languages.
- The course fee is approximately Rs. 32,000 which is quite affordable.
NOTE: STUDENTS ARE REQUIRED TO HAVE BASIC KNOWLEDGE OF R PROGRAMMING BEFORE JOINING THE COURSE.
Coming back to the Coursera Data Science Specialization: It consists of 10 courses. Here’s a brief overview of all these courses:
- Data scientist’s toolbox: As the name suggests this course is an introduction to all the tools and ideas a data scientist must be equipped with.
- R programming: This course teaches the students how to program in R and how to use it for data analysis.
- Getting and Cleaning Data: This course teaches the students all the components of a data set and how to obtain, clean, and share data.
- Exploratory Data Analysis: This course teaches the students all about plotting systems in R language, and basic principles of constructing data graphics.
- Reproducible Research: In this course, students are taught how to use statistical analysis tools to publish data analyses in a single document.
- Statistical Inference: This course teaches students how to use broad directions of statistical inference to make informed choices in data analysis.
- Regression Models: This course covers topics like ANOVA and ANCOVA and analysis of residuals and variability.
- Practical Machine Learning: In this course, students are taught model-based and algorithmic machine learning methods and building prediction functions.
- Developing Data Products: This course covers the basics of creating data products using Shine, interactive graphics, and R packages.
- Coursera Data Science Capstone project: This is the final course that focuses on the practical application of all the skills learned in the previous courses to create a usable, public data product.
Eligibility Criteria
There are no specified requirements for eligibility. Even if your background is non-technical, you are still very much eligible for the course. However, if you come from a technical background, it will give you an advantage because others without that background would need to put in more time and effort to learn the fundamentals first.
It’s time to get a picture of the Syllabus of the Program
In the syllabus, they cover Data Science through a comprehensive course curriculum encompassing essential topics like statistics, data visualization, machine learning, SQL, R, and Python with a Capstone project at the end.
Then you can choose one out of 2 of their electives which are;
- Data Science With R
- Deep Learning With Tensorflow And Keras
The Skills that they cover are:
- Multivariate Calculus
- Probability and Statistics
- Database Management
- Data Visualization
- Data Storytelling
- Linear and Logistic Regression
- Clustering
- Hypothesis Testing and Estimation
- Data Wrangling
- Supervised and Unsupervised Learning
- Time Series Modeling
- Ensemble Learning
- Neural networks
- Deep Learning
Placement
Placement is where all of our focus is. After all, that’s what all of you look forward to, and with good reasons. Coursera claims that they have 275+ Hiring Partners where they get their learners an average hike of 55%. Wait it doesn’t end there, They claim that their maximum salary hike is 85%. That’s a biggie!!. However, after going through several reviews online. We have mixed opinions on it.
Admission Fee
Now let me tell you the fee for this program; Coursera Data Science program fee is ₹ 2,50,000 (incl. taxes).
Which honestly to me feels like a little too expensive compared to their own programs in the same domain. I guess the Job Guarantee pulled the fees a little high. But that being said, let’s look at the most important section, Reviews from Learners and Alumni.
Reviews:
Learners have a lot to say about the program reviews that they have written. Some are quite bad, while others are good. We looked at multiple review platforms including our own:
Is Coursera IBM data science course any good?
We examined a number of review sites, including our own; Regarding the query,
Coursera Data Science course review based on different professional platforms:
- Mouth Shut
- Trust Pilot
- Site Jabber
Coursera Data Science course review Mouth Shut
Coursera Data Science course review is quiet good in MouthShut and it has managed to gain an overall rating of 4.14 which is a good rating out of a total of 392 Votes. As per the students review the Coursera Data Science course’s services and support rating is 4 out of 5. When it comes to Coursera Data Science course Administration, students have given 4 rating out of 5. Parameters like Students Engagement, Value for Money and Time to load have managed to gain a rating of 4 out 5.
Coursera Data Science course review Trust Pilot
Coursera Data Science course review on Trust Pilot is average as the rating is 3.3 out of 5 and the total number of reviews are 26. Reviewers of Trust Pilot have a mixed feeling when it comes to Coursera Data Science course, however, as the numbers of reviews are not that high so considering just this review would not be a good option for any data science aspirant.
Coursera Data Science course review Site Jabber
If we talk about Coursera Data Science course review on Site Jabber, it is a complete negative review as the reviewers have rated Coursera Data Science course with a rating of 2 out of 5 which is bad rating. If we see the number of reviews, it is 73 which is still a good number, so it is clear that audiences of Site Jabber dislike the Coursera Data Science course.
Conclusion
In conclusion, I would say that the Placement Guarantee and 100% return in the event that you don’t find employment within 180 days make the Coursera Data Science Specialization Track Program appear promising. Although it has a few partnerships with some of the best institutions, I truly felt that the fee is a little expensive.
Note: To know about reviews of other Data Science institutes you can Check the Data Science, Artificial Intelligence, Analytics Course Reviews.
