Monday, November 22, 2021

Coursera Certification Review - Is Data Science Specialization from John Hopkins worth it in 2022?

Hello guys, if you are thinking of joining Data Science Specialization at John Hopkins University in Coursera but thinking about whether it's worth your time and money or not, then you have come to the right place. Earlier, I have shared the best Coursera courses for Data ScienceCloud ComputingMachine Learning, Python Programming, and today, I will review one of the most popular Data Science specializations on Coursera, Data Science Specialization by John Hopkins University. While Coursera has many top-quality Data Science certifications, this is probably the most popular of them given its offered by the Johns Hopkins University of the USA. 
Nowadays, data is the fuel of this age, and companies are always developing tools that can extract insight from this data to make the right decisions and understand the market as well as the user's needs and learning how to use this data and take advantage of is not a hard task to understand.

Many instructors have created online courses teaching you how to use data to get insight into what’s known as data science. I’ve been searching in many online platforms until I saw this Data Science Specialization at Coursera offered by John Hopkins University.

You will see in this article what you will learn in this data science specialization, the instructor's reputation, and the people's review so you can make the right decision to take this course or search for another one that fulfills your needs.

The good thing about this course is that it's a specialization that means you will earn a Coursera certificate that you can add to your resume and LinkedIn profile to showcase that you have completed this specialization in Coursera and have relevant Data Science skills. This will really boost your profile as a recruiter search with keywords and prefer candidates with evidence like certifications. 





Review of  Data Science Specialization by Johns Hopkins University Certification

Now, let's start to find out whether Data Science Specialization by Johns Hopkins University on Coursera is the right course to learn Data Science in 2022 or not. We'll review the course on important parameters like Instructor, course content, and what other people who have already taken this course think about this specialization. 

1. The Instructors Reputation

The course is created by three instructors, and let’s start with Jeff Leek who is an assistant professor at John Hopkins University in biostatistics specialization and has a Ph.D. in this field.

Another instructor is called Roger D. Peng and has a Ph.D. in statistics from California university and works as a professor at John Hopkins University.

The last instructor, Brian Caffo, is a professor at John Hopkins University and a Ph.D. holder from the University of Florida in the biostatistics specialization. 


2. The Specialization Content

This data science specialization focuses mainly on using the R programming language to analyze and visualize the data and create machine learning models. So let’s start exploring the content of this course: 


2.1. The Data Scientist’s Toolbox

Every trade has its tools and Data Science is no exception. You need tools to extract data, cleanse data, normalize data, and transform data. You also need tools to visualize and play with the data and that's where this course helps. Since you are new to the data science field, you will get an introduction to this industry and some tools and platforms that will help you master data science.

 

2.2. R Programming

The second one focuses on programming using the R Programming language since it is the main one to do analysis and visualization in this course and install the environment and packages for statistical programming.  If you want to master the R language, you can also check out my list of best R programming courses which include the best courses from Udemy, Pluralsight, and Coursera to learn R programming. 


2.3. Getting and Cleaning Data

Before you can do your job as a data scientist, you need first to obtain and collect the data, so this course will introduce you to the various ways to get data from databases and the web, and more. 


2.4. Exploratory Data Analysis

After you collect the data, you need to process it and visualize it, which is all about in this course. You will learn the statistical and visualization packages available in the R language.

 

2.5. Reproducible Research

This course focuses on reporting and getting insight into your data after the visualization and analysis process and some other stuff to make the analysis process more effective and productive.

2.6. Statistical Inference

This course will introduce you to statistics and inference statistics, which is the process of drawing the conclusion of a population and some theories such as Bayesian and likelihood.

2.7. Regression Models

This course is toward statistical analysis and regression models such as linear and regression models, so it is an introduction to machine learning and regression analysis. 


2.8. Practical Machine Learning

Here, it comes to the fun part where you will apply machine learning algorithms to your data and prediction functions and some ML concepts such as training overfitting and more. 


2.9. Developing Data Products

This course is all about creating data products using the R language and some packages such as shiny and leaflets, and you will learn some visualization using the Plotly library. Data Visualization is a key skill and that's what you will learn in this course. All the information you have collected from Data Analysis is useless unless you can find some insights and that's where these charts and other visual elements help. I strongly suggest all the Data Scientist aspirants learn Data Visualization. \

2.10. Data Science Capstone

In the last course, you will do a capstone project where you will develop a data product using what you have learned in the past courses as well as analyze your data and make predictions, and more.  This is a really great opportunity to apply whatever you have learned so far in this course and this is also important to get the certification you are eyeing for. Unless you complete the project and all the assessments, you will not get the certification, but don't worry, there is plenty of help available online, in forums, and on youtube to complete the project. 


3. The People Review

The specialization gets 4.5 stars out of 5 from around 78k who submitted their rating, which seems pretty good and means the content itself is also good and the videos and quizzes.

It also has more than 350k enrollment and forgets to mention that the course is available in many languages such as Chines and Arabic and Spanish, Russian, and more, and the statistics show that 43% of the learners have started a new career in data science. Around 19% has got promotion after completing this specialization. 

And, here is the link to join this course - Data Science Specialization by Johns Hopkins.

Coursera Specialization Review - Data Science Specialization by Johns Hopkins University


That's all about the Data Science Specialization by Johns Hopkins University. Data science nowadays is a high in-demand industry that becomes almost mandatory for any company to hire an employee who can take advantage of their data to make the right decision and improve their services and compete with others in the market.

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Thanks for reading this article. If you like this review of Data Science Specialization by Johns Hopkins University on Coursera, please share it with your friends and colleagues. If you have any questions or feedback, then please drop a note.

P. S. - And, If you are looking for the best Udemy online courses to learn Data Science with Python, you can also check out The Data Science Courser 2022: Complete Data Science Bootcamp by 365 Careers and his teamThey have the best data science online courses on Udemy. 

1 comment:

  1. What are the chances of getting into the industry with that.

    ReplyDelete

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