IBM Data Science

Codecademy is generally good for syntax, but not much else; the content is quite shallow.

DataCamp is slick, and does go into more detail, but what you're getting is the appearance of learning, not the real thing. It's basically just fill-in-the-blanks.

I've heard good things about DataQuest, but haven't tried it myself. If you're looking for a single course to cover a wide base, then the one that I think gives the most solid grounding is IBM's Professional Certificate on Coursera.

I honestly don't know. I'm a computer science major that stumbled my way into the field after getting out of IT troubleshooting/support. I don't really know the best traditional path.

I have heard good things from colleagues about the IBM Data Science Certificate and Google Data Analytics certificates but I can't vouch for them personally. They seem hightly rated so maybe check those out if you can.

My main suggestion would be to pick up some basic SQL and/or Python classes to learn the fundamentals if you already haven't. A lot of other apps/programs are company specific but SQL and Python are useful regardless of where you work.

is the IBM Data Science Professional Certificate worth the investment?

I am a university scm student but my real interest lies in data analytics and business development. I really want to teach myself how to code, specifically Python (as it appears to be pretty universally recognized and used). this course looks legit, plus being able to put the "official certification" on my resume is huge, but its not free ($35/month, website says course takes \~3 months to finish @ 12 hours/week)

is the course worth the investment

here is the link for reference: https://www.coursera.org/professional-certificates/ibm-data-science

Thoughts on Coursera

Long time reader, maybe second/third time poster.

Recently I've decided to work on my programming skills. I'm currently in CC (or was) and will start (finish up) at a regular 4 year in the fall studying computer science. tbh I'm about 2-3 years out from graduation, but I'd like to learn how to program, so that when I'm out of school, I'm -somewhat- ready to go (maybe even during school, try to get an internship/co-op so I don't have to do retail sales like I'm doing now).

On Coursera, I came across an "IBM Data Science" certification( https://www.coursera.org/professional-certificates/ibm-data-science ). Essentially it's take a few different courses (basics, SQL, focus on Python -so it seems) and bam I get a cert and I can put it on my Linkedin. My question is:

1. Is it worth it? It would cost around $40/month and the pace is how I quickly/slowly I go through it (it est. 3 months).
2. If it's not, is there anything on Coursera worthwhile?
3. If not, where do you recommend I begin? I've done Codecademy and felt like I was just memorizing and typing out what I saw... not actually learning anything (if that makes sense). There was one like Codecademy too, except it's free. But I kind of got that same experience from it.

Thanks!

O curso da IBM no coursera é muito bom e passa por cima de todos tópicos, e já vai garantir um certificado com IBM no nome.

Se eu não me engano sai por volta dos R$250/mês. https://www.coursera.org/professional-certificates/ibm-data-science

Where exactly do I stand on the learning staircase? What do I do next?

Hey r/learnpython,

I have been exposed to python for about 2 years now but I'm not sure how much I actually know in regards to getting a job as a developer.

​

Tl;dr I know a lot of things at a very basic level but how do I take my knowledge to a level which is acceptable in industry.

​

I got taught python when I started university so that we could have more professional graphs for our lab reports. We got taught the basics like loops, conditionals, slicing, functions, scipy for data analysis and matplotlib for graphs then it was object-oriented programming for an assignment.

I applied to about 20 summer internships for software engineering mainly but got rejected by all of them. Just before summer began I applied to a company as a last-ditch effort where it was mainly cleaning data but it still used python and I got it (they didn't have any other applicants).

I've been working part-time for the last 2 and a half months and I did some web scraping with beautiful soup. Then it turned out that the company names we needed from the scraping would need to be extracted from google searches and so I read some blogs and copied their code on natural language processing to help me. Now I'm automating some Tableau workbooks which has xml manipulation. Through all of this, I learned a lot but it was still just me using for loops and pandas.

I've built a basic website for a friends ebay business to learn django but it was never deployed (it just linked the product to the relevant ebay page) since it didn't compare to professional level websites you see normally. I'm doing a data science course on Coursera ( https://www.coursera.org/professional-certificates/ibm-data-science ) but it doesn't really explain much and just tells you to use this function because it does what you want. I still understand it since I've coded for this long and the data analysis makes sense because I'm studying Physics.

Sure my CV can now say NLP, machine learning, Tableau, SQL, data analysis but my knowledge is shallow. Heck, I didn't know what a dictionary was a year and a half after learning python.

So what can I do to cement my foundations and expand what I know? What will help me get a job when I graduate next year? I want to either end up in data science or software engineering but I'm leaning more towards software engineering.

I came from a marketing background and wanted to hop into the DS field. Took this ibm coursera course to learn and see if I really like it. Course is in python, I think it shouldn’t be that difficult for you to try as a primer since you’ve a bit of programming background.

Starting at your last paragraph, one of my chief motivations for doing the DM/DA track is it included a class on machine learning which I think is a crucial skill. I am looking at the IBM Data Science Professional certificate (https://www.coursera.org/professional-certificates/ibm-data-science#courses) and I am pretty sure the Udacity nanodegree (which is part of this program) is similar. For example, in course 2 they mention Jupyter notebooks, python, and R. Right before I answered this I was working in a Jupyter notebook using Python (Pandas, Seaborn, and Numpy) so I think there will be a fair amount of crossover. Personally I was perusing the machine learning certs in the Azure track with Microsoft yesterday.

I would say that, with a bit of qualification, the courses are designed assuming you know nothing. The qualification is that it ramps up quickly to the point where the hand-holding turns into a friendly wave and a 'good luck' as you paddle upstream. If you were to do this, I suggest working with your mentor to structure your schedule in a way that makes sense knowing that you are starting really fresh.

The last thing I want to mention is this is 100% self motivated learning. It is really more of a correspondence college. We can't say that out loud because then you couldn't get federal student aide, but for all intents and purposes it is correspondence based. You are given a bunch of materials which cover 80% of the topic, supplementary materials to cover another 10%, and then Google/YouTube/StackExchange. You need to be ready and willing to research on your own. CIs are available and helpful but when it comes down to brass tacks it is about you, the material, and the PAs.

You might find this interesting

https://www.coursera.org/professional-certificates/ibm-data-science?action=enroll#courses

I took the IBM professional certification for Data science from Coursera! I found it helpful and affordable with lots of online resources to help you learn at your own pace. I also learned and refreshed python basics from Automating the basic stuff with python on YouTube and Udemy.

Codecademy has free courses you can get started in practicing and learning the basics of the language

https://www.coursera.org/professional-certificates/ibm-data-science

https://www.coursera.org/professional-certificates/ibm-data-science I have a bachelor's in Computer science and I want to get a job in data science field. Will this course give me enough knowledge and experience to land a job.

This is the one

I was thinking of this. Not sure of its general reputation: https://www.coursera.org/professional-certificates/ibm-data-science

Most work from home jobs that I have seen in the country are skill based ones and mostly tech related. That too its friends or friends of friends who have been needing something like a software or a website. There were a few posts regarding the posters wanting to learn Nepali, maybe if you can talk to them and draw up a curriculum they'd be happy to pay you if you don't charge them too expensively.

Academic ghostwriting would be nice to casually mention in an interview in the future. But, you can get certified with the courses you take. The course I mentioned above has a free certification. This one from IBM which is pretty popular has a certification at the end of the course too. ~~I think the course is free right now, but you might have to pay for the certification, I am not too sure about that.~~

https://www.coursera.org/professional-certificates/ibm-data-science?aid=true

Edit: The there is a 7day free trial, it is $39 per month. The course takes 3 months to complete but you can complete it in a month too.

Gotovo uvijek imaju popuste i svi se kreću oko 80-90%.

Kvaliteta jako varira. Zato je najbolje prvo pogledati ocjene i recenzije (po internetu) te pogledati preview video materijale kako bi se uvjerila da je to profesionalno odrađeno.

Certifikat možeš staviti na cv ili na linkedin, no nema težinu u odnosu na, primjerice sveučilišnu diplomu. Ne šteti ubaciti, više da pokažeš poslodavcu da konstantno ulažeš u svoje znanje.

Inače, imaš na courseri od ibm-a data science tečaj koji nudi besplatne materijale za učenje. Za rješavanje ispita te dobivanje certifikata potrebno je izdvojiti 39$ (mjesečno, ovisno o tome koliko vremena ti treba za položiti sve). Usporedi pa provjeri koji ti više odgovara.

This is not a master's programme, but it will give you broad, comprehensive introductory knowledge about data science, and is relatively cheap. IBM Data Science Professional Certificate contains 9 courses that cover all aspects of data science and do not require any background knowledge whatsoever. There are lectures, quizzes and hands-on labs. You can finish it in about a month or two if you give it enough time, and then you would be prepared for more advanced materials. Btw, Coursera also offers master's programmes but I am not sure how much they cost, you could check them out

IBM coursera

Yeah, you can cancel after that and be done with it, but they have other useful courses/certifications on there, as well.

Qualcuno ha mai seguito corsi su Coursera?

Quanto sono validi/apprezzati/calcolati una volta inseriti nel curriculum?

Il corso in questione è questo

https://www.coursera.org/professional-certificates/ibm-data-science

The specific cert doesn't really matter, but I've heard that the one from IBM is pretty decent to start, https://www.coursera.org/professional-certificates/ibm-data-science

Keep in mind that if you don't have ANY bachelor level experience it is unlikely the MITX program will accept you, as it is a graduate level (above bachelors) program.

The IBM Data science certificate is not enough to get a job. Trust me, I tried. I have that certificate myself through Coursera:

https://www.coursera.org/professional-certificates/ibm-data-science

Not sure about the JHU certificate, but I suspect the same.

You need to get an online degree. It would be much cheaper to go to a real university. Online Bootcamp is possible, but it'd cost MORE than a real university, and you cannot get financial aid for bootcamp unlike for university or college.

Yes sure.
IBM - https://www.coursera.org/professional-certificates/ibm-data-science It is complete data science certification.

Right now I'm taking this course:

https://www.coursera.org/professional-certificates/ibm-data-science

I did that to see if I really liked DS and was willing to change career, and I am. I have been looking for an MSc in Data Science, or and MSc in Artificial Intelligence.

On the other hand, I have a close friend that works as a Data Scientist. He is also an engineer (civil) and is convinced I don't need to take an MSc to get a data scientist job, because he was able to, and that I will learn more in an actual job. According to him, because we already know all the bases (except programming), we would be more than ready for a data job after learning how to program and getting familiar with all the software you use for DS.

So I really haven't decided yet. For now, I will continue on the course, which is really good for foundations, and am already applying for DS jobs. If I can get a job, I probably won't take the MSc, or I will look for a deeper MSc, like machine learning or deep learning. If I can't get a job in DS in the near future, I will definitely enroll for an MSc.

Good luck!

If you are looking for certifications, Coursera offers a IBM data science certificate. I don't know if that will make you stand out in the eyes of HR.

I'm positive i want to start a career as a data scientist, and i'm beggining from zero.
I found this courses that apeal me, but as i cant judge them on knowledge i wanted your opinion
https://www.coursera.org/professional-certificates/ibm-data-science
https://www.coursera.org/specializations/python
and theres also Dataquest and datacamp. My objective is to learn and to build a portfolio of works so i can make my career change as soon as possible.
I have 24 years old, highschool teacher, and have some basic computing stuff on my habilities but not programming.
For what ive been reading this week, it hits me that i least need to know SQL and Python.
what do you recomend me? Should i start as a data analyst and then try to transition to data science or should only search data science jobs.
Sorry for all my doubts!!

Si sabes ingles te recomiendo Coursera, los cursos son pagos, pero todos tienen la opción de aplicar a una beca (llenas un formulario diciendo que no podes pagar el curso). Yo ya vengo haciendo varios cursos completamente gratis, termino uno y ya aplico para otro.

Para lo que vos pedís por ejemplo tenes User Interface Design Specialization brindado por la Universidad de Minesota.

Lo bueno de coursera es que muchos cursos son dados por grandes universidades, incluso podes hacer certificaciones con peso a nivel internacional, como por ejemplo el curso de data science de IBM.

IBM data science course So hey guys I have no past coding experience and learning python alongside. How will this course be for learning the subject. Will I be actually learning anything as much as it's taught in a degree? Or I should just treat it as an introduction to the subject and apply for a master's after getting that intro and feeling intrested in the subject. It said u could land an entry level data science job after this course so it would be nice if I could explore the subject for some time on my own and self teach myself because that's where the freedom lies. Also I don't have a super good profile to land a nice college abroad rn. So I thought maybe getting some certifications and doing a few projects will help me land a better place to study in. Let me know your views. EDIT- if that Google photos link doesn't work this is the original link to the course https://www.coursera.org/professional-certificates/ibm-data-science

Career paths utilizing Python?

Hi All!

I'm looking for some assistance on the path to becoming job ready coding with Python. Thought it would be helpful to give a background on my progress. Thanks!

A few month ago I quit my sales job at a large recruitment website, and am now looking to make the transition into Software Development, Data Analysis, etc.

Reason for the change - The sales job I was at for four years was too volatile in terms of compensation, and the stress of always chasing a number was taking its toll. Looking into coding I was amazed at how many different career paths there were. I have always loved learning new things and continuing to expand my knowledge, which seems like a good trait to have for coding. After a few basic courses on Linkedin Learning I was hooked.

What I have so far - I took a few basic courses on Linkedin Learning before seeing if Python was something I wanted to invest time and money into. Once I saw it definitely was, I enrolled in the Coursera "Python For Everybody" Specialization. I am on the third class of five, "Using Python to access Web Data."

What's Next - After completing this specialization I was planning on taking IBM Data Science Professional Certificate and then Excel to MySQL: Analytic Techniques for Business Specialization. I also plan on using GitHub.

Questions - Where do these 3 completed courses put me realistically in terms of being job ready? Are there any good companies that offer paid training? What other resources should I be using to get job ready? How long does a transition like mine typically take? What job titles are good entry level roles? Any and all advice is appreciated! PM's are welcome too!

Such empty! Here's a question for those in ML/AI/data science:
I'm compensating for my degree not having AI/ML modules with Coursera and I'm currently on the advanced data science specialization from IBM but they also offer a mixed level professional certification. Are they equivalent or is one better than the other for my case of wanting to get into AI/data science jobs? Looks to me like the 'advanced' is more suited for someone already experienced with the topics and the 'professional' one spends ages teaching people basics of coding and data and whatnot so could include needless repetition of known topics for me graduating with MEng SWE in July.
How would employers/recruiters see the two in comparison?

i am doing the IBM data science professional certificate under which there are nine courses , does it make sense to do that , i am currently studying engineering and am doing this since my country is on lockdown and i have else to do but i have always had an intrest in data science , here is the link for reference

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https://www.coursera.org/professional-certificates/ibm-data-science#courses

I'm a career changer (worked in B2B sales for ten years) who just passed exam P and is looking to get an entry level job soon, likely later this year after passing FM.

Does anyone have any thoughts on the data science certifications available via apps like Coursera and Udemy? For example this one https://www.coursera.org/professional-certificates/ibm-data-science

I'm currently doing temp work equivalent to database administration in an attempt to build some experience and am concerned about standing out among other applicants this fall. If it helps I already know VBA, pivot tables, and a bunch of Excel tricks, just don't know if two exams and a bit of semi-relevant experience will be enough.

Hi, I'm a Software Engineer with my Bachelors in CS looking at courses in AI but, aren't sure whether to go with a Data Science or Machine Learning Course. I see people with no programming experience going for Data Scientist jobs so, I want to play to my strengths & utilize my programming background. That said, I'm new to AI all together and, aren't sure if I'll need to learn the data mining & visualization skills from a Data Science Course.

Background: Career wise, I'm in a pretty desperate situation with little/no work history and, need to get my foot in the door.

Looking at these courses

https://www.coursera.org/learn/machine-learning

https://www.coursera.org/professional-certificates/ibm-data-science

I have been enjoying www.datacamp.com 's course work. I also completed the IBM professional data science certification program through coursera as well.

I am surprised no one has mentioned it but in my opinion, IBM Data Science Professional Cert is an all-around great option. Its $40 a month, there's a free trial, you can also audit all the courses if you want. So you can see what you are going to do before you decide if it's worth it for you or not. And if at any point math is an issue Khan Academy is a no brainer.

It says in the course name it is Python Data Science Certificate. It's not just geared towards it, it's 100% focusing on the subject.

I took IBM Data Science Professional course on Coursera (https://www.coursera.org/professional-certificates/ibm-data-science) personally I'm not really a fan. Not sure how similar the EdX is but they're both IBM.

The Coursera courses tried to sound academic to the point it's really... bland... and did a terrible job explaining things. I felt one's suppose to already have learnt most of the topics of the courses from somewhere else before just stream roll this for the cert (I have 10+ years experience with Python and database prior to enrolling).

Tried any of the ML or data science classes for python ?

an example

https://www.coursera.org/professional-certificates/ibm-data-science

Hello, I am looking for an online course at coursera for Machine learning. I have completed Jose Portilla course from udemy and many online youtube courses. Now I am looking for a course that I can add in my resume. Please suggest a course that you find really helpful for Machine learning that uses Python.

I am looking at following two courses:

1. University of michigan course: https://www.coursera.org/specializations/data-science-python

2. IBM course: https://www.coursera.org/professional-certificates/ibm-data-science

As coursera needs investment I want to invest in a good course as I am limited on my budget too. Thanks!!

Happy to help. I have been looking at making the move recently so I’ve been talking to recruiters in my own company (and in others) and asking what they look for on resumes. They said ideally a master in CompSci / Data Science, but a certification and a portfolio can be competitive as well.

https://www.coursera.org/professional-certificates/ibm-data-science?utm_source=gg&utm_medium=sem&campaignid=1876641588&utm_campaign=10-IBM-Data-Science-US&utm_content=10-IBM-Data-Science-US&adgroupid=117357906417&device=m&keyword=&matchtype=b&network=g&devicemodel=&adpostion=&creativeid=507196710149&hide_mobile_promo&gclid=Cj0KCQjwktKFBhCkARIsAJeDT0gkvN6PyaJHMnfghr9tEoHn_bJ_oy7nJ1zQuid3ePgm7Uf6SLk3nn0aAoygEALw_wcB

That was the program I looked at from coursera, very cost effective. I’m currently going through the AI program at Columbia University Online, not very cost effective but has a fancy label on it.

https://requestinfo.ai.engineering.columbia.edu/index-m.html?experimentid=20003834140&x=OFB&s=search_brand_google&l=GGL%7CCU-CAI%7CBRD%7CSEM%7CTier0%7CBroad%7CSTD%7CEDU%7COffline%7CArtificial-Intelligence&ef_id=c:500389538862_d:m_n:g_ti:kwd-843001458158&gclid=Cj0KCQjwktKFBhCkARIsAJeDT0ipveo00W4xno0-zde0l03n6kybU0xL1icauU_2tlDIrHpit-u9LGsaArSnEALw_wcB&gclsrc=aw.ds

I am currently doing the University of Michigan Applied Data Science Specialization.

Reviews so far:

1. Introduction - Really damn good. Cleared up my concepts really well. They recommended some experience in python beforehand, but I still did well regardless and picked it along the way from the course hints, and some manual searching. (I have a background in CS, and I am a nerd, so consider that.)
2. Matplotlib - I didn't enjoy the tutorials as much as the first course. Went from 0 to 100 really quick. The questions seemed a bit tough due to the same reason, but the quality of the questions and the insights provided in the lectures was really good. Just do some external research and documentation reading, use StackOverflow.
3. Applied Machine Learning - Currently in Week 2. Loving it so far! It's a little longer than the previous ones, and the pacing is really great, cleared up the basics really well as well.

As for the rest, I'll update this comment and make a post when I am done.

P.S. Personally, I don't recommend the others like IBM Data Science, or the Johns Hopkins Data Science one because:

1) I did a little bit of the IBM course on EDx, and the quality was lacking. Not to mention IBM Watson Cloud (where you'll spend a lotta time with the IBM Course was kinda inconvenient.)

2) The Johns Hopkins University course is in R, and I prefer Python for too many reasons. (and I HIGHLY recommend starting out with Python instead of R.)

If you are into the heavy math I recommend this one with Andrew Ng. I think he uses Octave instead of Python but good nonetheless. https://www.coursera.org/learn/machine-learning

This one is a bit simpler, good for beginners, and uses Python. If I remember correctly they even provide code you can play with. https://www.coursera.org/professional-certificates/ibm-data-science?

I would say that logical problem-solving skills and statistics are good skills to have for either.

There are free courses available:

https://www.coursera.org/specializations/wharton-fintech

https://www.coursera.org/professional-certificates/ibm-data-science

These will give you a feel for what the job entails.

Hi, I guess this is a fairly frequent question, although with million different answers, and that's why I'm posting it again: What DS course/specialization to take? I'm talking about a multiple-month commitment, preferably, not a few week 'crash' course.

I'm down to following: https://www.coursera.org/professional-certificates/ibm-data-science?edocomorp=ibmdatascience10&ranMID=40328&ranEAID=vedj0cWlu2Y&ranSiteID=vedj0cWlu2Y-XTViE4Ux6h_ifTELl_ssRA&siteID=vedj0cWlu2Y-XTViE4Ux6h_ifTELl_ssRA&utm_content=10&utm_medium=partners&utm_source=linkshare&utm_campaign=vedj0cWlu2Y

https://www.edx.org/micromasters/mitx-statistics-and-data-science?source=aw&awc=6798_1584892487_ae5dc685ab539fe4dda0c4f2a39e5f3d&utm_source=aw&utm_medium=affiliate_partner&utm_content=text-link&utm_term=427859_Digital+Defynd

https://www.edx.org/professional-certificate/harvardx-data-science?source=aw&awc=6798_1584892490_8bd1685336c08b8eb150762fc8d24175&utm_source=aw&utm_medium=affiliate_partner&utm_content=text-link&utm_term=427859_Digital+Defynd

and Udacity courses.

Any suggestions? (CS background, ~6 yrs of experience, some statistics exposure, haven't done anything since Uni, basically).

I'm currently going through IBM's Data Science Professional Certificate, but more for economic analyses. It's been good so far. Udemy has several Python for Finance courses I'll be taking after IBM's, but you should also check out Columbia J School's Lede Program for data journalism (here's the actual course page). It's focused more on visualization and you have to teach yourself through it, but it'll teach you about several data viz and programming tools.

Look into data analysis, and business analytics. CompTIA is premiering a certification around it but with you're experience in Finance you'd be a good fit. You'll take a pay cut most likely down to like $60-70K but you might be able to find a role in your company already and lessen that blow completely.

• Become a Data Analyst https://youtu.be/5MZo2RoS8Yo

Skills you'll need are SQL, Python, and a BI software like Tableau or Power BI. You could also learn a basic cloud platform to just be able to be aware of that.

• Data Specialist Roadmap https://www.comptia.org/content/it-careers-path-roadmap/data-specialist

• https://www.udacity.com/course/data-analyst-nanodegree--nd002

• CompTia Data https://www.comptia.org/certifications/data

• Microsoft PowerBI Fundamentals Certification https://docs.microsoft.com/en-us/learn/certifications/power-platform-fundamentals/

• Coursera IBM Data Analytics https://www.coursera.org/professional-certificates/ibm-data-science

• Azure Data Fundamentals https://docs.microsoft.com/en-us/learn/certifications/azure-data-fundamentals/

Your local college may also have a certificate program that can be done in a semester or two for data analytics. Those are often nice because it can be from a well know University which has a good reputation and reach that wants local professionals to have the proper training. Here are some examples of that:

I was looking at these programs off Coursera:

• Hopkins (https://www.coursera.org/specializations/jhu-data-science)

• IBM Intro (https://www.coursera.org/specializations/introduction-data-science)

• Michigan (https://www.coursera.org/specializations/data-science-python)

• IBM DS (https://www.coursera.org/professional-certificates/ibm-data-science)

They have various estimated time lengths, which is understandable since they seem like they're pretty intense courses. I think I'd be able to handle finishing them faster than the estimated (or at least some more immediately relevant sections) since I've been juggling working full-time and being a full-time MS student... But idk.

Are there other Intro to DS courses you'd recommend? There are some other I've found here-and-there online, but I don't know how well they prepare people...

I am currently working as a financial auditor, and looking into changing career to data science (or data analyst). I have a bachelor's degree in Economics and Business Administration and a master's degree in Business Administration and Auditing.

I have taken some Python courses on Udemy (Jose Portilla) and Edx (MIT 6.00.1x), as well as some SQL courses. I would say im very comfortable in SQL, and decent at python. I am also very comfortable with math and statistics.

How do I showcase my skills in data science? I was thinking maybe making a personal website portfolio, and then have a section for python, a section for data science etc. In each section, let's take data science section as an example, I'll have a video of me analysing some random dataset from kaggle, cleaning it, and train test splitting it. In the python section I'll have some links to some github projects made in python (Hangman, a calculator, a to-do list etc).

Further more, I was thinking of taking these 3 specializations on coursera to supplement my lack of Data Science degree to put on my CV:

IBM Data Science Professional Certificate

Deep Learning Specialization

Data Visualization with Tableau Specialization

I know coursera specilizations dont weigh as much as a real course taken in a university, but I am spending around 3 hours on these courses and projects in weekdays, and 6-8 in the weekend, but clueless how I show my dedication in learning this to a hiring firm.

I am following this roadmap: Data Science Roadmap on GitHub, and I am familiar with all the terms used here.

Would like some feedback on this plan, or if it's unrealistic changing career. My goal is to change career in approx 1.5 years time.

I can also add, that I've been thinking about enrolling in a Computer Science degree. I wont attend lectures, only exams (will still keep my full-time job as an auditor).

And yes, I am willing to throw away a personal life for a year or two. :)

I am a CS student in my final year and I have some skills in python since I am currently working as a testautomation engineer in python and I also finished a Deep Learning class at my university which is heavily based on the Andrew Ng course(almost the same). I have fairly deep knowledge in maths so I don't need courses created for delivery guys who want to change their carreer.
Which specialization should I choose from theese? Can you maybe recommend me something better from coursera?
https://www.coursera.org/specializations/jhu-data-science

https://www.coursera.org/professional-certificates/ibm-data-science

JHU is top rated on most sites but I'm afraid of R since I think I could do better in python even if I have a statistics class with R. The IBM one seems prettier for me but I haven't seen ratings on major forums, idk why.
Thanks for your help!

Hello, I need some advice on how to gather formal education on Data Science and Visualization, Machine Learning. I finished studying Engineering in CS long time ago in 2003, and I've been working as computing manager in an interdisciplinary climate research center since 2014.. In practice I think I already do data science stuff (a lot of python, pandas, numpy, large puntual and surface datasets, some visualization, etc.). But I would really like to get some formal education on DS (both for the CV as for getting in depth and current knowledge from great teachers), and I see way too many options..

I cannot take a full time Master as I'd love, since I already have a full time job and kids and a house to take care of during pandemics, but I can take a structured course or program that takes some 8-10 hours a week ..

I found these two on MIT, others on coursera, edx, etc. and many many more ... :

• MITx MicroMasters in Statistics and Data Science (1.2 year ~1000 USD) https://micromasters.mit.edu/ds/ * MIT Professional Applied Data Science Program (12 weeks, ~3400 USD) O_o a bit expensive right? https://professional.mit.edu/course-catalog/applied-data-science-program

• Coursera The IBM one https://www.coursera.org/professional-certificates/ibm-data-science * The John Hopkins University ... https://www.coursera.org/specializations/jhu-data-science

Is there any formal course or institution specialized on DS that would really deepen my knowledge, help me get new insight for my current job and make a good reference in my CV? :)

Many thanks in advance

https://www.coursera.org/professional-certificates/google-data-analytics

https://www.coursera.org/professional-certificates/preparing-for-google-cloud-machine-learning-engineer-professional-certificate

https://www.coursera.org/professional-certificates/ibm-data-science?

do these 3 for a LOT less money and you'll be far better off

then add

https://www.coursera.org/specializations/mathematics-for-data-science

https://www.coursera.org/specializations/mathematics-machine-learning

Hello everyone,

I'm trying to get into a data science from from a Electrical Engineering background.

I recently graduated and have experience coding in matlab and python (and others). I've completed a couple of the 365datascience courses that were free for a while as well as some of the kaggle micro courses.

I'm trying to find something a little more challenging and have been looking at Coursera specializations for way too long now, seems like everyone of those has one major drawback and I'm having a lot of trouble deciding between them. In short:

- John hopkins : Uses OCTAVE and from what I understand Python is the way to go.

- Standford (Andrew NG) : Said to be very theoretical, doesn't prepare you to make your own projects.

- U Michigan: Said to be outdated, problems with exercises scoring, bad reviews all around.

(This information is based of reading reviews and reddit posts so I may well be wrong. )

I've also found University of Washington's and IBM's that seem to have good reviews but I'm not sure nonetheless.

Can anyone point me towards the best one of these (or others) considering I have previous coding experience and know some of the very (very) basics of Python DS libraries?