PA
Great content. When you apply yourself to this course , there's no "dirty" data you can't handle.

Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego. This Specialization is for learners who are proficient with the basics of Python. You’ll start by creating your first data strategy. You’ll also develop statistical models, devise data-driven workflows, and learn to make meaningful predictions for a wide-range of business and research purposes. Finally, you’ll use design thinking methodology and data science techniques to extract insights from a wide range of data sources. This is your chance to master one of the technology industry’s most in-demand skills. Python Data Products for Predictive Analytics is taught by Professor Ilkay Altintas, Ph.D. and Julian McAuley. Dr. Alintas is a prominent figure in the data science community and the designer of the highly-popular Big Data Specialization on Coursera. She has helped educate hundreds of thousands of learners on how to unlock value from massive datasets.

PA
Great content. When you apply yourself to this course , there's no "dirty" data you can't handle.
AM
It was great course ,helped me in getting better understanding of data and do predictive modeling.
PT
The course provided a lot of insights into predictive modeling.
OD
Great course to start with programming for business analytics.
PM
this platform provides an oppertunity to spread my knowledge beyond my careerline
NS
Excellent content, but presentation is a bit challenging at times.
MZ
Excellent to start your career in machine learning!!!
A
Design Thinking and Predictive Analytics for Data Products
SS
Pretty easy to start with, especially with a background in CS.
MS
This course is more rewarding than I thought. The instructors give step by step explanation of the process also the syllabus of the course is just perfect, Highly recommended.
YJ
It was a good Data Visualization course. I really liked it. It's a good beginner course to start with Data Visualization.
SR
Goes into great detail on ways to actually use the code in sophisticated and useful ways. I feel like this course has started me on building a great python toolkit.
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I learned a good deal from the course. I am satisfied with the content of the course.
The problem I encountered with this course is on the grading of the final project. The format is by using peer-review. But you need to have 3-peers to review your submission. I submitted my 3 weeks ahead of the final deadline of submission but still it was not reviewed by 3 peers. So there was no score on my final project. That does not seem fair.
This is not a Python introduction, but the authors approach it as if it were. Even the most basic data scientist will not calculate averages in the way described here. We'd use pandas or similar to get not just means, but other summary stats as well. For a Python course, I could understand doing it the way shown here. But not for data science.
The course is easy to follow, well organized, and assumes very little background. It effectively demonstrates the power of Python in large data applications and provides insights and guidance on which tools are best used.
This course is more rewarding than I thought. The instructors give step by step explanation of the process also the syllabus of the course is just perfect, Highly recommended.
Goes into great detail on ways to actually use the code in sophisticated and useful ways. I feel like this course has started me on building a great python toolkit.
Great course for an absolute beginner!
Great!
Overall, a good course, clear presentation and explanations.
Some minor things: In my opinion the questions are sometimes not very clear. Rating of the projects can take several days.
A really good course to learn data preprocessing before implementing the machine learning module.
Pretty easy to start with, especially with a background in CS.
Good course.
all of the data sets either no longer exist or are out of data
This course enables students to learn intermediate level skills in data wrangling, data exploration, and visualization. The final project requires selecting a topic of personal interest and constructing a complete project work flow. By doing this, areas of weakness in data wrangling, cleaning/QA, data exploration, and visualization may to uncovered and addressed. The result is to build greater skills and confidence.
This is definitely one of the better courses I've done. Its part of a specialization I belive and I'm about to try move to the next one. Its defnitely slightly deeper than just a beginners course but there are so many beginners courses on coursera that its nice to have something a bit more meatier. The presentation skills are excellent and I really enjoyed doing the course.
This course was very practical. I really appreciate the idea of the final project. Especially I like the web scraping project
It was a good Data Visualization course. I really liked it. It's a good beginner course to start with Data Visualization.
Great content. When you apply yourself to this course , there's no "dirty" data you can't handle.
Curso excelente. Las tareas y exámenes se ajustan perfectamente al material que se imparte.
Really nice. Learnt a lot ! Thanks to the faculties and UC San Diego.
Great course to start with programming for business analytics.