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You’re here because you’ve heard about the IBM Data Science Professional Certificate but you’re still unsure of one thing: is the IBM Data Science Professional Certificate worth it?

Is the IBM Data Science Professional Certificate Worth it?

I’ve done some research and here’s a short answer:

The IBM Data Science Professional Certificate is worth it. Perfect for beginners, the certificate is worth buying for its 143 hours of in-depth content, strong focus on Python applications, and data projects, at only a cost of USD $39/month. However, the IBM Data Science Certificate is unsuitable for advanced learners.

ibm data science professional certificate review

And here are the 7 reasons why this certificate is worth it:

7 Reasons Why The IBM Data Science Professional Certificate Is Worth It

Read on for more details on each reason below:

1. Wide Exposure to Data Science Skills

You’re likely looking for a certificate that will set you up to pick up all the necessary skillsets of a data scientist.

And that’s what the IBM Certificate is perfect for!

Throughout the 10 courses in this certificate, you’ll pick up real data science tools like these:

I’m sure you’ll agree that this is a long list!

Many of these technologies are common among data scientists and based on my own experience and work in data science, I agree that these are essential tools for anyone getting into data science.

With exposure to such a wide variety of data science tools, you’ll be introduced to the right tools targeted for a data science career.

Data scientist jobs tend to require a large skillset of prior knowledge on such tools, so this extensive list is pretty impressive!

Because this certificate is made by IBM, it also includes proprietary software like IBM Watson Studio. I’d have to disagree that this is a common tool used by data scientists.

However, this shouldn’t affect your decision in taking up the IBM Certificate!

You should see IBM Watson Studio as an additional tool that you can pick up to stand out from other data science job applicants!

This is a much longer list of skills compared to the shorter Google Data Analytics Professional Certificate.

Because of its shorter program, the Google certificate focuses on other skills like R and Tableau whereas the IBM Data Science Certification focuses on Python and its various applications!

You can check out my article on the Google Data Analytics Professional Certificate here if you’d like to read more!

2. Optimal Learning Stress Environment

Learning from online certificates can be tough, especially if you need that extra push to achieve your goal of completing the certification program.

According to this study, learning comes best when you’re having an optimal stress environment!

Eustress, also known as positive stress can help you learn better and faster when picking up new knowledge!

Have a look at the middle section of this diagram below:

This is where the IBM Data Science Professional Certificate is perfect for you!

The certificate has some factors that would help give you that added motivation to keep you going.

Here’s a list of those factors:

  • Email reminders from Coursera to keep pace with the learning schedule
  • A monthly subscription model
  • Well-structured content with a moderate pace of delivery
  • Peer-reviewed projects
  • Course Exams

Let me explain how these create an optimal learning stress environment.

Weekly email reminders from Coursera provide gentle reminders for you to stay on track. This helps you keep to the recommended schedule so you won’t fall behind!

This is why I’m glad that the IBM Certificate is hosted on Coursera’s platform.

Monthly subscription models are used for the IBM Certificate at USD $39/month.

This means that you’ll have a slight pressure to make your money worth and complete the certificate with lesser procrastination.

Based on my personal experience with this, I can safely say this was a major motivator in my learning!

Peer-reviewed projects are included in this certificate. This means that you’ll really have to use all your learned data science knowledge and apply that to a project.

Because of the peer-review aspect of the projects, this puts an optimal level of positive stress on you to ensure good work is submitted.

Nonsense submissions typically get rejected by peers so you’ll really need to push through with learning the right way!

Course exams are a part of every course in the IBM Certificate. At the end of each course, you’ll encounter a final exam covering all the content from that course.

Much like traditional exams, these exams are great to test your book knowledge of basic concepts in data science.

Moreover, these exams have a cooldown of 8 hours after each attempt. This means that you can only reattempt an exam 8 hours after failing.

There are unlimited attempts for each exam so stress is still kept optimal!

This should put you in a positive stress environment, where your exams have minor consequences but aren’t too large altogether.

This is why Coursera is one of my favorite platforms for learning because I tend to procrastinate a lot!

In fact, in my list of the best data analytics certificates, many of them are hosted on Coursera.

. Strong Focus on Python Applications

If you’re attempting the IBM Data Science course, you’re likely someone who’s new to data science.

You’ll be happy to know that this certificate has a really strong focus on Python and its varied applications!

According to the 2021 Kaggle Machine Learning & Data Science Survey, Python is the top language you should learn when starting out in data science.

Python is the go-to language among data science professionals for analyzing data and running common machine learning algorithms.

Here’s a table showing the number of hours of Python learning content in the certificate:

IBM Data Science Professional Certificate Python Learning Content Hours by Course

CourseHours of Python Learning Content
1What is Data Science?
2Tools for Data Science~55 minutes
3Data Science Methodology
4Python for Data Science, AI & Development22 hours
5Python Project for Data Science7-10 hours
6Databases and SQL for Data Science with Python11 hours
7Data Analysis with Python13 hours
8Data Visualization with Python18 hours
9Machine Learning with Python23 hours
10Applied Data Science Capstone12 hours+
Total106 hours, 55 minutes

You’ll have a good 100+ hours of Python learning content by the end of this certificate!

After 100+ hours of exposure, I’m sure you’ll be confident enough to approach most data science problems in Python!

Python is a great language to start with simply because of its versatility and ease of use in many different applications.

Here’s an article I wrote about the uses of Python in healthcare if you’re curious to learn more!

In comparison to the R programming language, another language used commonly in data science, Python is far more popular because of its machine learning and artificial intelligence libraries.

Moreover, most APIs can only be accessed by Python instead of R, which makes a big difference when working with external data. Python’s Pandas data frames also make it easy to analyze data!

Python is used more than R in Data Science because of its large community of existing users and simpler syntax compared to R. Python is also a general-purpose programming language, making it more versatile. These advantages lowered the barrier to entry for beginners learning Python and lead to it being used more than R.

You can read more on this in my article over here.

4. Rigorous Relevant Content

Content quality is a major factor that you’ll have to consider when selecting an online certificate.

Here’s why this IBM Data Science Professional Certificate gives you rigorous and relevant content:

The IBM Data Science Professional Certificate has over 143 hours of course content and 18 hours of video content!

Rigorous Content

Just take a look at this breakdown by hours below:

Breakdown of IBM Data Science Professional Certificate Course Content by Hours

Course NameApprox. Total Time to CompleteVideo Lecture Time
1What is Data Science?10 hours1 hour & 38 minutes
2Tools for Data Science19 hours3 hours & 30 minutes
3Data Science Methodology8 hours51 minutes
4Python for Data Science, AI & Development22 hours2 hours & 17 minutes
5Python Project for Data Science7-10 hours10 minutes
6Databases and SQL for Data Science with Python11 hours2 hours & 16 minutes
7Data Analysis with Python13 hours1 hour & 47 minutes
8Data Visualization with Python18 hours1 hour & 25 minutes
9Machine Learning with Python23 hours3 hours & 56 minutes
10Applied Data Science Capstone12 hours23 minutes
Total143 hours18 hours & 13 minutes

That’s a lot of online content to go through for a certificate so I’m confident it will make your money’s worth!

Just by taking a look at the 18 hours+ of video content, I can already tell that the content is going to be heavy since my college modules were only at a maximum of 40 hours.

Not to worry, though!

The IBM Data Science Professional Certificate is a fully-online program and can be completed over a long period of time, with no fixed schedules. I’ll cover this in reason #5 later on!

With such long hours of content to go through, things can get pretty dry but the IBM certificate does have some varied content types to keep you engaged.

Here’s a list of the content types in the IBM Data Science Professional Certificate:

  • Labs
  • Peer-reviewed assessments
  • Practice exercises
  • Quizzes
  • Exams

Relevant Content

This certificate also covers all steps in the data science process used by a typical data analyst.

Here’s how the data science process usually goes:

  1. Data collection
  2. Data cleaning
  3. Exploratory data analysis
  4. Model building
  5. Model deployment
Data science life cycle. (Drawn by Chanin Nantasenamat in collaboration with Ken Jee) Source

The IBM Data Science Professional Certificate covers all parts of this process through the use of Python.

Have a look at the table below:

Step in the Data Science ProcessWhich Courses Cover These Steps?
1Data collectionPython for Data Science, AI & Development
2Data cleaningPython for Data Science, AI & Development
3Exploratory data analysisPython Project for Data Science;
Data Analysis with Python;
Data Visualization with Python
4Model buildingMachine Learning with Python
5Model deploymentMachine Learning with Python;
Applied Data Science Capstone

This means that the IBM certificate should prepare you at a basic level of how a typical data science process should go!

Through these courses, you’ll get to learn how to perform data analysis, followed by honing your machine learning skills through building models.

5. Flexible Self-paced Exercises

All the courses in the IBM Data Science Professional Certificate are held on Coursera, an online platform.

This comes with some perks of having the flexibility to learn on the go!

This is perfect for students aspiring to be data scientists or mid-career changers.

A large amount of content is delivered through video lectures, which can also be accessed on mobile. This means that you’ll be able to learn while on your commute to work/school.

Moreover, the certificate has self-paced video lectures that allow you to pause and go at your own comfortable pace.

One neat feature that I found useful was the video speed function, which let me slow down and speed up video speed according to my preference.

I would go faster on lighter topics and slower on heavier content! I even rewatch these lectures to ensure I really absorb all the content properly.

This flexible style of content is very much different from data science boot camps, where information is crammed into you within a short period of time. It’s important to choose the style of content delivery that fits you.

Curious to know if data science boot camps are worth it?

Read more over here.

6. Good Career Credentials

Completing a Professional Certificate is very much different from completing just an online course.

By completing an IBM Data Science Professional Certificate, you earn two important achievements:

  1. Data Science Professional Certificate from Coursera
  2. IBM Digital Badge

The professional certificate from Coursera is useful for sharing and featuring on your LinkedIn profile. It also allows employers to verify your learning and certificate.

According to Coursera, 30% of certificate holders started a new career after completing this specialization.

The IBM Digital Badge provides credibility to any resume. IBM endorses these badges to prove that you’ve attained the necessary skills in data science.

BONUS: If you’re looking to start a Bachelor of Science in Computer Science from the University of London, this course can also help earn credit for your degree!

Having these digital assets prove that you’ve put in the effort to learn new skills and that’s a good sign for hiring managers!

However, employers, these days don’t just look at these paper credentials as much!

Thankfully, the IBM Certificate has a huge emphasis on projects that you can showcase to your interviewer!

More on this below.

7. Emphasis On Data Projects

The IBM Data Science Professional Certificate has such a strong emphasis on data projects and I’m glad that they’re included.

You’ll be taking on the following projects in this certificate:

  • Crowdsourcing Short squeeze Dashboard project from Course 5
  • House Market Price Analysis Project from Course 7
  • US Domestic Airline Flights Performance Project from Course 8
  • Machine Learning Final Project from Course 9
  • Applied Capstone Project from Course 10

That’s a total of 5 projects in 1 certificate!

In comparison to the Google Data Analytics Professional Certificate, which only has 1 project, the IBM Data Science Certificate provides you with many opportunities for hands-on learning.

These projects all seem very varied and should be interesting to most learners like you!

Some data science projects can be pretty computationally intensive on your machine, so here’s a good guide on how much RAM is required for data science.

Other than being fun, these projects can be included in your data scientist or data analyst portfolio to attract the attention of employers!

I’m sure some of these projects would catch their eye on your resume and become a conversation starter!

Want to know how long a data science project would take?

Then you’d love this article I wrote on average data science project timelines, explaining more about that!

You can choose to get a Coursera Monthly Subscription to gain access to all professional certificates at the cost of only one, at USD $59/month!

Related Questions

How Long Does it Take to Complete the Certificate?

It will take 9-10 months to complete the IBM Data Science Professional Certificate. This will vary depending on having a previous data science background, personal learning speeds, and hours committed per day. Although IBM suggests an 11-month completion time of 4 hours/week, most finish the program earlier.

Here’s what Coursera recommended to me for a timeline:

However, I’d recommend giving yourself more leeway and extra time to absorb the heavy content slowly. You’ll retain information much better like this!

How Difficult is the IBM Data Science Certificate?

The IBM Data Science Professional Certificate is at an entry-level to intermediate difficulty. The content in the certificate covers basic concepts in data science tools and that can be difficult for beginners. However, beginners do not have to worry about the difficulty due to the flexible certificate schedule.

How Much Does the Certificate Cost?

The IBM Data Science Professional Certificate costs USD $39/month. The certificate is priced on a monthly subscription model. Most certificate learners would require 9-10 months of completion time. However, based on discounts by IBM, a 3-month plan costs only USD $78 and a 6-month plan costs only USD $117.

Is the IBM Data Science Certificate a Good Course?

The IBM Data Science Certificate is a good course. The certificate provides 143 hours of in-depth content, a strong focus on Python applications, and data projects, at only a cost of USD $39/month. However, this certificate does not cover many details on R programming.

Who Should Take The Certificate?

Aspiring data scientists and data analysts without programming knowledge should take the IBM Data Science Professional Certificate. These individuals include learners without degrees, students with an interest in data science, and mid-career changers with no relevant experience. However, the certificate is not recommended for non-beginners.

Final Thoughts

Alright, so that’s all the 7 reasons why the IBM Data Science Certification is worth it.

I’m sure many beginners would benefit much from it too. All the best in your learning!

Thanks for reading!

My Favorite Learning Resources:

Here are some of the learning resources I’ve personally found to be useful as a data analyst and I hope you find them useful too!

These may contain affiliate links and I earn a commission from them if you use them.

However, I’d honestly recommend them to my juniors, friends, or even my family!

My Recommended Learning Platforms!

Learning PlatformWhat’s Good About the Platform?
1CourseraCertificates are offered by popular learning institutes and companies like Google & IBM
2DataCampComes with an integrated coding platform, great for beginners!
3PluralsightStrong focus on data skills, taught by industry experts
4StratascratchLearn faster by doing real interview coding practices for data science
5UdacityHigh-quality, comprehensive courses

My Recommended Online Courses + Books!

TopicOnline CoursesBooks
1Data AnalyticsGoogle Data Analytics Professional Certificate
2Data ScienceIBM Data Science Professional Certificate
3ExcelExcel Skills for Business Specialization
4PythonPython for Everybody SpecializationPython for Data Analysis
5SQLIntroduction to SQLSQL: The Ultimate Beginners Guide: Learn SQL Today
6TableauData Visualization with TableauPractical Tableau
7Power BIGetting Started with Power BI DesktopBeginning Microsoft Power BI
8R ProgrammingData Science: Foundations using R SpecializationLearning R
9Data VisualizationBig Book of Dashboards

To see all of my most up-to-date recommendations, check out this resource I’ve put together for you here.

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