Ratings and Reviews for Introduction to Data Science in Python

Really loved working on the assignments from the course, it was really helpful for me to learn by doing things practically, however the course video content could improve thus giving it a 4 star rating.

The content was high level and good. You should explain more

best course of beginners

IN SHORT\ \ This was a great course and I learnt a lot! Topics covered include a quick reminder on intermediate python and lots on pandas and some numpy. The weeks 3 and 4 assignments are quite challenging so expect to spend considerably more time than indicated on the course site if you're not experienced with python and pandas. This course is not for coding newbies.\ \ IN DETAIL\ \ I am proficient in R for data analysis and had dabbled with python before although had no experience with pandas. I was committed to learn the course material and to spend a substantial amount of time doing so. The speed of lectures is fast. I paused often to take notes and to try out the provided notebooks, and I returned to some of the videos when working on the assignments. I found the course assignments good and challenging. The lectures give a good tour of different functions and approaches you may want to use in the assignments, but there isn't much handholding with the assignments and you'll most likely spend quite of bit of time looking things up online in pandas docs and stackoverflow. If you're used to that and generally troubleshooting code, you'll probably be just fine. I spent much more time on the assignments than what is estimated on the site: ~5h for week 2 (vs 1.5h indicated), ~1 day for week 3 (vs 2h), and 2.5 days for week 4 (vs 4h).\ \ Week 1 gives a refresher on how to write functions, list comprehensions, and lambdas in python. If you're familiar with writing loops and functions in other languages, with this material you will get to writing them in python quickly if you invest a bit of time and effort. If you're not yet at the level of confidently writing functions, loops and vectorized alternatives in python or another language, I'd recommend starting with a different, more basic course because the learning curve with this one might be too steep.\ \ Week 2 gives the ins and outs of pandas including creating and querying pandas series and data frames.\ \ Week 3 covers merging data frames, grouping (groupby) with aggregation (agg), applying functions rowwise (apply), and pivoting data (pivot_table) etc. It also gives a whirlwind tour of date/time manipulation using pandas. numpy is also included.\ \ Week 4 has some lectures on distributions and more on numpy. The week consists mainly of the main project assignment where 50% of points are given on data cleaning and munging (contents of weeks 1-3) and the other 50% of points are on modelling and hypothesis testing. It's quite a proper project in the sense that you're given a number of non-clean data files scraped from different places and a hypothesis to test. There are some additional instructions on what format of cleaned data to produce from the different files and what type of test to perform, but for the rest you're on your own.

Good

This was a great course. But I would advice programming newbies to really be comfortable with problem solving and Python programming before going through it.\ \ Cheers

Assignments are really good but the pace of teaching can be improved upon

I did badly but it's still a good MOOC.

Worse course ever. Materials don't provide enough information for performing assignments. Explanation is very short, general and isn't clear. Actually the course doesn't explain almost anything in Pandas structure, functions and approaches. As a software engineer I'm capable of solving complex problems. But here it's not about solving problems, it's about self studying and surfing Internet obtaining knowledge. What the course for?\ \ Wrong column names, mistakes in formulas... Why the quality is so low?\ \ I'm really disappointed spending time for it. Have to cancel it on the second week.

Absolutely recommended for beginners, use of pandas for data wrangling taught very well.