Applied Data Science With Python Specialization Review- Latest 2025

Are you planning to enroll in Applied Data Science with Python Specialization?… If yes, then read my Applied Data Science With Python Specialization Review of 2025 and then decide whether to enroll in Applied Data Science With Python Specialization or not.

Now without any further ado, let’s get started-

Applied Data Science With Python Specialization Review

So, let’s start with the course quality and content covered-

Content Covered-

Applied Data Science with Python Specialization is available on Coursera and has 5 courses. Each course focus on some characteristic of using Python for data science.

After successfully completing all 5 courses, you will get a completion certificate for each course. You can add these certificates to your portfolio, and LinkedIn profile.

Courses details-

1. Introduction to Data Science in Python
2. Applied Plotting, Charting & Data Representation in Python
3. Applied Machine Learning in Python
4. Applied Text Mining in Python
5. Applied Social Network Analysis in Python

Course 1– Introduction to Data Science in Python

As the title sounds “Introduction to Data Science in Python“, I thought that this course will brush up on my Python concepts, but I was wrong. This course expects that you are comfortable in Python before enrolling in this course.

So, don’t think this is a beginner-level course for Python. This course will teach you more advanced Python concepts. In this course, you will learn NumPy and Pandas, two important Python toolkits for data cleaning and processing. This course will also teach you Pandas basics like how to store data into DataFrames, query data stored in DataFrames, etc.

This course also covers more advanced topics such as merging, grouping data, and manipulating dates. Along with this, this course will introduce you to Jupyter Notebook. Which you can use to complete your weekly assignments.

I liked the assignments of this course that were challenging and well designed. To complete the assignments, you have to be prepared for searching on google and reading on Stack Overflow.

Course 2–Applied Plotting, Charting & Data Representation in Python

After learning tools to manipulate and store data in Course 1, in this course, you will learn something interesting that is data visualization. This course contains a lot of theories related to data visualization. In this course, you will learn about matplotlib and Seaborn libraries and how to create useful visualizations with Python.

The assignments of this course will force you to search on google and stack overflow. That was good for me. Because I learned a lot during completing the assignments. I had to find my own datasets and produce a meaningful visualization. Once I completed my assignment, peer learners reviewed and provide feedback.

Course 3– Applied Machine Learning in Python

This is an introductory course to supervised machine learning methods. This course provides dense Machine Learning concepts, like Regression, Classification, Clustering, Neural Networks, and many more. In this course, you will also learn about the essential scikit-learn machine learning library. 

This course will cover supervised methods for both classification and regression tasks. What I loved in this course is an entire week dedicated to model evaluation and model selection methods. You can use these methods to understand and optimize the performance of your models. I really enjoyed taking this course.

Course 4– Applied Text Mining in Python

This course really helped me with my Ph.D. work. As my topic is “Depression Detection from Social Media“, and this course helped me to learn how to handle a variety of text mining and text manipulation tasks. In this course, I learned how text is handled by python and the important nltk framework for manipulating texts.

I also learned about regular expressions and how to clean and prepare the text for the machine learning process. This course also covers the basics of Natural Language Processing (NLP).

The last module of this course is Topic Modelling, where you will play with topic detection and group them by similarity.

Course 5– Applied Social Network Analysis in Python

I found this course a bit challenging as compared to other courses in this specialization program. This course will teach you the basics of network analysis through the NetworkX library. This course will not only provides theoretical knowledge about network analysis but also explains the use of each topic in real networks.

The last assignment of this course was fun for me to experiment with different models and analyzing the performance.

Now I would like to discuss few more important things related to Applied Data Science with Python Specialization–

Who Should Enroll?

This specialization is an intermediate-level specialization that assumes you have some previous basic(not advanced) knowledge in Python, Statistics, and discrete mathematics. Before enrolling in this specialization program, I had taken Andrew Ng’s Machine Learning course. So I had some previous knowledge of math and terminology.

So if you have some basic knowledge of maths and statistics, and you can write programs in Python, then only you should enroll in this specialization program.

Cost of the Course-

This specialization program is based on a subscription-based payment method. That means you have to pay $49 per month (until you complete the Certificate program). After paying 49$ you will get access to all the course modules, assignments, peer-graded assignments, and discussion forums.

Time to Complete

According to Coursera, if you spend 7 hours per week, you can complete the whole program in 5 months. But, It’s totally up to you. As the payment method is monthly, so it’s better to complete it in less time.

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.

-My Final Recommendation-

I recommend this specialization program to only those who have Intermediate level Python knowledge and interested to learn more advanced data science concepts with Python. People who are a beginner in Python, please don’t go for it. It’s better to learn Python first from Python for Everybody Specialization or from any other good Python Course.

Personal Tips-

This specialization needs a large time commitment and a strong focus on completing projects. So, my most important tip for this specialization 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 I experienced throughout all these specialization programs- Time Management is crucial. So before starting this specialization program 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 specialization program. 

What’s Next?

The biggest misunderstanding many people have that certifications will help them to get a data science job. No!. Certifications are not important, what you learned throughout the specialization program is important. So, don’t think that one specialization program will help you to land in the data science market.

This Applied Data Science with Python Specialization provides intermediate-level knowledge of Data Science with Python. So after completing this specialization, you have to work on projects with the skills you learned throughout the 5 courses and expand your portfolio with some other unique projects.

Conclusion

I recommend this specialization to only those who have enough Python knowledge and interested to learn more advanced data science concepts with Python. People who are a beginner in Python, please don’t go for it. It’s good to learn Python first from Python for Everybody Specialization or from any other good Python Course.

I hope my Applied Data Science with Python Specialization 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 enroll in this specialization, Check Here!

All the Best for your Data Science Journey!

Happy Learning!

Thank YOU!

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Though of the Day…

‘ It’s what you learn after you know it all that counts.’

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