Sunday, September 19, 2021

Everything that you need to know About John Hopkins Data Science Course in 2021

Introduction

To provide potential learners with knowledge of data science, Johns Hopkins University is offering various courses and programs. The courses are well structured and taught by experts in their fields.
The courses come with quizzes and projects to demonstrate skills. Thorough concepts of programming languages, data analyses, statistical inference, and Machine learning helps to boost expertise in data science.
Let’s get to know everything about Johns Hopkins Data Science courses.

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What is the John Hopkins Data Science Course?

Data science job roles are in huge demand due to the scarcity of people with the required skills. Thus, to resolve, Johns Hopkins University provides online courses to help people acquire requisite skills and knowledge of data science. The course is aimed to expand knowledge with Machine Learning, Game Theory, Large-Scales data systems, and Data Visualization to come up with advanced opportunities for upcoming data needs.
The course looks forward to preparing individuals for specialized tasks involving data storage, statistical analysis, and data mining to conclude profitable results from the data generated.

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Program options of John Hopkins Data Science

John Hopkins Data Science Master’s Program

The master’s degree at John Hopkins University is a diligent program that provides students with topics that cover both mathematics and computer science. The courses are available online to allow working individuals to acquire skills. The program aims to make students understand the theory as well as the real-world application of data science skills and tools.

Eligibility:

Applicants having a bachelor’s degree in technical streams like computer science, mathematics, engineering, statistics or more can apply. One semester of discrete mathematics, one of Java or Python, and three semesters of calculus are required. Undergraduates with a GPA of more than 3.0 need not take a standardized test.

Some prerequisite courses are Introduction to Python, Introduction to Programming Using Java, Data Structures, Discrete Mathematics, Introduction to Programming Using Python, General Applied Mathematics, Multivariable Calculus, and Complex Analysis, Introduction to Ordinary and Partial Differential Equations, Linear Algebra and Its Applications

Program Concentrations:

The main concentrations of the program are Computational Medicine, Computational Machine Learning, Language and Speech, Computer Vision, Statistical Theory, Mathematics of Data Science, and Computational Finance.

Fee:

The entire fee of the degree sums up to about $46,000.

Self-motivation of students is necessary if they pursue independent study. The program can be completed 100% online. Students may start the degree in Fall only.

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John Hopkins Data Science Coursera

John Hopkins in collaboration with Coursera is providing various data science courses and its approach towards other fields like biology, health care, and statistics. The duo has launched programs to help people gain practical skills in this field through project experience and theoretical knowledge. The course introduces an overview of data tools, tasks, programming languages, accessing and cleaning data, and making conclusions from the observation of data sets.

John Hopkins Data Science Specialization

The John Hopkins University is a major player in the data science field. With various courses and specialization, the university is promoting data science among passionate learners. The data science specialization is an initiative by the university along with Coursera to create more opportunities in the data world. The program is specifically designed to explain the terminologies, tasks, tools with video lectures, notes, projects, and quizzes. The specialization has a discussion forum where students can post their queries and views to discuss with other mates worldwide.

Let’s have a look at the program details in brief:

Program Duration:

As stated by Coursera, the course may take about 11 months to complete if 7 hours are dedicated per week.

Specialization fee:

The specialization comes with 7 days free trial and then approximately $48 per month. You can apply for financial aid. All you need to do is to fill up the requisite details in the form and wait until you get a confirmation notification.

Know the instructors:

  • Jeff Leek, PhD: He is an Assistant Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and co-editor of the Simply Statistics Blog.
  • Brian Caffo, PhD: He is a professor in the Department of Biostatistics at the Johns Hopkins University Bloomberg School of Public Health.
  • Roger D. Peng, PhD: He is a Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and a Co-Editor of the Simply Statistics blog.

The course provides potential learners with a good hold over the data science field. The topics covered through 10 courses in the specialization are:

  1. The Data Scientist’s Toolbox: The first course in the series gives a basic introduction to data science, installation of R and RStudio, version control, R markdown, and how to use Git and GitHub.
  2. R Programming: This course is all about R programming. Having previous knowledge of R programming is sought in this course as it doesn’t start from the basics. You are taught practical issues in statistical computing within R, reading and accessing data, debugging, writing and profiling R codes, and other working techniques.
  3. Getting and Cleaning Data: Loading data to transform for desired results. This course basically teaches data accessing and cleaning.
  4. Exploratory Data Analysis: This course explains all the techniques for summarizing data which helps transform data to conclude. It covers the plotting systems in R and the basics of constructing data graphics.
  5. Reproducible Research: This course covers Reproducible Research that involves presenting data in a well organized manner to make it easy to understand and more useful. The literate statistical tools are employed to publish data analyses in a single document that can be easily executed by others to obtain the same results.
  6. Statistical Inference: The course presents the practical approach to fundamentals of inference for getting tasks done. With this course, students will be able to reach conclusions and scientific facts from the analyzed data sets.
  7. Regression Models: This course deals with linear regression, multivariable regression, logistic regression, ANOVA and ANCOVA, residuals, diagnostics, variance inflation, and model selection.
  8. Practical Machine Learning: The course covers the basics of machine learning and predictions. The following topics are covered in the course- cross-validation, types of errors, tools for creating features and preprocessing, machine learning algorithms, cross-validation, regularized regression and combining predictors, data collection, feature creation, algorithms, and evaluation.
  9. Developing Data Products: The course covers statistical concepts of creating a data product through Shiny, R packages, and interactive graphics.
  10. Data Science Capstone: The last course of the specialization involves a project where you have to create a public data product that you can use to showcase your skills to probable employers.

John Hopkins Data Science Capstone Project

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The Capstone project is focused to build a public data product to deal with real world problems. You can access the Capstone project after completing all the previous courses in the specialization. The capstone project proves to be a true test of Data Analytics skills. In the project, you have to integrate data science knowledge and skills of programming, regression, mathematics, debugging, etc., that you learned throughout the course and demonstrate it through the project. It gives you more preference and experience while being hired as it is something which you can showcase to people from other fields that they can understand and use too.

John Hopkins University Data Science Ranking

The John Hopkins University makes it to the top each year worldwide. The university has secured ranks in 8 programs and 10+ specialties as reported by US News.

Also, the ranking on Coursera is substantial with 4.5 stars and 36,712 ratings. The course has a massive 428,717 overall students enrolled.

John Hopkins Data Science Undergraduate

Johns Hopkins Engineering for professionals online is a part time Data Science program for graduates that are specifically created for working professionals to expand their knowledge for better career opportunities. The program is meant to assess learners with theoretical as well as practical approaches towards applied mathematics and computer science to manage huge data sets.

Eligibility:

The eligibility requirements include skills like C++, Data Structures, Discrete Mathematics, Java, Linear Algebra or Differential Equations in place of Discrete Mathematics, Multivariate Calculus, and Python. A minimum of 3.0 GPA over the 4.0 scale.

Fee:

The tuition fee for the Data Science graduate degree is $52,170 per year. The Johns Hopkins University also provides financial aids to nearly 46% of its students.

John Hopkins Data Science Syllabus & Curriculum

The program mainly focuses on the theoretical and practical basis to upskill its students to perform intense data science related tasks. You can select from a plethora of courses ranging from applied mathematics to related data terminologies. Some of the courses are Principles of Database Systems, Introduction to Machine Learning, Data Visualization, Introduction to Optimization, Computational Statistics, Statistical Models and Regression, and Data Science.

John Hopkins Data Science Coursera

John Hopkins in collaboration with Coursera is providing various data science courses and its approach towards other fields like biology, health care, and statistics. The duo has launched programs to help people gain practical skills in this field through project experience and theoretical knowledge. The course introduces an overview of data tools, tasks, programming languages, accessing and cleaning data, and making conclusions from the observation of data sets.

Courses offered by John Hopkins University on Coursera

The university has brought some well articulated courses within the wide spectrum that includes the right from data science to biology. The listed courses somewhat deal with the data specific approach to problems with courses on data science, health equity, toxicology, and depression. The specialization includes Health Informatics, Patient Safety, Genomic Data Science, and other programs.

The top ten courses by Johns Hopkins as stated on Coursera are:

  1. Design and Interpretation of Clinical Trials: The course deals with analyzing clinical reports to test the efficiency of certain medications and the depth of diseases.
  2. Foundations of Health Equity Research: The course covers health equities research and the study of epidemiologies.
  3. Data – What It Is, What We Can Do With It: This course is an introduction to data. If you are someone who has to deal with data but does not know well about it, then this course can be very helpful.
  4. Implementing a Patient Safety or Quality Improvement Project (Patient Safety V): The course covers patient safety methods, the 4E model, and QI projects.
  5. Psychological First Aid: The course aims to teach people to give psychological first aid through the RAPID model: Reflective listening, Assessment of needs, Prioritization, Intervention, and Disposition.
  6. Fundamental Neuroscience for Neuroimaging: The course concentrates on neuroscience concepts and terminologies for a basic understanding of neuroimaging.
  7. Introduction to the Biology of Cancer: Worldwide, over 8 million people die of cancer each year. The course helps to make people understand the molecular biology behind cancer, the prevention, diagnosis, and treatment.
  8. Introduction to Genomic Technologies: The course is an introduction to the basics of genomic technologies and the tools that are employed.
  9. PrEParing: PrEP for Providers and Patients: The course teaches Pre-Exposure Prophylaxis (PrEP) which aims to reduce HIV, how to initiate a PrEP program, clinical management, and PrEP guidelines.
  10. The People, Power, and Pride of Public Health: The course focuses on the incredible accomplishments and promise of the public health field.

You may also like- Berkeley Data Science Masters: 9+ Most Important Things to Go Through before doing it

John Hopkins Data Science Reviews

  • Being one of the most registered data science courses, the Johns Hopkins data science course provides systematized explanations and tasks for better understanding.
  • With a price of $49 per course, the deal is pretty affordable and worth the skills delivered.
  • The average rating is 4.5 over 5 and the course is loaded with positive reviews as well as some negative ones.
  • Few courses covering R programming, extraction and cleaning, and exploratory analysis are fundamental to basic understanding.
  • However, some of the reviews suggest the course to be a little outdated with less mentoring to students. In this case, the long threads on the discussion forum are a savior.

Which is better? IBM data science professional certificate VS John Hopkins data science

IBM Data Science ProfessionalJohn Hopkins Data Science Specialization
Ratings4.6/54.5/5
Price$39/month (First 7days free trial)$49/month (First 7days free trial)
Duration
(According to Coursera)
10 months (If you spend 5h/week)11 months (If you spend 7h/week)
Best suited forComplete beginners with no previous knowledgePrevious knowledge of programming and algebra
No. of courses910
Programming language usedPythonR programming
ProsWell structured with a free IDE from IBM cloudWell organized content with interesting final projects for hands on experience.
ConsThe course starts from basics, so if you have previous knowledge then it might become a bit boringThe instructor has covered the Statistical Inference part in a very less time. Without previous knowledge of data science, the course may prove to be difficult.
YouTube video

John Hopkins Data Science Acceptance Rate

Being one of the top ranked universities the competition is high at the JHU. With an acceptance rate of about 12%, it is particularly difficult to get admission into the Johns Hopkins data science program. The admission process gives preference to high grades and overall professional background in the two selection phases.

Conclusion

A data science course can act as a foundation for your career. The efficient courses provide a thorough knowledge of basic terminologies and tasks. The courses come with a project which you can show on your resume.
If you learn well, then a data science course can help in the long run.

FAQs

Can I take the Coursera course for free?

Yes, you can avail the full course for free but you won’t get a certification. You can audit the course to learn or apply for financial aid.

Is there any financial aid available?

You can apply for financial aid which is on the website. You will be asked to add reasons about your application and how this program will be helping you. Stay true, write the application in a good manner. As soon as the application is passed you will get full access to quizzes and certificates as well.

Is this course 100% online?

The Coursera course is 100% online. And, the course offered by the Johns Hopkins University is hybrid, the learner can choose either online, on-site, or a hybrid mode of learning.

What is the duration of the data science specialization course online?

The specialization course is for 11 months though you will be able to complete it in 3-6 months if spent 10+ hours per week.

Will I get a certificate after completing this course?

After completing every course, you will earn a certificate for each and a specialization certificate at full completion.

Is John Hopkins data science course worth it?

It is the largest registered data science program in the world. The course has world class offering of resources and knowledge. So, it is worth a take.

Everything that you need to know About John Hopkins Data Science Course in 2021

"I make chemistry with words and chemicals"Hey! I am Radhika Mishra, a chemistry enthusiast, and a freelance content writer. I love writing and have been working on regular projects with websites, blogs, and startups. I also help entrepreneurs with LinkedIn branding and optimizing their profiles. Thanks for reading!

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Everything that you need to know About John Hopkins Data Science Course in 2021

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"I make chemistry with words and chemicals"Hey! I am Radhika Mishra, a chemistry enthusiast, and a freelance content writer. I love writing and have been working on regular projects with websites, blogs, and startups. I also help entrepreneurs with LinkedIn branding and optimizing their profiles. Thanks for reading!