IBM Data Science Professional Certificate Review- Latest 2024

Planning to enroll in IBM Data Science Professional Certificate?… If yes, then you should definitely read my experience with IBM Data Science Professional Certificate. I hope my IBM Data Science Professional Certificate Review will help you to take your final decision for Enrolling in this Certificate program.

IBM Data Science Professional Certificate Review 2024

Before starting the detailed review, I would like to provide a brief summary of the IBM Data Science Professional Certificate based on my experience. In IBM Data Science Professional Certificate, there are 9 courses. And here is my experience with these 9 courses-

Brief Review-

• The first “What is Data Science?” course is very basic and you may get bored if you have some previous understanding of data science.
• In course 2 “Tools for Data Science“, I felt some previous knowledge in programming is good to have. 
• I really appreciate the “Data Science Methodology” course because, in data science, strong analysis is important. And this course will teach you from Business understanding to the deployment part.
• The Python for Data Science and AI course is not a complete Python course. This course teaches only the required knowledge of Python for data science.
• I personally loved this “Databases and SQL for Data Science” course because this course is much practical than other courses.
• The “Data Analysis with Python” course is really a wonderful course for learning Data Analysis using Python.
• I found the “Data Visualization with Python” course a bit challenging as a beginner, but I believe that challenges allow you to think logically.
• “Machine Learning with Python” is my favorite course because I love machine learning.
• The last “Applied Data Science Capstone” was fun and challenging for me.

Now let’s start in-depth IBM Data Science Professional Certificate Review with the first section that is-

How is the Course Content of the IBM Data Science Professional Certificate?

IBM Data Science Professional Certificate is available on Coursera, an online learning platform for enormous online courses. This certificate program includes 9 courses that begin at a very basic to advanced level. All 8 instructors have experience in data science.

After successfully completing all 9 courses, you will get a completion certificate as well as 9 badges for each course. You can add these certificates and badges to your portfolio, and LinkedIn profile.

Courses Details-

1. What is Data Science?
2. Tools for Data Science
3. Data Science Methodology
4.  Python for Data Science and AI 
5. Databases and SQL for Data Science
6. Data Analysis with Python
7. Data Visualization with Python
8. Machine Learning with Python
9. Applied Data Science Capstone

Course 1-What is Data Science?

The first course is all about Introduction to Data Science. But this introduction is a very high-level introduction with interviews with students and professionals, explaining their experience in the data science field.

I really enjoyed this course and the knowledge everyone was sharing throughout the course. The whole IBM Data Science Professional Certificate Program is designed for beginners that’s why the first course is very basic. Some people find this course boring because they already know about data science. But for complete beginners, this course is the first step towards data science.

So if you already have some background knowledge in data science, you can skip this course. But it’s good to complete and know the experience of professional data scientists.

Course 2- Tools for Data Science

This course is all about open-source tools used in data science. The main focus of this course is on tools like Jupyter Notebooks, RStudio, Zeppelin, GitHub, and IBM Watson. This course makes you familiar with these tools. And you will get to know what each tool is used for, what programming languages they can execute, their features and limitations.

In this course, what I felt is some previous knowledge in programming is good to have. Otherwise, at some points, you will feel lost.

Course 3- Data Science Methodology

This course is all about how to think like a Data Scientist. This course will help you to understand each and every stage of Data science methodology. I really appreciate this course because, in data science, strong analysis is important. And this course will teach you from Business understanding to the deployment part.

The best part about this course is its step-by-step approach. The course begins with understanding the business problem and move in the step-wise approach to the model deployment.

Course 4- Python for Data Science and AI

As the name sounds, this course teaches Python basics, Pandas, and NumPy. This course provides only the required knowledge of Python for data science. All the modern methods and python libraries for data manipulation are included.

What I think about this course is that this course is not a complete Python Course. This course teaches only those topics that are important for data science. Some previous knowledge in python is good to have before starting this course.

This course also includes the first project of this IBM Data Science Professional Certificate Program. In the project, you have to analyze a set of economic data using Watson Studio.

Course 5- Databases and SQL for Data Science

I personally loved this course because this course is much practical than other courses. In this course, I learned how to build databases, how to collect and analyze the data using Python. The hands-on project in this course is also very interesting and challenging.

If you are a beginner in SQL, then definitely you will learn a lot from this course. The whole course is a well-structured and perfect balance between theoretical and practical knowledge.

Course 6- Data Analysis with Python

This course helped me to learn statistics in an easy way. This is really a wonderful course for learning Data Analysis using Python. In this course, you will learn a range of data analysis techniques, starting from importing and wrangling data to statistical analysis and modeling.

According to my experience, the best part about this course is that explains useful libraries( Pandas, Numpy, Scipy, and scikit-learn) and methods. And what I didn’t like in this course is the lab assignments. The lab assignments in this course need improvement.

Course 7- Data Visualization with Python

This course is all about data visualization using Python. Data Visualization is an important topic in data science. The course introduces a range of data visualization techniques like line graphs, pie charts, bar charts, and specialized visualizations like Waffle and Folium.

In this course, I got to know that with the help of Python, we can create charts as well as map functionality. I found this course a bit challenging as a beginner, but challenges allow you to think logically. And that makes learning interesting. According to my experience, having a familiarity with Pandas will be helpful to take most of this course.

Course 8- Machine Learning with Python

This is my favorite course because I love machine learning. This course covers a lot of machine learning topics like simple regression models, classification, clustering, and recommendation systems. The course explained the mathematical and theoretical foundations behind some of the machine learning algorithms.

In the final project of this course, you have to apply four different types of machine learning algorithms to a data set and check which is the best. This was really a fun challenge for me.

Course 9- Applied Data Science Capstone

Last but not least- The Capstone Project!

The capstone project has two parts. In the first part, there was another learning module, where we had to cover the Foursquare API to get location details. For me, this was a very exciting module.

The second and final project of this course is totally open-ended. In that project, we had to prepare our own questions to answer with the tools we had learned. The only requirements for this project were to use the Foursquare API, use data analytics, and create a Folium map as a part of the presentation.

The freeform nature of the project forced me to do a lot of self-learning in order to complete it. After completing this course, you have a report, a blog post, and a notebook with complete code that you can showcase in your portfolio.

Now, I would like to discuss few more important things related to IBM Data Science Professional Certificate–

Who Should Enroll?

I recommend this course to data science beginners who are planning to enter in Data Science field. This certificate program is worth it for you if you are interested in beginning a career in Data Science or you have no domain knowledge.

This program is also good for those who have been off the tools recently. The content in this course is well structured and keep a logical progression in both theoretical concepts & practical session throughout.

Cost of the Course-

This course is based on a subscription-based payment method. That means you have to pay $39 per month (until you complete the Certificate program). After paying 39$ you will get access to all the course modules, assignments, peer-graded assignments, and discussion forums.

Time to Complete

It’s totally up to you. But as the payment method is monthly, so it’s better to complete it in less time. I completed the whole certificate program in 25 days ( to save 39$ for next month😃). I was free after completing my Master’s, so I gave full time to IBM Data Science Professional Certificate Program to complete in one month.

But again, it’s up to you. Don’t rush to complete the program in under a month. If you are not able to give full time to this Course. No worries!. Learn according to your pace and time. Because what you will learn throughout the course is important not the completion speed.

Personal Tips-

My most important tip for this course or any other course is dedication and practice. Watching videos, running the provided code in Jupyter Notebooks, and clear the quizzes without reinforcing your knowledge is easy. That’s why you have to take the time and go through each module and exercise to clear your doubts.

What you can do is just try to rewrite the code that is provided to help during the course. And spend approx 30 minutes reading about data science articles. This 30-minute reading will help you to stay motivated and focused.

Another tip that I experienced during this course is to plan your day in advance. Before starting this course or any other, just plan your timing how much time you can give to the course daily and then try to follow the same time plan throughout the course. By doing so, you will not feel unorganized.

What’s Next?

Many people think that after completing this course, they will become a Data Scientist or get a job. According to my experience, this is the biggest misunderstanding many people have. This course will only start your data science journey and provide you all the necessary information related to data science with a few small projects and one unique project (the capstone).

And that’s alone is not enough to land in the data science market. So after completing this course, you have to work on projects with the skills you learned in this course and expand your portfolio with some other unique projects.

Conclusion

According to my experience, this IBM Data Science Professional Certificate Program is perfect for those who are beginners and want to get a high-level summary of data science. The whole program is really valuable to receive a broad understanding of all you need to know as a data scientist. That’s why I really recommend this course to beginners.

I hope my IBM Data Science Professional Certificate Review will help you to take your final decision. If you have any questions, feel free to ask me in the comment section. I am here to help you. And If you found this article helpful, share it with others to help them too.

If you want to begin your data science journey with the program. Click Here IBM Data Science Professional Certificate!

All the Best for your Data Science Journey!

Happy Learning!

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