Julian McAuley
This is the first course in the four–course specialization Python Data Products for Predictive Analytics, introducing the basics of reading and manipulating datasets in Python. In this course, you will learn what a data product is and go through several Python libraries to perform data retrieval, processing, and visualization. This course will introduce you to the field of data science and prepare you for the next three courses in the Specialization: Design Thinking and Predictive Analytics for Data Products, Meaningful Predictive Modeling, and Deploying Machine Learning Models. At each step in the specialization, you will gain hands–on experience in data manipulation and building your skills, eventually culminating in a capstone project encompassing all the concepts taught in the specialization. UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn’t just acquired in the classroom—life is their laboratory.
Instructor Details
Courses : 3
Specification: Basic Data Processing and Visualization
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17 reviews for Basic Data Processing and Visualization
Add a review
| Price | Free |
|---|---|
| Provider | |
| Duration | 14 hours |
| Year | 2019 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
FREE
Carl W –
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.
Cambron T D –
Great first class in this series.
Davide C –
The test scripts make no sense.
Sebastian S –
The positives: I liked the design of the final project, and how users were encouraged to ‘get out there’ and find some interesting open source data sets. The lectures were well structured with good narratives and good examples. The negatives: I would have liked a bit more focus on actual visualization libraries like matplotlib and maybe seaborn. When covering the data types (date, string, boolean etc.), it might be worth adding an extra week or so were these things are done with the help of the standard library pandas. I feel like this is what people will end up doing anyway bc there are so little alternatives in python to do processing, so a course on data processing should ideally cover that library.
Zakir U S –
Over all a great course for beginner
Mohd Z A –
Excellent to start your career in machine learning!!!
Paul E J –
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.
Oriol P M –
Excellent and interesting course
Jonas J T –
Quick intro to data processing. More material on numpy and pandas would have been nice. Im still trying to figure out why the specialization mentions “Design Thinking”. At least in this course…not a single design thinking concept was mentioned.
Clarence E Y –
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.
umair –
Great course for an absolute beginner!
Ioana B –
The information learned in this course is very useful, for a beginner in data science. It is a very good introduction in working with python, extracting data sets, defining features and plotting graphics. What I didn’t like at all is the engagement. Finishing the course was not satisfactory at all for me even if I submitted my project on time, I didn’t receive 3 reviews and I found the grading system very subjective. Knowing this, I would think twice about paying for this experience what I learned can be found in free tutorials too, and only for the interaction with other users I don’t think it is worth the price.
Tiago F –
Very Good to start learning Python
Kotronis A –
very subjective assignments
Xi L –
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.
Xuejie Z –
nice basic python course
Stan –
Can’t finish yet because I have nothing to grade.