Coursera -IBM Data Science course Review 2021

Coursera and IBM have come together to create the Data Science Professional Certification Program. Those who haven’t checked out the course can check it out by clicking on the underlined senetence above .

The program consists of 9 online courses including open source tools and libraries, Python, databases, SQL, data visualization, data analysis, statistical analysis, predictive modeling, and machine learning algorithms. You’ll learn data science through hands-on practice in the IBM Cloud using real data science tools and real-world data sets.At the end of the program, you will have a completion certificate as well as 9 badges, one for each course in the program. These badges can be added to your portfolio, LinkedIn profile too.

Okay so i recently finished the course and would like to share my reviews here, first of all i have done few courses on data science earlier and did the course to strengthen my basics. So the first word about the course is that it’s a great course for beginners and would recommend the course to every beginner out there looking to learn Data Science or individuals transitioning to Data Science Field.

TIME AND MONEY:

Coursera follows monthly payment structure so time here is directly proportional to money.It charges you 39$for one month and hence it kind of boosts you to compete the program as soon as possible which i believe is graet marketing.I completed this course in under 30 days as i had previously done Andrew NG’s Machine learning course and had some prerequiste knowledge for the course.

Average time estimate by Coursera for this course is 3 months for working individuals but I believe this could be easily be completed in under 2 months. However, if you are looking to finish the program within 1 month, I highly recommend completing some prerequisite learning programs before starting.

IBM’s Data Science Professional Certificate is structured across 9 courses.

The course list is the following:

  1. What is Data Science
What is Data Science

Simply,the easiest course, completed this in a single ,day had no major assignment. The Course basically defines what is data science and what is expected from a data scientist and gave a brief overview about data science topics and where is data science required in buisness.Try to complete the course in 1–2 day as you’ll be learning everything told in this course in detail in future.

2.Tools for Data Science

IBM WATSON

The real hustle starts with this course where you get to learn about the various useful toolkits that data scientists use on a daily basis .To defeat a enemy you first need to know what weapons do they possess. Similarly this course provides you about the basics of GitHub, Jupyter Notebooks, and RStudio IDE.And ofcourse ,IBM’s own data science platform IBM WATSON. You’ll also learn about other IBM tools used to support data science projects, such as IBM Watson Knowledge Catalog, Data Refinery, and the SPSS Modeler which will come handy in upcoming courses and first major assignment will be to create a jupyter notebook.

3.Data Science Methodology

This course teaches you how to think like a programmer ,and i really appreciate this course as no previous course had something like this, in this course you will learn how to complete the Data Understanding and the Data Preparation stages, as well as the Modeling and the Model Evaluation stages pertaining to any data science problem. How to tackle any data science problem statement, and how to break the small problem statement in small pieces.

4.Python for Data Science and AI

Majority of Data Scientist’s use two programming languages-Python or R.This course teaches Data Science in Python which is the most popular language now-a-days for data scientist. Joseph Santarcangelo(instructor for this course)does a tremendous job in teaching the basics of python And teaches you just enough python required for data science. Although it is a great course but i would suggest you to learn a bit more of python via Jose portilla’s python course or Telusko’s Python playlist.

5.Databases and SQL for data science

This course will teach you about basics of SQL Databases and how to access them with python.You will learn how to explain the basic concepts related to using Python to connect to databases and then create tables, load data, query data using SQL, and analyze data using Python.

6.Data Analysis with Python:

Up to this point everything was being buildup via different tools ,language ,SQL. From this course the real deal starts ,for being a good data Analyst you should have great knowledge in data analysis and visualisation .Although i had done data analysis in some other courses too ,I liked revisiting Pandas, NumPy, and SciPy. This course covered a range of data analysis techniques, from finding and wrangling data to statistical analysis and modeling. The course was structured in a very efficient and intriguing way I loved the whole course layout and had pretty fun completing the assignments which i believed could have been a bit tougher to test our skills but all in all it was a pretty good course.

7.Data Visualization with Python

A visual for my Applied datascience Capstone project

“A picture is worth a thousand words”. We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data. This course was probably my favorite and it was great fun plotting graphs,piecharts and actually visualising the data.

8.Machine Learning with Python

This course dives into the basics of machine learning using Python. I thought this course needed to be a bit more explained ,the maths behind different machine learning algorithms was absent from this course. This course was quite a let down for me and i believed it could have been better, for machine learning i would suggest you guys to follow Andrew NG’s Machine Learning Course.

9.Applied Data Science Capstone Project

This course is the whole summary of the program and is pretty great in itself you have to create a simple project by yourself and submit it for getting graded by your peer and then only you will get final badge of completion.

This capstone project course will give you a taste of what data scientists go through in real life when working with data.You will learn about location data and different location data providers, such as Foursquare. You will learn how to make RESTful API calls to the Foursquare API to retrieve data about venues in different neighborhoods around the world. You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code. You will utilize Python and its pandas library to manipulate data, which will help you refine your skills for exploring and analyzing data. Finally, you will be required to use the Folium library to great maps of geospatial data and to communicate your results and findings.

Overview(Worth your money and Time??):

Should I take this Course
  1. A major highlight of the course are Peer Graded assignments which gives you an opportunity to grade your peers and see how they have performed and completed the same problem statement in a different way through which we get to learn a lot.
  2. Applied Capstone project gives you a real life overview of how data science projects are made ,how to tackle a data science project statement which is absent in most of other data science courses.
  3. Another aspect of the Certificate which I appreciated was the fact that its entire curriculum is structured as if it were a project, taking you from little knowledge to project delivery in a smooth manner, never making you feel too stretched or too bored. Thus, I experienced a smooth transition between the various topics and components.
  4. Engaging learning experience and a great introduction to more advanced courses.
  5. It will help you Build confidence to get started with personal projects.
  6. If you are a beginner in the field of data science /transitioning to data science it is one of the best course out there and would highly recommend to take this course,and is pretty economic too as compared to other courses.
  7. If you have previously done any other data science course then Iwould suggest you to not take this course as it is pretty basic and you’ll need other resources to learn more deeply.
  8. I believe the course was pretty Light on Maths and statistics, machine learning is something which is pretty math heavy and everyone should understand the math behind the machine learning algorithms , Andrew NG’s machine learning and deep learning courses can be pretty great to cover this aspect .

I am a university student / graduate that wants to start a career in Data Science; is this certificate right for me?

Yes, this certificate is perfect for you. If you are just starting out in your analytics career, and have loads of free time, this certificate is the perfect accompaniment to your university degree. If I were hiring for junior to mid level analyst positions, a candidate who took their own initiative to achieve this certificate would stand out in a pool of otherwise equal credentials.

Yes, this certificate is perfect for you. If you are just starting out in your analytics career, and have loads of free time, this certificate is the perfect accompaniment to your university degree. If I were hiring for junior to mid level analyst positions, a candidate who took their own initiative to achieve this certificate would stand out in a pool of otherwise equal credentials.

Wrapping Up

This was a pretty long post. If you’ve made it all the way here. Thank you for reading!

I’ve been wanting to write this article as I felt that it would be beneficial to others who are starting out on their data science journey. I hope that by sharing my experiences and the steps/courses I took to learn, it will help you discover your own path.

One more thing I want to add is that everyone’s path is different. From the methods, to the time they took to learn. Don’t feel down when things get hard. There were so many times I wanted to give up and still do. The key is to be consistent and take small steps to move forward.

This is my first post on data science and hopefully there will be many more to come. If you have any questions or comments feel free to leave your feedback below. You can also connect with me on LinkedIn and also check out and follow my Github that includes projects from the course.

If you have completed the certification program, I’d love to know what you thought. Please Comment below to share your thoughts and do give a clap if you find this article.

Cheers and Happy learning to all.

However, learning is like a nutrition plan, you need to keep a healthy distribution of books, articles, MOOCs, bootcamps and all of that.

I am a university student / graduate that wants to start a career in Data Science; is this certificate right for me?

Yes, this certificate is perfect for you. If you are just starting out in your analytics career, and have loads of free time, this certificate is the perfect accompaniment to your university degree. If I were hiring for junior to mid level analyst positions, a candidate who took their own initiative to achieve this certificate would stand out in a pool of otherwise equal credentials.

Happy learning all.

An avid programmer, Data Scienctist, storyteller , Helping individuals find greater happiness through personal branding, story, and creativity.