perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.
I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.
By Swapna N•
It was a wonderful experience in learning the course. It was completely a practical approach. I enjoyed the process of assignment submission and reviewing peers assignments. I would highly recommend the course for everyone. Thanks once again.
By Mike F•
Outstanding course! Valuable information and methodologies all with clear and concise presentation. The labs are detailed and filled with awesome examples. Coursework is intuitive and easy to understand. I would highly recommend this course.
By Saurabh M•
Its very nicely designed course .Its designed such that you get brush up your fundamentals and get to know the real taste of statistics and probability applying practically to real world. i really enjoyed and earned a valuable knowledge.
By Ricardo S•
La calidad de los cursos de coursera es excelente. Obviamente tienen detalles que se deben trabajar como algunas presentaciones que no coinciden con las voces en off. Sin embargo con suspicacia se pueden solventar estos infimos detalles.
By Ritik K•
I learnt a lot in this course, the teaching way is quite good with animation and real life based example. I must say the course is designed very carefully. I want to thanks all the course creators to gave us such a great opportunity..
By Jafed E G•
I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand
By Vss T•
Very helpful and useful course especially for beginners who are willing to gain knowledge on Data Analysis. I would recommend starting with this course for those who are interested in mastering their skills in Data Science later on.
By Sayak P•
This course is based mostly on very basic concepts , it's good for those lacking the slightest knowledge in the field of statistics , but yes for beginners it's pretty fine.I loved the presentation of those labs,quite useful
By Phil L•
Really good course. More challenging than I expected. I expect it will take a few applications of the concepts to get them down 100%. Very good presentation of material. The labs were critical to learning the concepts.
By QUAN Z•
The course perfectly fits those who has some knowledge on python and want to do data analysis with it. It explains how professionals would process data, build model with the data, and use the model to solve a real problem.
By Min T A•
This course covers exploratory data analysis and even furthers onto machine learning with some key statistical introduction such as Linear Regression, Correlation, P-value, F-score, etc, explained in its most clear form.
By Pranav K J•
Very good course and well designed , so that a new person also can understand it very well. They way it is taught is admirable. I will recommend, the aspiring data science Engineer, must take this course specialisation!
By Jonathan I O•
This course provides a robust walk-through in the use of python for data analysis. The labs ensure the theories taught are put into practice through hands-on projects that further reinforces skills learned. I loved it!
By Aman S•
A very detailed course. The hands-on exercises were really good and I got to learn a lot of things from this wonderful course. Thanks to all the instructors for their hard work in putting together such a course for us.
By Paul A•
I think this course is the highlight of the Applied Data Science specialization. I learned so much and gave me the tools to learn more on my own. It was really engaging and I never had a dull moment in this Course.
By Roseline A•
This is a great course. I went away with so much knowledge on modelling and model testing. The labs are also very well structured and not just a repetition of the class presentation. I recommend this course highly.
By Ferenc F P•
The beginning of the course helps you understanding how you can manage your data with python. In the end linear regression, and ridge regression is also introduced. Good course for those not familiar in this field.
By Wilfredo A•
Excellente content and very didactic laboratory. There is a lot of information in the course and at the same time it encourages me to investigate and further develop, particularly in Model Evaluation and Refinement
By Brian B•
Very "meaty" hands-on work with doing some data wrangling, exploratory analysis and models with single linear, multiple linear, and polynomial regression fits. I took several hundreds of lines of code in my notes.
By Ashutosh P•
Thank you so much for creating this is great learning and useful course that I got for Data Analytics.This course is very beneficial for all to enhance the knowledge about data analysis with Python.Thank you sir.
By Nilo V•
I find the course well organized and the lab sessions made use of relevant instruction that I can use for my daily work. The final assignment could be more challenging. Overall a very helpful learning experience.
By RAM K A•
Excellent explanation about the topics and helpful examples. Course requires reading outside the course module for better understanding. Will be helpful, if you could run the program on the window and explain us.
By Daniel L•
A rotating three-dimensional plot may be added. Its very easy and practical to complement the analysis presented. Otherwise the course is very complete.
Also, the pipe explanation may be improved a little bit.
By Seemant T•
I am reviewing this course after the completing it. It was a good learning experience!!
The entire course is based of the student interaction and requires basic knowledge of Python and its Libraries.
By vrushabh l•
Very good course to begin with in the field of Data Science. The analysis of data is very important before we start implementing predictive models on the data, which has been covered very well in the course.