Introduction to Data Science in Python

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Below are the top discussions from Reddit that mention this online Coursera course from University of Michigan.

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library.

Python Programming Numpy Pandas Data Cleansing

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Taught by
Christopher Brooks

and 11 more instructors

Offered by
University of Michigan

Reddit Posts and Comments

0 posts • 31 mentions • top 16 shown below

r/learnpython • comment
35 points • haragoshi

Phenomenal free course on python and pandas. You can watch lectures and submit assignments for free. It got me started on the path of using pandas and python for a lot of my data diving.

https://www.coursera.org/learn/python-data-analysis

It's the first of a 4 class certificate. The later classes require payment to get peer-grading of homework, so while I tried the second one i don't recommend it as eagerly.

If you like the course and want to put a certificate of completion on your linked in profile (like i did) you can pay $80.

r/mathematics • comment
6 points • knestleknox

I learned most of my coding foundation through side-projects in college. But it wouldn't be that hard to pick up as a mathematics major as it's a very logical field. While I learned general coding myself, I decided to take this course which I highly recommend for picking up data science in python/pandas.

Yeah, Python/R are the 2 giants in the industry now but imo Python is far superior as it can be used in a more general programming context, it's quickly becoming the most popular language of all time, and it has amazing package support. As I said, python's not too hard to learn. What is harder harder to learn is the data science tools such as pandas/keras/matplotlib etc...

r/learnpython • post
10 points • Zeppelin2k
Best online courses to learn python for an intermediate programmer?

I have no experience with Python and I'd like to learn this year. But I am familiar with programming to a degree; I use Matlab frequently for work, mostly for data analysis and fitting. I have a firm grasp on programming fundamentals.

With that in mind, I'd like some advice on ways I can start learning. I think an online course, preferably free, would be best. I know a number of them are starting next week. There's something like MIT's Intro to Computer Science (https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-11), but since this is geared towards beginners I'm worried I won't get as much out of it. There's also something like this five-part Applied Data Science with Python course on Coursera (https://www.coursera.org/learn/python-data-analysis), which might be the right level but I'm not sure it's a good or worthwhile class. Any thoughts on these or other recommendations would be greatly appreciated. Thank you!

r/analytics • post
10 points • nolenole
Come join me in Coursera's Introduction to Data Science in Python course!

Hey ya'll! Coursera's "Applied Data Science with Python" specialization is starting its first course on April 9th - Introduction to Data Science in Python. If you've got a bit of Python/programming experience but are otherwise starting fresh with data analytics, come join me on the journey! I want to get a Slack group going where we can discuss assignments and our journeys into the wonderful world of data with Python.

Shoot me a PM if you're interested or join the Slack at data-with-python.slack.com.

r/Accounting • comment
4 points • dtizzlenizzle

Introduction to Data Science in Python | University of Michigan https://www.coursera.org/learn/python-data-analysis

r/learnpython • post
3 points • AirieFenix
[REQUEST-ELI5] How this for-in works?

Hi, people!

I'm doing the University of Michigan's Introduction to Data Science in Python course and I'm finding one particular line on their Jupyter notebook hard to understand.

There is a list of dictionaries with fuel consumption and other cars data.

print(mpg[0])
{'': '1', 'year': '1999', 'cty': '18', 'class': 'compact', 'trans': 'auto(l5)', 'model': 'a4', 'manufacturer': 'audi', 'fl': 'p', 'hwy': '29', 'drv': 'f', 'displ': '1.8', 'cyl': '4'}

There are some examples of what to do with this data and how to accomplish them. But I'm puzzled on how do they calculate average mpg:

sum(float(d['cty']) for d in mpg) / len(mpg)

Sure thing, they got the desired result. The thing is, I kinda know what's going on on that line but I don't really know or can explain. I get the interpreter is using d for each item in mpg(mpg.items) but I don't how the first d['cty'] works.

So the question is what the d['cty'] piece of the for statement do, how it works and what the interpreter actually does with that piece of the statement?


Sidenote, I have done:

a=0
for i in mpg:
    a += float(i['cty'])
print(a/len(mpg))

And while it works just fine, it doesn't seem as pythonic as the lecturer way of do it.

Thanks in advance!

EDIT: formatting.

r/learnmachinelearning • post
2 points • GetsTrimAPlenty
An alternative to Machine Learning with Andrew Ng?

My wife is interested in learning about data science, and the titular course was highly recommended in her research. The issue is, is that she thinks that the course is very boring; so boring that she has a hard time picking it up again after a break. Are there other alternatives that you would recommend?

​

To put that "boring" comment in context, my wife is a genius. I don't mean that poetically, I mean that literally, she's had at least one IQ test measure her IQ in the range of 150-160. She also happens to be very gifted in math and has her Master's degree in applied math. She often complains that lectures and content in math courses or texts are "too slow" or simple for her. I don't have her gifts, so I'm not sure how to help her, so I wanted to ask here for insights.

​

She has taken another data science course previously: Introduction to Data Science in Python, which she seemed to enjoy; though she did have complaints about their "just look up everything on StackExchange" philosophy, as she put it. She's hoping to take one more course and then start taking part in Kaggle competitions to build her portfolio before applying for Data Science jobs.

​

Thank you.

r/Romania • comment
8 points • centient_srouton

Presupund ca ca iti place in continuare ceea ce faci, chiar daca te simti mediocru, sunt curios, cum ai invatat sa programezi?

Ai urmat vreodata un curriculum structurat sau ai fost genul care tot timpul a trebui sa invete in timp ce rezolva probleme concrete?

Ceea ce urmeaza sa zic e o opinie relativ nepopulara, dar m-am izbit de situatia asta suficient cat sa imi o asum: Programatorii self-taught nu sunt constanti in a rezolva probleme intr-un timeframe rezonabil.

Am 25 de ani si sunt lead dev si arhitect intr-o echipa de vreo 20 de oameni. Am ajuns in pozitia asta dupa 6 ani de scoala (4 din ei am lucrat part time ca programator). Echipa noastra e mixta, sunt oameni self taught, care au avut schimbare de cariera pe la 30 de ani si s-au apucat de programare, si sunt oameni care au terminat macar licenta in ceva IT related. Cei "cu scoala" sunt un pic mai predictibili cand vine vorba de capacitatea lor de a rezolva probleme intr-un timeframe rezonabil pentru ca scoala s-a asigurat de acoperirea tuturor elementelor esentiale si de baza. Sa inveti sa "programezi" nu e doar a invata limbajul X, tehnologia Y sau stack-ul Z. Inseamna sa dezvoltii un mod analitic de gandire. Asta de obicei dureaza, luni, ani daca vrei sa fii un programator bun. Am dat de destui oameni care care nu inteleg chestii de baza, cum ar fi cum functioneaza o functie anonima, care e diferenta dintre o variabila statica si unda de instanta, desi teoretic aveau 3-4 ani de experienta in limbajul respectiv. Problema lor e ca de multe ori s-au concentrat doar sa "faca sa mearga" chestia pe care o scriau, si nu s-au obosit sa inteleaga conceptul care o face sa mearga. O data ce iti dezvolti modul analitic de gandire o sa tinzi sa ai o abordare similara pentru aproape toate problemele pe care incerci sa le rezolvi.

Daca esti intr-o situatie similara, sugerez sa pui mana pe o carte care exploreaza elemente mai avansate din limbajul pe care il folosesti acum, si cum ar trebui folosite, si eventual 1-2 cursuri online axate pe folosirea lui intr-un context mai analitic, care te forteaza sa intelegi de ce functioneaza asa cum functioneaza si nu doar cum.

e.g. pentru Python:

r/jobs • comment
1 points • beige4ever

sure. it needs knowledge of Python or other programming language, your VB shoul be enough. https://www.coursera.org/learn/python-data-analysis?

r/learnpython • comment
1 points • synthphreak

Neither book nor site, but I can recommend this absolutely fantastic resource:

https://www.coursera.org/learn/python-data-analysis?specialization=data-science-python

I recommend paying to enroll so that you have access to the assignments. The lectures (free) are very helpful, but you really need to get your hands dirty actually using this stuff to really solidify it in your brain.

Anyway, this course is the thing that really cracked the nut that is pandas for me. And now I use it every day at work. The course has literally, palpably improved my daily life. May it do the same for you.

r/learnmachinelearning • comment
1 points • mallasahaj

I took Introduction to Data Science in Python by the University of Michigan. This is an intermediate course and assignments here are tough. The assignments will throw you to the wolves very early. The assignments make you research more about how to apply pandas and NumPy in the given task. This made me learn more and more about it. I can only recommend this course to anyone interested and who already has a basic knowledge of Python.

r/Python • comment
1 points • chip-sandwich

Looking forward to a python course on coursera.

Looking to learn overall basics + grab some context of data science using python.

This my shortlist -

  1. https://www.coursera.org/learn/python-crash-course?specialization=google-it-automation#syllabus

  2. https://www.coursera.org/learn/python-data-analysis?specialization=data-science-python#syllabus

Any suggestions on which of the above should I choose? I don't seem to understand the difference between these (as I am yet to start with Python)

r/datascience • comment
1 points • Fantastic_Horse1454

This is a 5 Course specialization offered by University of Michigan, this is specially focused on data science https://www.coursera.org/learn/python-data-analysis

A more general course regarding Neural networks and deeplearning would be https://www.coursera.org/specializations/deep-learning this is offered by deeplearning.ai

This is a five course specialization as well.

The courses offered by IBM https://www.coursera.org/specializations/introduction-data-science is a more basic fundamentals specialization

Based on your comfort level choose a specialization.

if you are running short on time, streamline to a few courses of the specialization (Usually the starting Courses)

r/learnpython • comment
1 points • ASIC_SP

https://www.dunderdata.com/master-data-analysis-with-python and https://www.coursera.org/learn/python-data-analysis might fit

See also:

r/statistics • comment
1 points • sparedOstrich

On the contrary to what people on willbell thread are saying, I have a BTech in Electronics and Communication engineering. I have learnt some coding languages like C, C++, python, along with coding languages in ECE like assembly, Arduino. I have used them to develop codecs and for audio signal processing. I think learning languages gives you an understanding of how you can use a machine to do what you desire.

So you can start with a MOOC like Chuck Severance's Programming for everybody. You can even audit it. Or you can use Youtube series like Bucky Robert's Python Programming Tutorials (OLD version, Python 2) or Python 3.4 Programming Tutorials. You can use this to learn python, in general, to do whatever you want. And then " you learn one statistic concept and then see how you can program the concept in r or python ".

Or if you want to learn statistics-intensive way, you can find MOOCs like

a. https://www.coursera.org/learn/python-data-analysis

b. https://www.coursera.org/specializations/statistics

c. https://www.edx.org/course/statistics-and-r

d. https://www.edx.org/course/probability-and-statistics-in-data-science-using-python-0

Now I am doing BSc in Statistics, Maths and Computer Science. (programming then statistics) order has benefitted me. I could easily learn other languages like Maxima or Scilab. I also have the option of implementing the code in a language I already know.

I personally feel "it's easier to teach a software developer statistics than it is to teach a statistician to program" - google or Amazon, as I see some of the old stats professors and research scholars at my University are devoid of programming skills and find it hard sometimes.